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Killexams : IBM Intelligence study help - BingNews https://killexams.com/pass4sure/exam-detail/M2020-645 Search results Killexams : IBM Intelligence study help - BingNews https://killexams.com/pass4sure/exam-detail/M2020-645 https://killexams.com/exam_list/IBM Killexams : Climate risks are a major business threat – here’s how AI can help

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When Hurricane Harvey struck southeast Texas in 2017, it caused $125 billion in economic damages. A recent assessment of local businesses in the area found that 90% lost revenue in the five figure range due to employee disruptions, lower customer demand, utility outages, and/or supply chain issues. Those that suffered property damage experienced compounded losses with parts of the business being shuttered for weeks and months at a time until repairs could be made.

Since 2017 there’s been an average of 17.8 weather/climate disaster events per year in the US alone. In fact, just in 2022, there have been 9 weather/climate disaster events with losses exceeding $1 billion each.

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Rising temperatures, floods, droughts, wildfires and other offshoots of climate change present major challenges to economies and communities around the world. As a result, businesses are feeling the pressure to adopt new strategies to reduce their carbon footprint in the long term. But many have yet to prepare themselves for the impact that climate change can and will have on their operations.

Many companies are already feeling the heat, experiencing climate-related damage to their assets, and disruptions to supply chains. According to a exact report from the World Economic Forum, global heat waves and other extreme weather conditions could also cause a spike in the cost of raw materials for production, which would inevitably present huge revenue losses across sectors.

With such a high risk the question is, why have so few businesses prepared for the potential effects of climate change?

The complicated world of climate data

While an overwhelming majority of businesses have plans in place for cyberattacks and Covid-19, the World Economic Forum’s Global Risks Report 2021 found that extreme weather, climate action failure, and human-led environmental damage are in fact the top three most likely risks for businesses over the next ten years. Yet, many still don’t have clear strategies and risk analyses in place to guide decision-making.

“One of the major challenges for general business operations is that companies are still getting familiar with the many variables involved in collecting climate data,” says Miguel Modestino, an Associate Professor and Director of the Sustainable Engineering Initiative at New York University’s Tandon School of Engineering.

Indeed, tracking climate data requires historical weather data, sensors, intensive manual labor, computing power, as well as internal climate and data science skills. Even if you can capture this data, the problem then lies in being able to combine and compare all of the different variables to create one big picture of what’s happening on the ground.

Geospatial analysis is key to unlocking the potential of climate data.

According to Hendrik Hamann, Chief Scientist for Future of Climate at IBM:

In order to understand the economic damage of a flood, for example, one has to combine flood risk information with road and elevation information, or many other sets of information in order to understand its overall impact on business.

Once you capture climate data, the next challenge lies in understanding how to extract valuable insights from this information and how to actually apply them to business operations.

An EY study found that only 41% of organizations conduct scenario analysis of climate-related risks. This means that, in the increasingly likely event that a weather-related disaster does occur, many organizations don’t have a clear picture of what the potential risks, costs, and action plan would be. Without this understanding, prevention measures, budgeting, and other essential decision-making becomes a guessing game for business leaders who need to present this information to investors and other stakeholders.

“We’re sitting on this mountain of information, yet we’re only looking at the tip of the iceberg. There’s all of this high value data out there including observations about our planet Earth, but we’re not taking advantage of that to make better decisions,” Hamann explains.

Curbing climate impact with new tech

Geospatial analysis is key to unlocking the potential of climate data – but these insights are based on massive amounts of complex and disparate data types, including satellite, GPS, and historical weather data and imagery. The use of AI and machine learning holds great potential for helping businesses access and analyze these datasets in a way that is more manageable.

“With AI, companies can also develop advanced models that use machine learning to really quickly calculate the environmental impact of a particular set of business operations,” Modestino explains. “Having efficient machine learning models can help optimize their operations to maximize profit while maintaining a particular climate target.”

IBM recently launched its Environmental Intelligence Suite (EIS) which brings together a wide variety of weather, climate, AI and operational technologies into a single software as a service offering that companies can use to better plan for and respond to climate risks.

Map out the potential risks across your business’ operations.

A unique capability within this suite is a geospatial analytics engine developed within IBM Research, which helps provide insights on complex geospatial datasets in a way that can be more easily accessed and combined with broader business technologies and data. This can help companies efficiently understand and analyze geospatial data to predict the risk and potential impact of upcoming climate and weather threats to their business.

“When we think about satellite observations of the earth, we think, ‘how can it be analyzed?’, or ‘how can we understand natural phenomena like tree growth, vegetation growth and how much carbon is being stored in it,” Hamann says. “This is all covered by geospatial analytics.”

For instance, where a utility company has tens of thousands of substations which are used to supply electricity to customers, climate impact might supply rise to the following questions: Which of our asset locations are at the biggest risk? How can those sites be prepared to withstand the impact? How will investments be allocated? The ability to analyze geospatial data keeps companies informed about potential risks and prioritizes them while making actionable business decisions.

How to get started

It’s clear that developing clear strategies for extreme weather and climate change is no longer just for a rainy day. They will become key to enabling businesses to function, operate, and even grow.

The first step is to map out the potential risks across your business’ operations, from resource scarcity to the potential for logistics disruptions.

The next step is to consider the potential opportunities. How might changing your sourcing/production/distribution strategies lower your risk for climate change disruptions and boost your bottom line? How might these changes also contribute to your company’s longer-term sustainability strategies?

As it continues to affect populations all over the world, it’s also becoming increasingly clear that a warming planet poses a looming threat to business operations. Advanced technologies and methods, like geospatial analysis, are still in early stages and therefore we expect to see a lot more room for innovation in the coming years.

Tue, 04 Oct 2022 20:48:00 -0500 en text/html https://thenextweb.com/news/climate-risks-major-business-threat-how-ai-can-help
Killexams : Biden: IBM investment to help in tech competition with China

POUGHKEEPSIE, N.Y. (AP) — President Joe Biden predicted Thursday a $20 billion investment by IBM in New York's Hudson River Valley will help supply the United States a technological edge against China, hailing the expansion during an appearance with two House Democrats in competitive races in next month's critical elections.

The president cited IBM's commitment as part of a larger manufacturing boom, spurred by this summer's passage of a $280 billion measure intended to boost the semiconductor industry and scientific research. That legislation was needed for national and economic security, Biden said in Poughkeepsie, adding that “the Chinese Communist Party actively lobbied against” it.

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“The United States has to lead the world of producing these advanced chips — this law is going to make sure that it will,” Biden said.

The speech was part of a whirlwind trip that focused heavily on campaigning and included two fundraising events. During one, he warned that Russian President Vladimir Putin's threat about using nuclear weapons as his Ukrainian invasion has floundered is the most severe “threat of Armageddon” since Cuban Missile Crisis in 1962.

Democratic candidates have largely avoided election-year appearances with Biden, whose approval ratings remain underwater. Bucking that trend in New York were Reps. Sean Patrick Maloney and Pat Ryan, who attended the president's remarks at IBM.

The lawmakers, along with Democratic Gov. Kathy Hochul, greeted Biden upon his arrival at Stewart Air National Guard Base.

“When I heard @POTUS was looking to see the benefits of the CHIPS & Science Act first-hand, I told him that the Hudson Valley was the perfect place,” Maloney wrote Wednesday on Twitter. “I’m thrilled to host him in Poughkeepsie this week to celebrate the major wins and good-paying jobs we are delivering here in NY.”

The CHIPS and Science Act, which Biden signed in August, was a rare bill for which the president was able to win bipartisan support.

IBM's $20 billion investment over the next decade is intended to bolster research and development and the manufacture of semiconductors, mainframe technology, artificial intelligence and quantum computing.

“As we tackle large-scale technological challenges in climate, energy, transportation and more, we must continue to invest in innovation and discovery — because advanced technologies are key to solving these problems and driving economic prosperity, including better jobs, for millions of Americans," said Arvind Krishna, IBM's chairman and CEO.

IBM's commitment comes on the heels of chipmaker Micron announcing this week an investment of up to $100 billion over the next 20-plus years to build a plant in upstate New York that could create 9,000 factory jobs. In his remarks, Biden also celebrated Intel's plant groundbreaking in Ohio and an investment by WolfSpeed for chip production in North Carolina.

Maloney, chairman of the Democratic congressional campaign fundraising arm, is running against Republican state Assemblyman Mike Lawler in the 17th Congressional District. Ryan faces state Assemblyman Colin Schmitt in the 18th District.

The boundaries of most New York districts, including Maloney's and Ryan’s, have been affected by redistricting.

Ryan in August won a close special election to serve out the term of Democrat Antonio Delgado, who vacated his 19th District seat after he was appointed lieutenant governor by Hochul. Ryan is running for a full term in the 18th District, where he lives.

Maloney, who had represented that district since 2013, decided to run in the 17th District. His Hudson Valley home fell inside the new boundaries after redistricting.

Hochul, who took office last year after Democrat Andrew Cuomo resigned amid sexual harassment allegations, is looking to win a full term as governor. Her opponent is Republican Rep. Lee Zeldin.

Later Thursday, Biden spoke out against Republicans at a fundraiser at the home of New Jersey Gov. Phil Murphy in support of the Democratic National Committee. The president has warned that followers of former President Donald Trump who deny the results of the 2020 presidential election are a threat to U.S. democracy, labeling them through Trump's slogan of “Make America Great Again.”

“Not all Republicans are MAGA Republicans," he said, but a “good 35% are Trumpites."

In the evening, Biden attended a Democratic Senatorial Campaign Committee fundraiser in Manhattan hosted by James Murdoch, the son of News Corp. publisher Rupert Murdoch. He warned about Putin hinting in a speech last month about deploying Russia's nuclear arsenal, a possible response to the exact loss of territory to Ukrainian forces.

“We have not faced the prospect of Armageddon since Kennedy and the Cuban Missile Crisis,” Biden said.

James Murdoch and his wife, Kathryn, a climate change activist, were major donors to Biden’s 2020 presidential campaign. In 2020, Murdoch resigned from the board of News Corp. amid differences over editorial content at his father's company, which operates The Wall Street Journal and the New York Post. The elder Murdoch is also chairman of Fox Corp., which includes Fox News Channel.

While Biden has been kept at arms length by many Democratic candidates, he's been a prodigious fundraiser for his party this election cycle, raising more than $19.6 million for the Democratic National Committee.

Associated Press writers Michelle L. Price in New York City and Michael Catalini in Trenton, New Jersey, contributed to this report.

Copyright 2022 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed without permission.

Thu, 06 Oct 2022 12:43:00 -0500 en text/html https://buffalonews.com/lifestyles/technology/biden-ibm-investment-to-help-in-tech-competition-with-china/article_8c84d18a-4904-53c4-88e3-edf89c6ccd6c.html
Killexams : Artificial Intelligence In Manufacturing Market Astonishing Growth with Top Influencing Key Players like IBM, SAS, SAP SE, Siemens, Oracle, Microsoft

Artificial intelligence in manufacturing - Business Going Digital

 Latest research on Artificial Intelligence In Manufacturing Market report covers forecast and analysis on a worldwide, regional and country level. The study provides historical information of 2016-2020 together with a forecast from 2022 to 2027 supported by both volume and revenue (USD million). The entire study covers the key drivers and restraints for the Artificial Intelligence In Manufacturing market. This report included a special section on the Impact of COVID19. Also, Artificial Intelligence In Manufacturing Market (By major Key Players, By Types, By Applications, and Leading Regions) Segment’s outlook, Business assessment, Competition scenario and Trends.

The Artificial Intelligence In Manufacturing Market is expected to register a CAGR of around 22.5%, during the forecast period 2022 to 2027

Get trial Copy Of This Report + All Related Graphs (Covid-19 Update):

https://www.marketinsightsreports.com/reports/09199633713/global-artificial-intelligence-in-manufacturing-market-research-report-2022-impact-of-covid-19-on-the-market/inquiry?Mode=130

The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market. Top Companies in the Global Artificial Intelligence In Manufacturings Market: – IBM, SAS, SAP SE, Siemens, Oracle, Microsoft, Mitsubishi Electric Corporation, Huawei, General Electric Company, Intel, Amazon Web Services, Google, Cisco Systems, PROGRESS DataRPM, Salesforce, NVIDIA, Autodesk

Market Overview:

The exact advancements in AI have enhanced the Cobots to run operations more smoothly in dynamically changing workplaces such as manufacturing. Innovations in robotics have made Cobots more compatible, safer, and cost-effective. Cobots use computer vision technology to quickly examine huge quantities of the flaws and avoid hazards using its predictive intelligence. Cobots integrated with AI are used in industries for repetitive and dangerous tasks, making it safer and efficient for human counterparts.

The manufacturing industry process involves continuous improvement, i.e. present work process can be upgraded by utilizing advanced technologies such as AI, IoT, and machine learning, among others. The Cobots can add a meaningful contribution to its implementation by detecting the changing condition on the floor and accordingly monitor and optimize its further operations. Additionally, Cobots can inspect the testing equipment, diagnose failure condition, read its result, and accordingly make changes in its decisions. This is likely to gain the attention of many manufacturers owing to the rising demand for customization.

Recent Development:

March 2020 – Siemens collaborated with NEC Corporation to provide manufacturing industries analysis solutions and AI monitoring to accelerate digitization. This will offer manufacturing industries an easy to visualize and analyze the huge generated data sets. AI will help to model large and complex process to increase the productivity.

This report segments the market on thse basis of Types are:

PLC
SCADA|HMI
MES
ERP

On the basis of Application, the market is segmented into:

Ferrous Metallurgy
Non-ferrous Metallurgy
Mining
Oil and Gas
Chemical
Others

For More Information On This Report, Please Visit: https://www.marketinsightsreports.com/reports/09199633713/global-artificial-intelligence-in-manufacturing-market-research-report-2022-impact-of-covid-19-on-the-market?Mode=130

Regional Analysis For Artificial Intelligence In Manufacturing Market:

For comprehensive understanding of market dynamics, the global Artificial Intelligence In Manufacturing market is analyzed across key geographies namely:

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

South America (Brazil, Argentina, Colombia)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Asia Pacific is expected to grow with the highest CAGR for the forecast period. The governments of China, Japan, Singapore and India are investing in artificial intelligence and also boosting the AI in manufacturing industry for smart factories and Industry 4.0. China has invested USD 150 billion on its Artificial Intelligence Development Plan for its national AI industries and with an aim to become AI super leader by 2030. AI in the China manufacturing industry is likely to have great opportunities owing to the rising adoption of smart factory technology.

Europe is growing next in line after Asia Pacific during the forecast period. UK is likely to grow significantly owing to its big investments of about USD 1.3 Billion in artificial intelligence technology. The country is also investing in sponsoring education programs for AI graduates, along with players such as Google’s Deepmind, BAE Systems and Cisco Systems.

Each of these regions is analyzed on basis of market findings across major countries in these regions for a macro-level understanding of the market.

Key Points of Artificial Intelligence In Manufacturing Market Table of Contents:

Market Overview: The report begins with this section where a product overview and key content on the product and application segments of the global Halal Foods market are provided. The highlights of the segmentation study include price, revenue, sales, sales growth rate, and market share by product.

Competition by company: Here we analyze the competition of the global Artificial Intelligence In Manufacturing market, by company price, revenue, sales and market share, market share, competitive landscape, and latest trends, mergers, expansions, acquisitions, and market share of top companies.

Company Profile and Sales Data: As the name suggests, this section provides sales data and useful information about the business of key players in the global Artificial Intelligence In Manufacturings market. It describes the key businesses of gross margin, price, revenue, products and specifications, types, applications, competitors, manufacturing base, and key players operating in the global Artificial Intelligence In Manufacturing market.

Market Forecast: Here the report provides a full forecast for the global Artificial Intelligence In Manufacturing market by product, application, and region. It also provides global sales and revenue forecasts for all years in the forecast period.

Research Results and Conclusion: One of the last sections of the report where analyst findings and findings are provided.

Customization Of The Report:

MarketInsightsReports provides customization of reports as per your need. This report can be personalized to meet your requirements. Get in touch with our sales team, who will ensure you to get a report that suits your necessities.

If you have any questions about any of our “Artificial Intelligence In Manufacturing market report” or would like to schedule a personalized free demo of Artificial Intelligence In Manufacturing market report, please do not hesitate to contact me at [email protected] .

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MarketInsightsReports provides syndicated market research on industry verticals including Healthcare, Information and Communication Technology (ICT), Technology and Media, Chemicals, Materials, Energy, Heavy Industry, etc. MarketInsightsReports provides global and regional market intelligence coverage, a 360-degree market view which includes statistical forecasts, competitive landscape, detailed segmentation, key trends, and strategic recommendations.

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Thu, 06 Oct 2022 12:00:00 -0500 Xherald en-US text/html https://www.digitaljournal.com/pr/artificial-intelligence-in-manufacturing-market-astonishing-growth-with-top-influencing-key-players-like-ibm-sas-sap-se-siemens-oracle-microsoft
Killexams : IBM Watson Services Market Projections and Regional Outlook, Sales Revenue Focus on Specific Product and Dynamics by 2030

The MarketWatch News Department was not involved in the creation of this content.

Oct 10, 2022 (Alliance News via COMTEX) -- Quadintel's exact global IBM Watson Services market research report gives detailed facts with consideration to market size, cost revenue, trends, growth, capacity, and forecast till 2030. In addition, it includes an in-depth analysis of This market, including key factors impacting the market growth.

The global IBM Watson Services market is anticipated to grow at a CAGR of around 32.5% over the period of next 5 years.

This study offers information for creating plans to increase the market’s growth and effectiveness and is a comprehensive quantitative survey of the market.

Download Free trial of This Strategic Report :-https://www.quadintel.com/request-sample/ibm-watson-services-market/QI046

For industry executives, marketing, sales, and product managers, consultants, analysts, and stakeholders searching for vital industry data in easily accessible documents with clearly presented tables and graphs, the research contains historical data from 2017 to 2020 and predictions through 2030.

A component of IBM Corporation, The IBM Watson is a cognitive computing platform which aids in efficiency and agility of businesses by incorporating AI and other related technologies with advanced hypothesis generation and analytical algorithms.

It integrates various cognitive techniques for facilitating construction of software by crafting dialogues and defining intents for simulating conversion. These services are employed for processing insights, relationships and patterns across un-structured images, social media, emails and others.

The Watson introduced to shape businesses more intelligent; is delivered as a Software-as-a-Service on cloud and can be called by its clients using a small code snippet embedded in their system.

MARKET DRIVERS:

The growth of this market is attributed towards major relying factors including the proliferating usage ofIBM Watson servicesin healthcare & analytics across various regions, the growing demand for cognitive insight & digital technology globally and the rising number of technological advancements in healthcare as well as medical devices substantially etc.

Additionally, the advent of technologies such as machine learning, artificial intelligence, cognitive computing, natural language processing (NLP), data mining, and advanced text analytics have changed the whole working scenario of the healthcare industry. From quicker decision making, assisting in disease diagnosis, optimizing patient selection for clinical trials with intelligence matching, screening of patients? structured & unstructured data, fast marketing of new drug, the technological platforms of IBM Watson have been effectively aiding in the operations of healthcare sector over the past few years, which is thereby opening enormous growth opportunities for the market players existing in the market and eventually assisting in the growth of the overall market considerably.

Moreover, IBM Watson Services are also in extensive use in the media and entertainment industry since the last years and is contributing in the fueling of the market growth comprehensively.

Furthermore, other factors such as the effective and process downtime features of IBM Watson, the proliferating demand for collection of patient data in healthcare facilities, the rapid emergence of innovative drugs, the growing revolution in the field of medical devices & healthcare facilities and the increasing importance of data generated from the patients further augment the growth of the market.

However, few factors pertaining to IBM Watson Services such as the lack of trained professionals, the unstructured and fragmented data structuring technology, the imperfections in AI methodologies, their inability of making connections with different corpora, language issues, concerns relating to maintenance, the high switching cost and time-intensiveness involved in installation and training of the process are major barriers which hamper the growth of this market.

Access full Report Description, TOC, Table of Figure, Chart, etc. @https://www.quadintel.com/request-sample/ibm-watson-services-market/QI046

IBM WATSON SERVICES MARKET SEGMENTATION:

By Services:

Watson Studio
Watson Knowledge Catalog
Watson AI Assistant
Watson Discovery
Watson IoT Platform
Watson Speech to Text (STT)
Watson Text to Speech (TTS)
Watson Language Services
Watson Visual Recognition
Watson Tone Analyzer
Watson Personality Insights
Watson Data Refinery
Watson Machine Learning
Watson Deep Learning
Watson Compare and Comply
Other Services
By End User Industry:

Healthcare
BFSI
Retail
Discrete & Process Manufacturing
Telecom
Media & Entertainment
Transportation & Logistics
Government
Travel & Tourism
Education
Others
By Region:

North America
Europe
Asia Pacific
Latin America
Middle East & Africa
REGIONAL INSIGHT:

The North America region followed by the European region holds the largest share in the IBM Watson Services market. The region is also expected to bolster tremendous growth in the upcoming years owing to factors such as the introduction of the Watson development platform in region by IBM for various purposes, the acquisition of a leading digital marketing & creative agency based in the U.S., Resource/Ammirati by IBM with a goal to create transformative brand experiences, the surging application of IBM Watson APIs for providing interactive mobile experiences to consumers in the region and the successful development of the production capacities of industries by these services in the region etc. The major contributors to the region include U.S and Canada.

The Asia Pacific region is the fastest growing regional market for IBM Watson Services in the world and is projected to also grow robustly in the upcoming years as well. The growth in the region can be attributed to factors such as the growing adoption of technologies such as blockchain, cognitive computing and others in various industries for assisting in commercialization and rapid prototyping of the client?s solutions in the region and the expansion of IBM?s headquarters in the major economies of this region etc. Japan, South Korea, India and China are the major contributors to this region?s growth.

Download trial Report, SPECIAL OFFER (Avail an Up-to 30% discount on this report ): -https://www.quadintel.com/request-sample/ibm-watson-services-market/QI046

FEW KEY PLAYERS IN IBM WATSON SERVICES MARKET:

KPMG International Limited
Capgemini SE
Tata Consultancy Services Limited
Wipro Limited
IBM Corporation
Datamato Technologies Private Ltd.
Mainline Information Systems Inc.
DXC Technology Limited Accenture Plc
Deloitte Touche Tohmatsu Ltd.
Tech Mahindra limited
Infosys Limited
HCL Limited
Other Players
RECENT DEVELOPMENTS:

In February 2021, Humana Inc. and IBM Watson Health announced a collaboration leveraging IBM?s conversational artificial intelligence (AI) solution to help provide a better member experience while providing greater clarity and transparency on benefits and other related matters for Humana Employer Group members. As part of the agreement, Humana will deploy IBM Watson Assistant for Health Benefits, an AI-enabled virtual assistant built in the IBM Watson Health cloud.

In February 2021, IBM and Palantir Technologies announced a new partnership consisting of IBM?s hybrid cloud data platform designed to deliver AI for business, with Palantir?s next generation operations platform for building applications. The product is expected to simplify how businesses build and deploy AI-infused applications with IBM Watson and help users access, analyze, and take action on the vast amounts of data that is scattered across hybrid cloud environments without the need for deep technical skills. The new product, Palantir for IBM Cloud Pak for Data, is planned to be mace available in March of 2021.

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COMTEX_416302742/2796/2022-10-10T05:43:26

The MarketWatch News Department was not involved in the creation of this content.

Sun, 09 Oct 2022 21:43:00 -0500 en-US text/html https://www.marketwatch.com/press-release/ibm-watson-services-market-projections-and-regional-outlook-sales-revenue-focus-on-specific-product-and-dynamics-by-2030-2022-10-10
Killexams : New IBM Study Finds Cybersecurity Incident Responders Have Strong Sense of Service as Threats Cross Over to Physical World

-      Sense of duty to protect others cited amongst the top reasons 77% of respondents entered Incident Response (IR)

-      Ransomware has exacerbated the psychological demands of IR for 81% of respondents

-      Majority of respondents have sought out mental health assistance due to their experiences responding to cyberattacks

CAMBRIDGE, Mass., Oct 3, 2022 /PRNewswire/ -- IBM Security (NYSE: IBM) today announced the results of a global survey that examines the critical role of cybersecurity incident responders at a time when the physical and digital worlds are increasingly converging. The study, released during National Cybersecurity Awareness Month, found that incident responders surveyed – the frontline responders to cyberattacks – are primarily driven by a strong sense of duty to protect others; a responsibility that's increasingly challenged by the surge of disruptive attacks, from the proliferation of ransomware attacks to the exact rise of wiper malware.

Cybersecurity Awareness Month - IBM Security Sense of Duty

Organizations that are essential to the global economy, supply chains and the movement of goods have become prime targets for disruptive attacks. In 2021 IBM Security X-Force observed cyberattacks against energy companies quadrupling from the year prior, while manufacturers saw more ransomware attacks than any other industry – from food manufacturers to medical devices, cars and steel manufacturers. As cyberattacks threaten essential services to our daily needs, incident responders in these industries are faced with more pressure to defend the digital front line. In fact, 81% of respondents stated that the rise of ransomware has exacerbated the psychological demands associated to cybersecurity incidents.

The global survey of over 1,100 cybersecurity incident responders in 10 markets, conducted by Morning Consult and sponsored by IBM Security, revealed trends, and challenges that incident responders experience due to the nature of their profession. Some key highlights include:

  • A Sense of Service – Over a third of incident responders were attracted to the field by a sense of duty to protect and opportunity to help others and businesses. For nearly 80% of respondents, this was one of the top reasons attracting them to IR.
  • Fighting Multiple Battlefronts – Amid a growing number of cyberattacks in exact years, 68% of incident responders surveyed stated it's common to be assigned to respond to two or more overlapping incidents simultaneously.
  • Impact on Daily Life – The high demands of cybersecurity engagements also affect incident responders' personal lives, with 67% experiencing stress or anxiety in their daily lives. Insomnia, burnout and impact on social life or relationships followed as effects respondents cited. Despite these challenges, the vast majority acknowledged they have a strong support system in place.

"The real-world repercussions that cyberattacks now have are causing public safety concerns and market-stressing risks to grow," said Laurance Dine, Global Lead, IBM Security X-Force Incident Response. "Incident responders are the frontline defenders standing between cyber adversaries causing disruption and the integrity and continuity of critical services. IBM salutes all IR teams  across the cybersecurity community, and the essential role they play in defending the digital front line."

An Uneven Battlefield

In exact years, not only have cyberattacks become more disruptive, but their sheer volume has increased. X-Force saw a nearly 25% rise in cybersecurity incidents its IR team engaged in from 2020 to 2021. Add to that, Check Point Software Technologies research indicates  a 50% increase in overall network attacks per week in 2021 compared to 2020. But as the industry is called to respond to a growing number of cyberattacks, there's only a finite number of security professionals specifically trained and skilled to respond to cybersecurity incidents.

As a result, while many IR teams are forced to take on multiple battlefronts, businesses could be left without the necessary resources to mitigate and recover from cyberattacks. The IBM study found that 68% of incident responders surveyed find it common to simultaneously need to respond to two or more cybersecurity incidents, highlighting a field that is constantly engaged. Amongst U.S. respondents 34% said the average length of an IR engagement was 4-6 weeks, while a quarter cited the first week as often the most stressful or demanding period of the engagement. During this period about a third of respondents work more than 12 hours per day on average.

A Strong Support System in Place

As incident responders take on the pressure and high demands associated with cyber response, the overwhelming majority of respondents acknowledged they have a strong support system in place. Specifically, most respondents feel their leadership has a strong understanding of the activities IR involves, while 95% say it provides the necessary support structure for them to be successful. As well, 84% state they have adequate access to mental health support resources, with many respondents (64%) seeking out mental health assistance due to the demanding nature of responding to cyberattacks.

But businesses can further support incident responders, whether in-house Blue Teams or the external IR teams they engage in the event of a cyber crisis, by prioritizing cyber preparedness and creating plans and playbooks that are customized to their environment and resources. This can help enable a more agile and quick response at the onset of an incident and alleviate an unnecessary layer of pressure across the business.

To that end, situational awareness of their infrastructure is important. Businesses can focus on testing their state of readiness through simulation exercises, not only to get a feel of how their teams will react under attack, but to provide opportunities to correctly integrate multiple teams that are engaged during a cyber incident.

Additional Resources

  • Read the complete findings from IBM Security's Incident Responder study
  • Celebrate and recognize incident responders this Cybersecurity Awareness Month here
  • Read a Security Intelligence blog on incident responders holding the digital frontline
  • To register for IBM Security X-Force's incident response webinar, "Tales from the Digital Frontlines," on Wednesday, October 12 at 1:00 pm ET, sign up here
  • Schedule a consult with IBM Security X-Force

About IBM Security
IBM Security offers one of the most advanced and integrated portfolios of enterprise security products and services. The portfolio, supported by world-renowned IBM Security X-Force® research, enables organizations to effectively manage risk and defend against emerging threats. IBM operates one of the world's broadest security research, development, and delivery organizations, monitors 150 billion+ security events per day in more than 130 countries, and has been granted more than 10,000 security patents worldwide. For more information, please check www.ibm.com/security, follow @IBMSecurity on Twitter or visit the IBM Security Intelligence blog.

Contact:
Georgia Prassinos
IBM Security Communications 
gprassinos@ibm.com

IBM Corporation logo. (PRNewsfoto/IBM)

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SOURCE IBM

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Killexams : Artificial Intelligence in Energy Market Market Still Has Room to Grow | Siemens, Schneider Electric, IBM, General Electric

The latest study released on the Global Artificial Intelligence in Energy Market by AMA Research evaluates market size, trend, and forecast to 2027. The Artificial Intelligence in Energy market study covers significant research data and proofs to be a handy resource document for managers, analysts, industry experts and other key people to have ready-to-access and self-analyzed study to help understand market trends, growth drivers, opportunities and upcoming challenges and about the competitors.

Download trial Report PDF (Including Full TOC, Table & Figures) @ https://www.advancemarketanalytics.com/sample-report/115268-global-artificial-intelligence-in-energy-market#utm_source=DigitalJournalShraddha

Key Players in This Report Include:

Alphabet (United States), General Electric (United States), Siemens (Germany), Watty (Sweden), IBM (United States), Schneider Electric (France), BuildingIQ (United States), ABB (Switzerland), Grid4C (United States)

Definition:

Artificial intelligence in the energy sector is now reaching emerging markets, where it may have a critical impact, as clean, cheap, and reliable energy is essential to development. Artificial intelligence technologies are closely tied to the ability to provide clean and cheap energy that is essential to development. Increasing demand for artificial intelligence in the energy sector from developed nations that allow for communication between smart grids, smart meters, and Internet of Things devices is propelling the growth of the global artificial intelligence in the energy market.

Market Trends:
Increasing Use of Machine Learning

Market Drivers:
Lack of Analytics Needed for Optimal Management
Rising Demand for Energy across the Globe

Market Opportunities:
Technological Advancement and Development in Artificial Intelligence in Energy

The Global Artificial Intelligence in Energy Market segments and Market Data Break Down are illuminated below:

by Type (Software, Hardware, Services), Application (Fault Prediction, Maintenance Facilitated by Image Processing, Energy Efficiency Decision Making, Disaster Recovery, Prevention of Losses Due to Informal Connections), Organization Size (Small and Medium Size Organization, Large Size Organization), Deployment (Cloud-based, On-premise)

Global Artificial Intelligence in Energy market report highlights information regarding the current and future industry trends, growth patterns, as well as it offers business strategies to helps the stakeholders in making sound decisions that may help to ensure the profit trajectory over the forecast years.

Have a query? Market an enquiry before purchase @ https://www.advancemarketanalytics.com/enquiry-before-buy/115268-global-artificial-intelligence-in-energy-market#utm_source=DigitalJournalShraddha

Geographically, the detailed analysis of consumption, revenue, market share, and growth rate of the following regions:

The Middle East and Africa (South Africa, Saudi Arabia, UAE, Israel, Egypt, etc.)

North America (United States, Mexico & Canada)

South America (Brazil, Venezuela, Argentina, Ecuador, Peru, Colombia, etc.)

Europe (Turkey, Spain, Turkey, Netherlands Denmark, Belgium, Switzerland, Germany, Russia UK, Italy, France, etc.)

Asia-Pacific (Taiwan, Hong Kong, Singapore, Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia).

Objectives of the Report:

-To carefully analyze and forecast the size of the Artificial Intelligence in Energy market by value and volume.

-To estimate the market shares of major segments of the Artificial Intelligence in Energy

-To showcase the development of the Artificial Intelligence in Energy market in different parts of the world.

-To analyze and study micro-markets in terms of their contributions to the Artificial Intelligence in Energy market, their prospects, and individual growth trends.

-To offer precise and useful details about factors affecting the growth of the Artificial Intelligence in Energy

-To provide a meticulous assessment of crucial business strategies used by leading companies operating in the Artificial Intelligence in Energy market, which include research and development, collaborations, agreements, partnerships, acquisitions, mergers, new developments, and product launches.

Buy Complete Assessment of Artificial Intelligence in Energy market Now @ https://www.advancemarketanalytics.com/buy-now?format=1&report=115268#utm_source=DigitalJournalShraddha

Major highlights from Table of Contents:

Artificial Intelligence in Energy Market Study Coverage:

It includes major manufacturers, emerging player’s growth story, and major business segments of Artificial Intelligence in Energy market, years considered, and research objectives. Additionally, segmentation on the basis of the type of product, application, and technology.

Artificial Intelligence in Energy Market Executive Summary: It gives a summary of overall studies, growth rate, available market, competitive landscape, market drivers, trends, and issues, and macroscopic indicators.

Artificial Intelligence in Energy Market Production by Region Artificial Intelligence in Energy Market Profile of Manufacturers-players are studied on the basis of SWOT, their products, production, value, financials, and other vital factors.

Key Points Covered in Artificial Intelligence in Energy Market Report:

Artificial Intelligence in Energy Overview, Definition and Classification Market drivers and barriers

Artificial Intelligence in Energy Market Competition by Manufacturers

Impact Analysis of COVID-19 on Artificial Intelligence in Energy Market

Artificial Intelligence in Energy Capacity, Production, Revenue (Value) by Region (2022-2027)

Artificial Intelligence in Energy Supply (Production), Consumption, Export, Import by Region (2022-2027)

Artificial Intelligence in Energy Manufacturers Profiles/Analysis Artificial Intelligence in Energy  Manufacturing Cost Analysis, Industrial/Supply Chain Analysis, Sourcing Strategy and Downstream Buyers, Marketing

Strategy by Key Manufacturers/Players, Connected Distributors/Traders Standardization, Regulatory and collaborative initiatives, Industry road map and value chain Market Effect Factors Analysis.

Browse Complete Summary and Table of Content @ https://www.advancemarketanalytics.com/reports/115268-global-artificial-intelligence-in-energy-market#utm_source=DigitalJournalShraddha

Key questions answered:

How feasible is Artificial Intelligence in Energy market for long-term investment?

What are influencing factors driving the demand for Artificial Intelligence in Energy near future?

What is the impact analysis of various factors in the Global Artificial Intelligence in Energy market growth?

What are the exact trends in the regional market and how successful they are?

Thanks for studying this article; you can also get individual chapter wise section or region wise report version like North America, Middle East, Africa, Europe or LATAM, Southeast Asia.

Contact US :

Craig Francis (PR & Marketing Manager)

AMA Research & Media LLP

Unit No. 429, Parsonage Road Edison, NJ

New Jersey USA – 08837

Phone: +1 (551) 333 1547

[email protected]

Tue, 04 Oct 2022 02:00:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/artificial-intelligence-in-energy-market-market-still-has-room-to-grow-siemens-schneider-electric-ibm-general-electric
Killexams : Artificial Intelligence (AI) in Insurance Market May See a Big Move : Google, Microsoft , IBM: Long Term Growth Story

New Jersey, NJ -- (SBWIRE) -- 10/10/2022 -- The Global Artificial Intelligence (AI) in Insurance Market Report assesses developments relevant to the insurance industry and identifies key risks and vulnerabilities for the Artificial Intelligence (AI) in Insurance Industry to make stakeholders aware with current and future scenarios. To derive complete assessment and market estimates a wide list of Insurers, aggregators, agency were considered in the coverage; Some of the top players profiled are Google, Microsoft Corporation, Amazon Web Services Inc, IBM Corporation, Avaamo Inc, Baidu Inc, Cape Analytics LLC, Oracle Corporation & ?Artificial Intelligence (AI) in InsuranceMarket Scope and Market Breakdown.

Next step one should take to boost topline? Track exact strategic moves and product landscape of Artificial Intelligence (AI) in Insurance market.

Get Free Access of Global Artificial Intelligence (AI) in Insurance Market Research trial PDF https://www.htfmarketreport.com/sample-report/3570714-global-artificial-intelligence-205

Globally, the insurance industry experienced strong premium growth in 2022, at percent, whereas growth in 2022 is noticeably slower, at percent. Total premiums (GWP) are expected to reach ... by 2028. Artificial Intelligence (AI) in Insurance Companies seeking top growth opportunities in the global insurance markets can explore both the fastest-growing markets and the largest developed markets; the slowing growth rates suggest; however, most carriers would also need to search farther afield. "The growth during this period will be fuelled by the emerging markets in the APAC and Latin American regions"

The report depicts the total market of Artificial Intelligence (AI) in Insurance industry; further market is broken down by application [on, Life Insurance, Car Insurance, Property Insurance, Channel, By Channels, Market has been segmented into, Direct Sales, Distribution Channel, Regional & Country Analysis, North America Country (United States, Canada), South America (Brazil, Argentina, Peru, Chile, Rest of South America), Asia-Pacific (China, Japan, India, South Korea, Australia, Singapore, Malaysia, Indonesia, Philippines, Thailand, Vietnam, Others), Europe (Germany, United Kingdom, France, Italy, Spain, Switzerland, Netherlands, Austria, Sweden, Norway, Belgium, Rest of Europe) & Rest of World [GCC, South Africa, Egypt, Turkey, Israel, Others]], type [, Software & Platform] and country.

Geographically, the global version of report covers following regions and country:
- North America [United States, Canada and Mexico]
- Europe [Germany, the UK, France, Italy, Netherlands, Belgium, Russia, Spain, Sweden, and Rest of Europe]
- Asia-Pacific [China, Japan, South Korea, India, Australia, Southeast Asia and Others]
- South America [Brazil, Argentina, Chile and Rest of South America]
- Middle East and Africa (South Africa, Turkey, Israel, GCC Countries and Rest of Africa)

Browse Executive Summary and Complete Table of Content @ https://www.htfmarketreport.com/reports/3570714-global-artificial-intelligence-205

Research Approach & Assumptions:

- HTF MI describe major trends of Global Artificial Intelligence (AI) in Insurance Market using final data for 2022 and previous years, as well as quarterly or annual reports for 2022. In general, Years considered in the study i.e. base year as 2022, Historical data considered as 2022-2028and Forecast time frame is 2022-2028.

- Various analytical tools were used to assess how the insurance Sector and particularly Artificial Intelligence (AI) in Insurance Industry might respond over the next decade to global macroeconomic shifts. Our "consensus scenario" assumes a recovery of Global GDP growth in the coming years in addition to fluctuating interest rates; the results presented in Artificial Intelligence (AI) in Insurance Market report reflect the output of this model.

- While calculating growth of Artificial Intelligence (AI) in Insurance Market, we generally used nominal gross premium figures based on 2022 fixed exchange rates, since this data allowed us to compare local growth rates without the interference of currency fluctuations. The exceptions, which use floating exchange rates, are Argentina, Ukraine, and Venezuela, many African Countries etc due to high inflation rates.

Get full access to Global Artificial Intelligence (AI) in Insurance Market Report; Buy Latest Edition Now @: https://www.htfmarketreport.com/buy-now?format=1&report=3570714

Thanks for studying Artificial Intelligence (AI) in Insurance Industry research publication; you can also get individual chapter wise section or region wise report version like USA, China, Southeast Asia, LATAM, APAC etc.

About Author:
HTF Market Intelligence consulting is uniquely positioned empower and inspire with research and consulting services to empower businesses with growth strategies, by offering services with extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist in decision making.

For more information on this press release visit: http://www.sbwire.com/press-releases/artificial-intelligence-ai-in-insurance-market-may-see-a-big-move-google-microsoft-ibm-1358920.htm

Nidhi bhawsar
PR & Marketing Manager
HTF Market Intelligence Consulting Pvt. Ltd.
Telephone: 2063171218
Email: Click to Email Nidhi bhawsar
Web: https://www.htfmarketreport.com/

Mon, 10 Oct 2022 09:21:00 -0500 en-US text/html https://insurancenewsnet.com/oarticle/artificial-intelligence-ai-in-insurance-market-may-see-a-big-move-google-microsoft-ibm-long-term-growth-story-66
Killexams : IBM CEO Arvind Krishna To Partners: To Win New Clients, ‘We Need Your Help’

Cloud News

Wade Tyler Millward

‘I want to increase the number of clients, also, not just wallet share,’ IBM CEO Arvind Krishna says at The Channel Company’s Best of Breed conference in Atlanta. ‘That means that we need your help. We are not going to go there directly at all.’

Under Arvind Krishna’s watch, IBM has decreased the number of direct customers from about 5,000 in 2020 to about 400, the CEO told a crowd Monday. And the tech giant plans to leave potential new clients to partners.

“I want to increase the number of clients, also, not just wallet share,” Krishna said. “That means that we need your help. We are not going to go there directly at all.”

The CEO of Armonk, N.Y.-based IBM discussed his company’s investment in partners, the integration of subsidiary Red Hat, encouraged partners to raise their prices given the inflationary economic environment and even weighed in on chipmaker Broadcom‘s pending acquisition of cloud vendor VMware at CRN parent The Channel Company’s 2022 XChange Best of Breed (BoB) conference in Atlanta.

Krishna was on stage responding to questions from The Channel Company Founding Partner Robert Faletra and CRN Executive Editor of News Steven Burke.

[RELATED: IBM Assimilates Red Hat Storage Technology Into Own Storage Business]

Mark Wyllie, CEO of Boca Raton, Fla.-based IBM partner Flagship Solutions Group, told CRN in an interview that he’s glad to hear IBM plans to continue integrating different parts of the Red Hat business.

Earlier this month, IBM announced that it had absorbed storage technology and teams from its Red Hat business to combine them with IBM’s own storage business unit as a way to help clients take advantage of the two without requiring extra integration or having to deal with multiple sales teams.

Wyllie wants to see IBM further integrate Red Hat services into its portfolio to help partners push the services out to existing IBM customers.

“I think that’d be a benefit to us and IBM,” Wyllie said.

Red Hat’s autonomy within IBM has been essential to its position as an open source software vendor. Krishna clarified Monday that the Red Hat brand will stay in areas where it has a stronger brand than IBM. For storage, “maybe we already have a storage channel, which Red Hat kind of didn’t,” Krishna said.

He said IBM gave Red Hat more security and management capabilities after its acquisition in 2019. Partners can expect more integration between Red Hat and IBM in areas involving Linux.

“So if you can take maybe 50,000 Linux servers and consolidate them using OpenShift on LinuxOne, maybe that‘s a play to be made,” Krishna said. “There’s a few clients who have woken up to that and are doing it right now. So I think that’s going to be a really big play you’re going to see.”

During his talk, Krishna encouraged partners to explore more opportunities in IBM’s artificial intelligence operations (AIOps) offerings, including Turbonomic, Watson AIOps and Instana.

Customers will continue to spend on automation tools, he said.

“The ability to go into an enterprise and tell them, ‘Look, we can do things a lot more automated. We can take some cost out. We can do monitoring, and eventually go closed loop on AI’ – which I don‘t think is happening yet,” Krishna said. “I think is a massive opportunity given the current labor market.”

IBM’s security offerings, as well as Red Hat and containerization offerings, are also areas for partners to invest in, Krishna said.

As for Broadcom and VMware, Krishna said that VMware remains an important partner for his company. And as long as VMware keeps investing in its products, it should remain “a strong franchise.”

“I think it’ll come down to what is going to happen in 2023 and 2024,” Krishna said. “As long as they keep innovating on the products, they keep giving more function back to their clients – it’s a strong franchise. That falls away, then that‘s a different question. But I think the virtualization world likes those products. Now it’s up to them to keep innovating.”

Krishna also told partners they should raise prices to cover the growing cost of labor with such high inflation in the U.S.

“From our conversations with clients, I would tell you that nobody loves it, but they all understand,” he said. “Because most of our clients are doing the same out to their clients. … Pricing power comes down to something simple. Is the product highly valuable and is it sticky? … In a world of fewer skills, if you have the skills, you can price those skills.”

Wade Tyler Millward

Wade Tyler Millward is an associate editor covering cloud computing and the channel partner programs of Microsoft, IBM, Red Hat, Oracle, Salesforce, Citrix and other cloud vendors. He can be reached at wmillward@thechannelcompany.com.

Mon, 10 Oct 2022 06:44:00 -0500 en text/html https://www.crn.com/news/cloud/ibm-ceo-arvind-krishna-to-partners-to-win-new-clients-we-need-your-help-
Killexams : Artificial Intelligence in Diabetes Management Market 2022 : Global Industry Overview, Sales Revenue, Demand and Forecast by 2029 | 109 Report Pages

The MarketWatch News Department was not involved in the creation of this content.

Oct 14, 2022 (The Expresswire) -- "Final Report will add the analysis of the impact of COVID-19 on this industry."

Global “Artificial Intelligence in Diabetes ManagementMarket2022 Research report is an in-depth study of the market Analysis. Industry growth drivers, supply and demand, risks, market attractiveness, annual growth comparison, BPS analysis, SWOT analysis, and Porter's Five Forces model. Artificial Intelligence in Diabetes Management Market report gives an inside and out audit of theExpansion Drivers, Potential Challenges, Distinctive Trends, and Opportunities for Market Players. Our Research experts have carried out detailed checks of the critical environment and have predicted the methodological structure used by market participants. The primary goal of the Artificial Intelligence in Diabetes Management business report is to supply key insights on competition positioning, current scope, market potential, growth rates, and alternative relevant statistics.

Get a trial PDF of the report at -https://www.researchreportsworld.com/enquiry/request-sample/21211351

Global Artificial Intelligence in Diabetes Management Market Analysis

The primary highlights of the report offer important details pertaining to profit estimations, statistics, and applications of this product. Our report covers regional analysis of the domestic markets, key company profiles, value chain analysis, consumption, demand, and growth areas. The report analyzes major market firms, focusing on their innovative developments, product launches, operations, and emerging market players to implement new business growth strategies. The report focuses on growth prospects, restraints, and trends of the global Artificial Intelligence in Diabetes Management market analysis. The study provides Porter’s five forces analysis to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on the global Artificial Intelligence in Diabetes Management market outlook.

Artificial Intelligence in Diabetes Management uses tracking and customer behavioral analysis to Strengthen corporate operations. Furthermore, when compared to on premise deployment, the deployment paradigm enables the implementation of analytics solutions at a low cost. Executives, data analysts, team leaders, managers, and professionals use business intelligence (BI) tools to collect, analyses, visualize, and report on numerous functions within a company and apply their results to their respective industries.

The report contains different market predictions related to revenue size, production, CAGR, Consumption, gross margin, price, and other substantial factors. While emphasizing the key driving and restraining forces for this market, the report also offers a complete study of the future trends and developments of the market. It also examines the role of the leading market players involved in the industry including their corporate overview, financial summary and SWOT analysis.

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List of Top Key Players in Artificial Intelligence in Diabetes Management Market Report:The survey describes the qualities of the entire company based on an industry-wide analysis: -

● DreaMed ● Google Inc. ● Medicsen ● XBIRD ● GlucoMe ● Medtronic ● Wellthy Therapeutics Pvt Ltd ● Sensyne Health plc ● IBM Corporation ● Diabnext ● Virta Health Corp ● Tidepool ● Hedia ● PredictBGL ● Sweetch ● Livongo Health ● Vodafone Group Plc ● TypeZero Technologies,Inc. ● Apple Inc. ● Glooko Inc.

Global Artificial Intelligence in Diabetes Management Market Growth report serves to be an ideal solution for better understanding of the Market. It is helpful in finding out the size of the Market for specific products. These major players operating in this Market are in strong competition in terms of technology, innovation, product development, and product pricing. The Market study aids in making sales forecasts for its products and thereby, establishing harmonious adjustment between demand and supply of its products.

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Global Artificial Intelligence in Diabetes Management Market Segmentation Analysis

Global Artificial Intelligence in Diabetes Management Market forecast report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

Based on Product Type, this report shows the creation, income, cost, piece of the pie, and development pace of each kind, principally split into:

● Glucose Monitoring Devices ● Diagnostic Devices ● Insulin Delivery Devices ● Others

Based on Component, Artificial Intelligence in Diabetes Management is a business solution that provides an in-depth analysis of crowd movement at large gathering locations such as airports and train stations, city malls, retail stores, convention centers, stadiums, and other venues. Data from a variety of sources, including closed-circuit television cameras (CCTV), commercial off-the-shelf cameras, and first- and third-party consumer data, is processed using powerful artificial intelligence approaches to present prediction crowd flow models and customer preference patterns.

On the Basis of the End-User/Applications, this report focuses on the status and outlook for major applications production, revenue, price, market share, and growth rate:

● Case-based Reasoning ● Intelligent Data Analysis

Based on the End Use, the Artificial Intelligence in Diabetes Management Market Trend is bifurcated into Aromatic Industries, Automotive, Building and Construction, Paints, Agrochemicals, and others. It is a low-cost solution that outperforms most composite applications in terms of price vs. performance. In the next five years, hydrocarbon resin is expected to remain the second-largest application in the worldwide Artificial Intelligence in Diabetes Management Market, owing to increased usage in adhesives, coatings, printing inks, and rubber goods. Also growing construction activities will help this market is growing.

COVID-19 impact on the market

COVID-19 is an infectious disease caused by the novel coronavirus. Largely unknown before this outbreak across the world, COVID-19 has moved from a regional crisis to a global pandemic in just a matter of a few weeks. The World Health Organization (WHO) declared COVID-19 as a pandemic on March 11, 2020.

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Geographic Segment Covered in the Report:

The Artificial Intelligence in Diabetes Management report provides information about the market area, which is further subdivided into sub-regions and countries/regions. In addition to the market share in each country and sub-region, this chapter of this report also contains information on profit opportunities. This chapter of the report mentions the market share and growth rate of each region, country and sub-region during the estimated period.

North America(USA and Canada) ● Europe(UK, Germany, France and the rest of Europe) ● Asia Pacific(China, Japan, India, and the rest of the Asia Pacific region) ● Latin America(Brazil, Mexico, and the rest of Latin America) ● Middle East and Africa(GCC and rest of the Middle East and Africa)

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Detailed TOC of Global Artificial Intelligence in Diabetes Management Market Research Report 2022 - Impact of COVID-19 on the Market

1 Artificial Intelligence in Diabetes Management Market Overview
1.1 Product Overview and Scope of Artificial Intelligence in Diabetes Management Market
1.2 Artificial Intelligence in Diabetes Management Market Segment by Type
1.2.1 Global Artificial Intelligence in Diabetes Management Market Sales and CAGR (%) Comparison by Type (2017-2029)
1.3 Global Artificial Intelligence in Diabetes Management Market Segment by Application
1.3.1 Artificial Intelligence in Diabetes Management Market Consumption (Sales) Comparison by Application (2017-2029)
1.4 Global Artificial Intelligence in Diabetes Management Market, Region Wise (2017-2029)
1.4.1 Global Artificial Intelligence in Diabetes Management Market Size (Revenue) and CAGR (%) Comparison by Region (2017-2029)
1.4.2 United States Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.3 Europe Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.4 China Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.5 Japan Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.6 India Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.7 Southeast Asia Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.8 Latin America Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.4.9 Middle East and Africa Artificial Intelligence in Diabetes Management Market Status and Prospect (2017-2029)
1.5 Global Market Size (Revenue) of Artificial Intelligence in Diabetes Management (2017-2029)
1.5.1 Global Artificial Intelligence in Diabetes Management Market Revenue Status and Outlook (2017-2029)
1.5.2 Global Artificial Intelligence in Diabetes Management Market Sales Status and Outlook (2017-2029)
1.6 Influence of Regional Conflicts on the Artificial Intelligence in Diabetes Management Industry
1.7 Impact of Carbon Neutrality on the Artificial Intelligence in Diabetes Management Industry2 Artificial Intelligence in Diabetes Management Market Upstream and Downstream Analysis
2.1 Artificial Intelligence in Diabetes Management Industrial Chain Analysis
2.2 Key Raw Materials Suppliers and Price Analysis
2.3 Key Raw Materials Supply and Demand Analysis
2.4 Market Concentration Rate of Raw Materials
2.5 Manufacturing Process Analysis
2.6 Manufacturing Cost Structure Analysis
2.6.1 Labor Cost Analysis
2.6.2 Energy Costs Analysis
2.6.3 RandD Costs Analysis
2.7 Major Downstream Buyers of Artificial Intelligence in Diabetes Management Analysis
2.8 Impact of COVID-19 on the Industry Upstream and Downstream3 Players Profiles
3.1 DreaMed
3.1.1 DreaMed Basic Information, Manufacturing Base, Sales Area and Competitors
3.1.2 Product Profiles, Application and Specification
3.1.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.1.4 Business Overview
3.2 Google Inc.
3.2.1 Google Inc. Basic Information, Manufacturing Base, Sales Area and Competitors
3.2.2 Product Profiles, Application and Specification
3.2.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.2.4 Business Overview
3.3 Medicsen
3.3.1 Medicsen Basic Information, Manufacturing Base, Sales Area and Competitors
3.3.2 Product Profiles, Application and Specification
3.3.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.3.4 Business Overview
3.4 XBIRD
3.4.1 XBIRD Basic Information, Manufacturing Base, Sales Area and Competitors
3.4.2 Product Profiles, Application and Specification
3.4.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.4.4 Business Overview
3.5 GlucoMe
3.5.1 GlucoMe Basic Information, Manufacturing Base, Sales Area and Competitors
3.5.2 Product Profiles, Application and Specification
3.5.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.5.4 Business Overview
3.6 Medtronic
3.6.1 Medtronic Basic Information, Manufacturing Base, Sales Area and Competitors
3.6.2 Product Profiles, Application and Specification
3.6.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.6.4 Business Overview
3.7 Wellthy Therapeutics Pvt Ltd
3.7.1 Wellthy Therapeutics Pvt Ltd Basic Information, Manufacturing Base, Sales Area and Competitors
3.7.2 Product Profiles, Application and Specification
3.7.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.7.4 Business Overview
3.8 Sensyne Health plc
3.8.1 Sensyne Health plc Basic Information, Manufacturing Base, Sales Area and Competitors
3.8.2 Product Profiles, Application and Specification
3.8.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.8.4 Business Overview
3.9 IBM Corporation
3.9.1 IBM Corporation Basic Information, Manufacturing Base, Sales Area and Competitors
3.9.2 Product Profiles, Application and Specification
3.9.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.9.4 Business Overview
3.10 Diabnext
3.10.1 Diabnext Basic Information, Manufacturing Base, Sales Area and Competitors
3.10.2 Product Profiles, Application and Specification
3.10.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.10.4 Business Overview
3.11 Virta Health Corp
3.11.1 Virta Health Corp Basic Information, Manufacturing Base, Sales Area and Competitors
3.11.2 Product Profiles, Application and Specification
3.11.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.11.4 Business Overview
3.12 Tidepool
3.12.1 Tidepool Basic Information, Manufacturing Base, Sales Area and Competitors
3.12.2 Product Profiles, Application and Specification
3.12.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.12.4 Business Overview
3.13 Hedia
3.13.1 Hedia Basic Information, Manufacturing Base, Sales Area and Competitors
3.13.2 Product Profiles, Application and Specification
3.13.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.13.4 Business Overview
3.14 PredictBGL
3.14.1 PredictBGL Basic Information, Manufacturing Base, Sales Area and Competitors
3.14.2 Product Profiles, Application and Specification
3.14.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.14.4 Business Overview
3.15 Sweetch
3.15.1 Sweetch Basic Information, Manufacturing Base, Sales Area and Competitors
3.15.2 Product Profiles, Application and Specification
3.15.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.15.4 Business Overview
3.16 Livongo Health
3.16.1 Livongo Health Basic Information, Manufacturing Base, Sales Area and Competitors
3.16.2 Product Profiles, Application and Specification
3.16.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.16.4 Business Overview
3.17 Vodafone Group Plc
3.17.1 Vodafone Group Plc Basic Information, Manufacturing Base, Sales Area and Competitors
3.17.2 Product Profiles, Application and Specification
3.17.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.17.4 Business Overview
3.18 TypeZero Technologies,Inc.
3.18.1 TypeZero Technologies,Inc. Basic Information, Manufacturing Base, Sales Area and Competitors
3.18.2 Product Profiles, Application and Specification
3.18.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.18.4 Business Overview
3.19 Apple Inc.
3.19.1 Apple Inc. Basic Information, Manufacturing Base, Sales Area and Competitors
3.19.2 Product Profiles, Application and Specification
3.19.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.19.4 Business Overview
3.20 Glooko Inc.
3.20.1 Glooko Inc. Basic Information, Manufacturing Base, Sales Area and Competitors
3.20.2 Product Profiles, Application and Specification
3.20.3 Artificial Intelligence in Diabetes Management Market Performance (2017-2022)
3.20.4 Business Overview4 Global Artificial Intelligence in Diabetes Management Market Landscape by Player
4.1 Global Artificial Intelligence in Diabetes Management Sales and Share by Player (2017-2022)
4.2 Global Artificial Intelligence in Diabetes Management Revenue and Market Share by Player (2017-2022)
4.3 Global Artificial Intelligence in Diabetes Management Average Price by Player (2017-2022)
4.4 Global Artificial Intelligence in Diabetes Management Gross Margin by Player (2017-2022)
4.5 Artificial Intelligence in Diabetes Management Market Competitive Situation and Trends
4.5.1 Artificial Intelligence in Diabetes Management Market Concentration Rate
4.5.2 Artificial Intelligence in Diabetes Management Market Share of Top 3 and Top 6 Players
4.5.3 Mergers and Acquisitions, Expansion5 Global Artificial Intelligence in Diabetes Management Sales, Revenue, Price Trend by Type
5.1 Global Artificial Intelligence in Diabetes Management Sales and Market Share by Type (2017-2022)
5.2 Global Artificial Intelligence in Diabetes Management Revenue and Market Share by Type (2017-2022)
5.3 Global Artificial Intelligence in Diabetes Management Price by Type (2017-2022)
5.4 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Growth Rate by Type (2017-2022)
5.4.1 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Growth Rate of Glucose Monitoring Devices (2017-2022)
5.4.2 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Growth Rate of Diagnostic Devices (2017-2022)
5.4.3 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Growth Rate of Insulin Delivery Devices (2017-2022)
5.4.4 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Growth Rate of Others (2017-2022)6 Global Artificial Intelligence in Diabetes Management Market Analysis by Application
6.1 Global Artificial Intelligence in Diabetes Management Consumption and Market Share by Application (2017-2022)
6.2 Global Artificial Intelligence in Diabetes Management Consumption Revenue and Market Share by Application (2017-2022)
6.3 Global Artificial Intelligence in Diabetes Management Consumption and Growth Rate by Application (2017-2022)
6.3.1 Global Artificial Intelligence in Diabetes Management Consumption and Growth Rate of Case-based Reasoning (2017-2022)
6.3.2 Global Artificial Intelligence in Diabetes Management Consumption and Growth Rate of Intelligent Data Analysis (2017-2022)7 Global Artificial Intelligence in Diabetes Management Sales and Revenue Region Wise (2017-2022)
7.1 Global Artificial Intelligence in Diabetes Management Sales and Market Share, Region Wise (2017-2022)
7.2 Global Artificial Intelligence in Diabetes Management Revenue and Market Share, Region Wise (2017-2022)
7.3 Global Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.4 United States Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.4.1 United States Artificial Intelligence in Diabetes Management Market Under COVID-19
7.5 Europe Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.5.1 Europe Artificial Intelligence in Diabetes Management Market Under COVID-19
7.6 China Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.6.1 China Artificial Intelligence in Diabetes Management Market Under COVID-19
7.7 Japan Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.7.1 Japan Artificial Intelligence in Diabetes Management Market Under COVID-19
7.8 India Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.8.1 India Artificial Intelligence in Diabetes Management Market Under COVID-19
7.9 Southeast Asia Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.9.1 Southeast Asia Artificial Intelligence in Diabetes Management Market Under COVID-19
7.10 Latin America Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.10.1 Latin America Artificial Intelligence in Diabetes Management Market Under COVID-19
7.11 Middle East and Africa Artificial Intelligence in Diabetes Management Sales, Revenue, Price and Gross Margin (2017-2022)
7.11.1 Middle East and Africa Artificial Intelligence in Diabetes Management Market Under COVID-198 Global Artificial Intelligence in Diabetes Management Market Forecast (2022-2029)
8.1 Global Artificial Intelligence in Diabetes Management Sales, Revenue Forecast (2022-2029)
8.1.1 Global Artificial Intelligence in Diabetes Management Sales and Growth Rate Forecast (2022-2029)
8.1.2 Global Artificial Intelligence in Diabetes Management Revenue and Growth Rate Forecast (2022-2029)
8.1.3 Global Artificial Intelligence in Diabetes Management Price and Trend Forecast (2022-2029)
8.2 Global Artificial Intelligence in Diabetes Management Sales and Revenue Forecast, Region Wise (2022-2029)
8.2.1 United States Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.2 Europe Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.3 China Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.4 Japan Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.5 India Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.6 Southeast Asia Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.7 Latin America Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.2.8 Middle East and Africa Artificial Intelligence in Diabetes Management Sales and Revenue Forecast (2022-2029)
8.3 Global Artificial Intelligence in Diabetes Management Sales, Revenue and Price Forecast by Type (2022-2029)
8.3.1 Global Artificial Intelligence in Diabetes Management Revenue and Growth Rate of Glucose Monitoring Devices (2022-2029)
8.3.2 Global Artificial Intelligence in Diabetes Management Revenue and Growth Rate of Diagnostic Devices (2022-2029)
8.3.3 Global Artificial Intelligence in Diabetes Management Revenue and Growth Rate of Insulin Delivery Devices (2022-2029)
8.3.4 Global Artificial Intelligence in Diabetes Management Revenue and Growth Rate of Others (2022-2029)
8.4 Global Artificial Intelligence in Diabetes Management Consumption Forecast by Application (2022-2029)
8.4.1 Global Artificial Intelligence in Diabetes Management Consumption Value and Growth Rate of Case-based Reasoning (2022-2029)
8.4.2 Global Artificial Intelligence in Diabetes Management Consumption Value and Growth Rate of Intelligent Data Analysis (2022-2029)
8.5 Artificial Intelligence in Diabetes Management Market Forecast Under COVID-199 Industry Outlook
9.1 Artificial Intelligence in Diabetes Management Market Drivers Analysis
9.2 Artificial Intelligence in Diabetes Management Market Restraints and Challenges
9.3 Artificial Intelligence in Diabetes Management Market Opportunities Analysis
9.4 Emerging Market Trends
9.5 Artificial Intelligence in Diabetes Management Industry Technology Status and Trends
9.6 News of Product Release
9.7 Consumer Preference Analysis
9.8 Artificial Intelligence in Diabetes Management Industry Development Trends under COVID-19 Outbreak
9.8.1 Global COVID-19 Status Overview
9.8.2 Influence of COVID-19 Outbreak on Artificial Intelligence in Diabetes Management Industry Development10 Research Findings and Conclusion11 Appendix
11.1 Methodology
11.2 Research Data Source
 

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Killexams : Cloud Migration Services Market Size to Reach Valuation of $340.7 Bn by 2028 | AWS, IBM, and Microsoft top Providers | Vantage Market Research

Vantage Market Research, The North Star for the Working World

WASHINGTON, Oct. 12, 2022 (GLOBE NEWSWIRE) -- Global cloud migration services market touched valuation of USD 92.4 Billion in 2021 and is projected to generate revenue of USD 340.7 Billion by 2028 at a CAGR of 24.30% during the forecast period, 2022–2028.

As businesses continue to grow larger and more complex, the need for an easier way to move their data and applications to the cloud becomes more apparent. Cloud migration services market is becoming a popular way to meet this need. The services offered by cloud migration providers can help companies move their data, applications, and servers to different cloud platforms, including Amazon Web Services, Google Cloud Platform, Microsoft Azure, and IBM BlueMix.

Some of these providers also offer managed migration services that include everything from data prepping and analysis to creating cloud-ready environments. This enables companies to focus on their business goals rather than spending time figuring out how to migrate their data. The demand for cloud migration services market is likely to increase as businesses become increasingly interested in moving their data to the cloud in order to decrease costs and Strengthen flexibility.

In addition to offering reliable cloud migration services, many professional cloud migration companies also offer other IT consulting services. This includes advice on how best to use the various features of the cloud, as well as help with implementing new technology in an effort to Strengthen business efficiency. By providing comprehensive solutions for both migrating data to and from the cloud, professional cloud migration companies are quickly becoming a valuable resource for businesses of all sizes.

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One provider in global cloud migration services market, SoftLayer by IBM, has seen rapid growth in exact years. Analyst from Vantage Market Research says that customers are looking for a "simple path" to migrating to the cloud. Migration can be complex and time-consuming, but SoftLayer emerging to provide as smooth as possible. The company offers a wide variety of services, including migrations between public clouds like Amazon Web Services (AWS) and Microsoft Azure, as well as private clouds like those run by companies such as Google and IBM. They also offer migration services from on-premises servers to virtual servers running in the cloud, as well as backup and disaster recovery services.

Global Cloud Migration Services Market Top Companies Profile:

  • AWS (US)

  • IBM (US)

  • Microsoft (US)

  • Google (US)

  • Cisco (US)

  • NTT Data (Japan)

  • DXC (US)

  • VMware (US)

  • Rackspace (US)

  • Informatica (US)

  • WSM (US)

  • Zerto (US)

  • Virtustream (US)

  • River Meadow (US)

  • OpenStack (US)

Key Finding of the Global Clod Migration Services Market

Cloud migration is one of the most complex and often time-consuming tasks for companies in today's ever-connected world. This is especially true for companies that have a global workforce and need to move employees from on-premises infrastructure to the cloud in the global cloud migration services market.

Vantage Market Research surveyed 50 providers of cloud migration services, ranging from small startups to global giants. The goal was to provide an overview of the market, identify key trends, and evaluate providers across eight categories: migration management, data migration, application migration, platform migration, infrastructure transformation, governance and security, and federation.

The results of the cloud migration services market survey are overwhelming in terms of both the breadth and depth of offerings available from these providers. Migration management (20%) is by far the most popular service category; data migration (21%), application migration (18%), platform migration (16%), infrastructure transformation (13%), and federation (12%) are all close behind.

Limited Time Offer | Buy this Premium Research Report with Exclusive Discount and Immediate Delivery@ https://www.vantagemarketresearch.com/buy-now/cloud-migration-services-market-1861/0

The report on cloud migration services market finds that a majority (60%) of enterprises have moved some or all application workloads to the cloud, but that only a fraction (10%) of these migrations have been accomplished using traditional migration techniques such as blue-sky planning, analysis, mapping and testing. Instead, most enterprise migrations are driven by emergent needs such as faster time to market or simplified management.

The top reasons cited for migrating to the cloud were cost savings and improved agility. Other reasons included delivering applications and services faster to customers and improving availability of workloads. Organizations are increasingly turning to cloud migration services in order to reduce costs and get applications up and running more quickly in the cloud. The report identifies five key strategies for migrating to the cloud: embracing public clouds, orchestrating private Clouds with public Clouds, developing hybrid clouds, making use of purpose-built infrastructure as a service provider and creating microservices architectures.

Scope of the Report:

Report Attributes

Details

Market Size in 2021

USD 92.4 Billion

Revenue Forecast by 2028

USD 340.7 Billion

CAGR

24.3% from 2022 to 2028

Base Year

2021

Forecast Year

2022 to 2028

Key Players

•  AWS (US)

•  IBM (US)

•  Microsoft (US)

•  Google (US)

•  Cisco (US)

•  NTT Data (Japan)

•  DXC (US)

•  VMware (US)

•  Rackspace (US)

•  Informatica (US)

•  WSM (US)

•  Zerto (US)

•  Virtustream (US)

•  River Meadow (US)

AWS, IBM, and Microsoft top Providers in Cloud Migration Services Market

AWS, IBM, and Microsoft are the top three most popular cloud migration service providers. AWS ranks first, with IBM coming in second and Microsoft third. AWS uses its own services, as well as partner services, to move applications to the cloud. AWS has a variety of tools and services to choose from, such as Elastic Beanstalk (which helps developers build and deploy cloud-based applications) and Amazon Sage Maker (a machine learning service).

IBM, a leading player in the global cloud migration services market, also has services to help companies migrate their applications to the cloud. One of IBM’s main offerings is its SoftLayer cohort, which provides businesses with access to IBM’s cloud infrastructure as a service. SoftLayer also offers migration assistance, DDoS protection, and application flexibility.

Microsoft Azure is another popular option for migrating applications to the cloud. Azure offers a wide range of features for building, deploying, and managing applications in the cloud. Azure also offers migration assistance and the ability to connect legacy systems to the cloud.

Vantage Market Research Study Says Enterprises are Deploying Cloud Migration Services to Reduce Complexity and Save Time

VMR’s survey on cloud migration services market is one of the most comprehensive surveys on the topic. The survey polled over 2,000 IT professionals who have experience with migrating workloads to the cloud.

The results of the survey showed that most respondents felt that cloud migration services were helpful in reducing complexity and saving time. However, there were some concerns raised about cost and security. Overall, the majority of respondents were satisfied with their experience using cloud migration services.

One of the key findings from the survey on cloud migration services market was that automated tools are critical for successful cloud migrations. Respondents who used automation reported higher levels of satisfaction with their overall experience. They also noted that automated tools helped reduce complexity and save time.

Another important finding was that training and support are essential for successful migrations. Respondents who had access to training and support reported higher levels of satisfaction with their experience. They also noted that training and support helped reduce complexity and save time.

Browse market data Tables and Figures spread through 147 Pages and in-depth TOC on Cloud Migration Services Market Forecast Report (2022-2028).

The Report on the Cloud Migration Services Market highlights:

  • Assessment of the market

  • Premium Insights into Industry

  • In-depth Competitive Landscape

  • COVID Impact Analysis

  • Historical Data, Current Data, and Forecast Data

  • Top and Emerging Company Profiles

  • Global and Regional Dynamics

In a exact survey of IT decision makers from around the global cloud migration services market, our study found that 43% of respondents are either already migrating or plan to do so in the next 12 months. The top reason for this migration activity is because employees demand access to the cloud for work-related tasks, with 54% citing access as the main motivation. In addition, 43% of respondents from large enterprises said their organization is using at least two MSPs for cloud migration services. The most popular use case for MSP services is transitioning workloads to the public cloud, cited by 53% of respondents.

Choosing the right cloud migration service is critical for success. Vantage found that 70% of respondents in the cloud migration services market report successful migrations when using a third-party service provider, but only 39% say the same about self-deployment. In addition, self-deployment requires more planning time than using a pre-packaged service from a third party (37% vs. 22%).

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We, at Vantage Market Research, provide quantified B2B high quality research on more than 20,000 emerging markets, in turn, helping our clients map out constellation of opportunities for their businesses. We, as a competitive intelligence market research and consulting firm provide end to end solutions to our client enterprises to meet their crucial business objectives. Our clientele base spans across 70% of Global Fortune 500 companies. The company provides high quality data and market research reports. The company serves various enterprises and clients in a wide variety of industries. The company offers detailed reports on multiple industries including Chemical Materials and Energy, Food and Beverages, Healthcare Technology, etc. The company’s experienced team of Analysts, Researchers, and Consultants use proprietary data sources and numerous statistical tools and techniques to gather and analyse information.

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