It’s said that the familiar adage, “The one constant is change” originated with the Greek philosopher Heraclitus. While this assertion may be centuries old, it could easily have been coined to describe the tech industry. And among the technologies that may soon be seeing revolutionary changes is the one familiar staple most of us use every day: the Web.

From Web3 and blockchain technology giving users more power, to new ways to explore and “experience” goods and services, to a growing governmental focus on protecting consumers’ data, the ways we browse, shop and interact on the Web may soon look very different. Below, 16 industry experts from Forbes Technology Council discuss the top trends they see coming to the Web within the next year or two and why they will be so impactful.

1. Highly Personalized Services Across Channels

Consumers increasingly expect services on the Web and mobile to be more than just a nice front for a traditional business. They expect a personalized, connected world, where all channels provide service in a real-time, intelligent, personalized manner. This hugely impacts operations, as complex businesses must break from the status quo and evolve to have a fully operationalized, end-to-end technology stack that meets consumer demand. - Udi Ziv, Earnix

2. The Metaverse

Within the next year, I see the metaverse being beautifully woven into the core fabrics of the Web. Both businesses and community-focused platforms, such as social media, will look to explore improving the user experience by creating more immersive, experiential ways for users to understand and interact with the value proposition they provide. - Joel Ogunsola, Prunedge Development Technologies Ltd

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3. Web3

Web3 is a game changer. As decentralized tech such as blockchain comes to power, the internet’s infrastructure, Web3, will be run by builders and users rather than “gatekeepers” such as the search engines and social platforms that largely control the Web today. This shift will change how data is held—from consumers offering their data for access to services, as we do today, to services offering data protection instead. - Sandeep Malhotra, Mastercard

4. Blockchain

A few changes are coming, but key among those is blockchain technology. As the world moves to granular democratization enabled by tech, blockchain is a key enabler, giving the power to the end user without intermediary help. And this power can be used not just for financial transactions but for any transactions—it enables them to be carried out discreetly, providing the user with privacy, confidentiality and control over their data and its uses at all times. - Vivek Shaurya, beGalileo

5. Enhanced Comparison Shopping Tools

With rampant inflation across the world in almost every product category, I see more consumers comparison shopping. That’s an obvious statement, but it will lead to more robust comparison calculators and technology across websites that typically don’t provide these services. Comparisons won’t just be to other products within the same brand; users will also be able to compare variables such as career or life fulfillment. How much do I value my time? Does this product provide joy and happiness? - Brad Redding, Elevar

6. Microtransactions To Access Content

I see a trend toward more microtransactions. The Web is too siloed at the moment, and almost no one can afford multiple subscriptions for quality content behind paywalls, paid newsletters and so on. The evolution toward bite-sized content, in which you’ll pay for the one article you want to read or the one video you want to watch via micro payment (likely on top of crypto rails), will unlock quality content for the masses and, hopefully, contribute to the general population being more informed. - Nico Girard, OXIO

7. New Personalization Strategies

As we witness the demise of the third-party cookie, it’s evident that a new and improved personalization strategy will have to take its place. Accordingly, we’ll see new strategies for online personalization—especially in e-commerce—gain traction this year as companies aim to prioritize such things as on-site actions and real-time, demonstrated preferences rather than demographic data. - Alexandre Robicquet, Crossing Minds

8. AI-Generated Content

One trend will be using artificial intelligence to create Web content that’s personalized to the individual customer. From shopping to support, this AI-generated Web content will create an experience akin to having a personal concierge. In addition, this trend will drive growth in AI-powered chatbots and voice assistants, evolving the Web into more conversational, rather than point-and-click, interactions. - Gary Nakanelua, Blueprint

9. ‘MOD-ifiable’ Software

“MOD-ifiable” software is a growing trend. In the gaming industry, developers have software frameworks—MODs—that let them add players, levels and worlds to their favorite games. MODs are coming to cloud-based enterprise software as well. A Web-based MOD framework unlocks, for example, the ability to inject thousands of pre-built AI models and D3 visual components into popular applications such as business intelligence tools. - Mark Palmer, TIBCO

10. Prescriptive Marketplaces

Marketplaces will become prescriptive. Websites collect and share tremendous amounts of information and have the intelligence to customize how they interact with you based on that data. Gone will be the days when you had to identify what you wanted and figure out where to get it. Instead, a bot (in your computer, phone or car) will anticipate your needs, notify you and explain how to address them. - Ari Kahn, Bridgeline Digital

11. ‘Meaning’ Creation

The infrastructure and industry standards of Web3, particularly the metaverse, are starting to solidify. As the market matures from its “gold rush” stage, we’re going to see a shift from immediate wealth creation to “meaning” creation. Expect to see more brands building curated metaverse experiences aimed at humanizing the time audiences spend online rather than simply adding to it. - Lincoln Wallen, Improbable Worlds

12. 3D Visualization

3D visualization is becoming the biggest trend in the world of the Web. As the Web has become more easily accessible, users are spending more time online. However, they require immersion—3D content—to gain in-depth perception. Services including Unity, PlayCanvas and PixiJS will make it happen.​​ Using them, you can create fantastic 3D graphics, thus turning a website into an entirely digital world where everything is possible. - Slava Podmurnyi, Visartech Inc.

13. Passwordless Authentication

I expect the World Wide Web to become much more secure. The commitments of Google, Microsoft and Apple to support the FIDO standard in 2023 will accelerate the availability of passwordless authentication and make it the modern standard. And then the problems of password management, weak passwords, credentials phishing and all kinds of password-based breaches will become history. - Aleksandr Galkin, Competera

14. Gamification

Gamification is likely to make a giant leap across all genres of websites, as brands are desperate and are trying innovative means to better engage with their customers. Those in catch-up mode will be forced to adopt basics such as goals and rewards, leaderboards, and so on, while the leaders will start forging cross-website, noncommercial, user-centric, secure gamification alliances with site-agnostic rewards. - Pramod Konandur Prabhakar, Pelatro PLC

15. More Consumer Data Privacy Regulations

More states will enact consumer data privacy protections. Europe’s General Data Protection Regulation and California’s California Consumer Privacy Act continue to pave the way for broader consumer data privacy practices, but operating virtually will continue to accelerate the demand for these protections. Consumers want to know that their privacy is being protected while they use digital services, especially now that most are operating digitally. - Stephen Ritter, Mitek Systems

16. Increased Accessibility Awareness

Judging from what’s been on our clients’ wish lists, accessibility awareness will continue to grow, especially if we’re talking about the public sector and other highly regulated industries. Ensuring professionals with disabilities have equal access to modern tech solutions is a major prerequisite to building an inclusive, welcoming and compliant workplace. - Konstantin Klyagin, Redwerk

PALO ALTO, Calif., July 12, 2022 — TIBCO Software Inc., a global leader in enterprise data, empowers its customers to connect, unify, and confidently predict business outcomes, solving the world’s most complex data-driven challenges. Today, TIBCO announced the release of TIBCO ModelOps, which enables businesses to deploy AI models faster, from anywhere to everywhere, safely and at scale. This addition to the company’s game-changing analytics portfolio helps customers simplify and scale cloud-based analytic model management, deployment, monitoring, and governance.

“While 92% of firms spent more overall on data science in 2021 compared to previous years, only 12.1% deployed it at scale¹. To help organizations realize the value of their AI deployments, we’ve designed a system that puts self-service access to data science firmly in the hands of teams, including business users,” said Mark Palmer, senior vice president, engineering, TIBCO. “This allows decision-making teams to choose the algorithm they want, work from any cloud service, and run it safely, securely, and at scale. This is a bold step to enabling business users to take AI out of the lab and out on the road.”

TIBCO ModelOps addresses the requirement for speed in deploying AI, and draws from TIBCO’s leadership in data science, data visualization, and business intelligence. This aids AI teams in confronting critical deployment hurdles like ease-of-applying analytics to applications, identification and mitigation of bias, and transparency and manageability of an algorithm’s behavior within business-critical applications. The solution enables businesses to deploy and manage model pipelines into production environments efficiently, and in robust ways. The TIBCO ModelOps solution is format-agnostic, supporting all common model formats, including API-based models in any cloud service or on-premises. TIBCO ModelOps makes it easy to add governed models to TIBCO Spotfire, TIBCO Data Virtualization, and TIBCO Streaming, with more to follow. Users looking to employ TIBCO ModelOps in existing environments can take advantage of its format-agnostic and open-standards approach.

The launch of TIBCO ModelOps is the culmination of TIBCO’s extensive work with customers and partners throughout the design and beta program of TIBCO ModelOps. “As the world’s second-largest memory chipmaker, we have aggressive growth goals as we expand our fabrication capacity. Optimizing the yield of our processes, predicting when problems are about to occur, and fixing them before they occur, is a huge competitive advantage for us,” said InSoo Ryu, technical leader, SK Hynix. “The ability to quickly deploy, measure, and adjust models of any kind – machine learning models, python code, rules and more – is essential to our success. TIBCO ModelOps is the right platform to scale our data science efforts with a more governed, process-oriented approach to data science operationalization.”

A exact survey of TIBCO customers confirmed that it’s no longer uncommon for organizations to manage hundreds – even thousands – of analytic models and workflows. TIBCO ModelOps allows any authorized business user, data scientist, analyst, or IT user to manage and deploy thousands of models in production with complete governance and management capabilities. Users are able to deploy in the cloud or on-premises, highlighting model performance through built-in, customizable dashboards powered by Spotfire. With TIBCO ModelOps, clients can now move past the worry of unintended negative consequences of failed automation because of complex or poorly managed AI or rules-based models, making it safer to automate based on validated and secure AI models.

Learn more about TIBCO ModelOps and its advanced analytics capabilities.

Note

¹New Vantage Partners, 2021 Big Data and AI Executive Survey, Tom Davenport and Randy Bean

About TIBCO

TIBCO Software Inc. unlocks the potential of real-time data for making faster, smarter decisions. Our Connected Intelligence Platform seamlessly connects any application or data source; intelligently unifies data for greater access, trust, and control; and confidently predicts outcomes in real time and at scale. Learn how solutions to our customers’ most critical business challenges are made possible by TIBCO at www.tibco.com.

Source: TIBCO

Operations staff get a hard time. The lowly systems administrator (sysadmin), database administrator (DBA) and all the other operations engineering team members from cyber penetration specialists to user acceptance testing (UAT) and so on are generally unloved.

This reality is why we used to talk about software application developers (who, you may have noticed, have been getting a lot of the limelight in exact years) finishing their application builds and then just ‘throwing it over the wall’ to the operations team to figure out how to provision backend systems and be able to run it.

Things have gotten better and the DevOps developer (Dev) + operations (Ops) drive to form a more coalseced workforce ethic and culture has progressed things, but not always.

Ops champions emerge

Clearly, we need to keep evolving DevOps and at the same time (and this could be the good news part for operations staff) we also need to start creating directly applied Ops functions to specific parts of the modern IT stack.

Key among these functions will be Artificial Intelligence (AI).

Enterprise data platform company Tibco wants to make life easier for the AI operations team (now commonly written as AIOps) with its ModelOps release. This software service is designed to enable businesses to deploy AI models faster across a broader range of devices, machines and user endpoints at scale. Sometimes written as TIBCO to denote the organization’s lengthy acronym (The Information Bus COmpany), the firm is known for its data integration pedigree and its data analytics portfolio.

To put it in really direct terms, this is scalable secure cloud-based data analytic model management, monitoring and governance - now with an increased focus and function set aligned to AI model deployment.

Ingredients in an AI model

When we talk about an AI ‘model’ in this sense, the term is used to encapsulate the algorithmic logic that goes into the AI engine (or brain) and it also straddles the critical life-support systems that the AI will need in order to work without bias, without loss of insight into what it is doing and with transparency of an algorithm’s behaviour within business-critical applications

In this case, Tibco ModelOps addresses the requirement for speed in deploying AI and draws from the company’s work in data science, data visualisation and business intelligence (BI). The software itself works to get AI models to a state where they can be deployed and managed into ‘model pipelines’ (a digital journey that describes the lifeblood, location, lifecycle and lifespan of an AI model) so that they can be moved into production environments efficiently in robust ways.

The Tibco ModelOps solution is format-agnostic, supporting all common model formats, including Application Programming Interface (API)-based models in any cloud service or on-premises. This service promises to make it easy to add governed models to other Tibco products including Tibco Spotfire (technology for data visualization, discovery, wrangling and predictive analytics), Tibco Data Virtualization and Tibco Streaming.

Mark Palmer, Tibco senior vice president of engineering points to New Vantage Partners, 2021 big data and AI executive survey by Tom Davenport and Randy Bean.

“While 92% of firms spent more overall on data science in 2021 compared to previous years, only 12.1% deployed it at scale [according to the above-linked survey]. To help organizations realise the value of their AI deployments, we’ve designed a system that puts self-service access to data science firmly in the hands of teams, including business users,” said Palmer. “This allows decision-making teams to choose the algorithm they want, work from any cloud service, and run it safely, securely, and at scale.”

AI road trip, out of the lab

These product developments from Tibco push AI to a new point according to Palmer i.e. he says that this is the moment where we can witness bold new steps as we now enable business users to take AI out of the lab and out on the road.

A 2022 survey of Tibco customers suggested that it's no longer uncommon for organizations to manage hundreds – even thousands – of analytic models and workflows. Tibco ModelOps claims to be able to allow any authorized business user, data scientist, analyst, or IT user to manage and deploy thousands of models in production with complete governance and management capabilities.

Users are able to deploy in the cloud or on-premises, highlighting model performance through built-in, customizable dashboards powered by Tibco Spotfire. This means that Tibco ModelOps, clients can now move past the worry of unintended negative consequences of failed automation because of complex or poorly managed AI or rules-based models, making it safer to automate based on validated and secure AI models.

Ops on the up

There’s a bit of the digital democratization transformation message here that we’re hearing from every enterprise technology platform worth its salt. There’s also a bit of the robust scalability message… and there’s obviously the all-important managed intelligence as a means of mitigating AI bias that we absolutely positively need to hear from every company in this space.

But that’s not to say that Tibco isn't coming forward with a genuinely new developmemt.

The company is (arguably) one of the first vendors many people think of when the subject turns to data integration, so there’s no reason why we shouldn’t now extend that thought to AI model data integration, governance, refinement, augmentation, management and visualization.

Ops is on the up and AI is helping to share the love, let’s never be haters.

Global Master Data Management (MDM) Market Size, Status, and Forecast 2022-2028. In-depth research accumulated to offer Latest insights about acute features of the global Master Data Management (MDM) market. This report provides a detailed overview of key factors in the Master Data Management (MDM) Market and factors such as driver, restraint, past and current trends, regulatory scenarios and technology development. The impact of the COVID-19 outbreak on the industry was fully assessed. Fully risk assessment and industry recommendations were made for Master Data Management (MDM) in a special period. This report also compares the markets of Pre COVID-19 and Post COVID-19. In addition, research considers the impact of COVID-19 on the regional economy.

Over the next five years the Master Data Management (MDM) market will register a 13.4% CAGR in terms of revenue, the global market size will reach US$ 6641.4 million by 2026.

Some of the key players profiled in the study are
SAP, Oracle, IBM, Informatica, Stibo Systems, TIBCO Software, Riversand Technologies, Orchestra Networks, EnterWorks, Magnitude, Talend, SAS Institute, Microsoft, KPMG, Teradata, Software AG, Agility Multichannel, VisionWare, SupplyOn AG, Sunway World, Yonyou, and Others.

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Market Outlook:
Master Data Management (MDM) is a method of helping organizations in linking all critical and important data to a master file.

MDM is the process of the collection of best data management practices. The benefits of the Master Data Management (MDM) model increase as the number and diversity of organizational units, the role of workers, and the expansion of computing applications. MDM may be more valuable to large or complex businesses than small, medium, or simple businesses. Master data management can facilitate the operation of a variety of system architectures, platforms and applications.

The key industries are: Banking, Finance and Insurance (BFSI); IT and Telecommunications, Government & Health Care, Manufacturing & Logistics, Others. Manufacturing & Logistics was the largest application which took up about 25.5% of the global total in 2017, closely followed by Banking, Finance and Insurance (BFSI); IT and Telecommunications.

The Leading growing markets are China, India, Southeast Asia, etc. USA, Europe, Japan, etc. are the mature market with lower growth rate.

USA is the largest consumption countries of master data management in the world in the past few years and it will keep increasing in the next few years. USA market took up about 35% the global market in 2017, while Europe was about 30%, and China is followed with the share about 10%.

USA, Denmark, UK and China are now the key developers of master data management. There are some other vendors, such as Sunway World, Yonyou, etc. in China, but the Chinese market is still controlled by foreign vendors.

SAP, Oracle, IBM, Informatica, Stibo Systems, TIBCO Software, Riversand Technologies, Orchestra Networks, EnterWorks and Magnitude are the key suppliers in the global Master data management market. Top 10 took up about 50% of the global market in 2017. Abroad vendors took up more than 50% of the Chinese market.

Most important types of Master Data Management (MDM) covered in this report are:
Customer Data

Product Data

Others

Most widely used downstream fields of Master Data Management (MDM) market covered in this report are:
Banking, Finance and Insurance (BFSI)

IT and Telecommunications

Government & Health Care

Manufacturing & Logistics

Others

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

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Impact of the Master Data Management (MDM) Market report:

–Comprehensive assessment of all opportunities and risk in the Master Data Management (MDM) Market.
–Master Data Management (MDM) Market exact innovations and major events.
–Detailed study of business strategies for growth of the Master Data Management (MDM) Market market-leading players.
–Conclusive study about the growth plot of Master Data Management (MDM) Market for forthcoming years.
–In-depth understanding of Master Data Management (MDM) Market market-particular drivers, constraints and major micro markets.
–Favorable impression inside vital technological and market latest trends striking the Master Data Management (MDM) Market.

 Strategic Points Covered in Table of Content of Master Data Management (MDM) Market:

– Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Global Master Data Management (MDM) market (2022-2028).

– Chapter 2: Exclusive Summary – the basic information of the Global Master Data Management (MDM) Market.

– Chapter 3: Changing Impact on Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Global Master Data Management (MDM); Post COVID Analysis.

– Chapter 4: Presenting the Global Master Data Management (MDM) Market Factor Analysis, Post COVID Impact Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

– Chapter 5: Displaying the by Type, End User and Region/Country 2018-2022.

– Chapter 6: Evaluating the leading manufacturers of the Global Master Data Management (MDM) Market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile.

– Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2022-2028).

… To be continued

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Data management firm TIBCO has unveiled its new TIBCO ModelOps platform designed to enable faster deployment of AI models at scale.

The Palo Alto-based company cited a 2021 survey from NewVantage Partners that showed a majority of surveyed companies are spending more on their AI initiatives, yet very few have deployed models on a large enough scale for tangible business value or problem solving.

“While 92% of firms spent more overall on data science in 2021 compared to previous years, only 12.1% deployed it at scale. To help organizations realize the value of their AI deployments, we’ve designed a system that puts self-service access to data science firmly in the hands of teams, including business users,” said Mark Palmer, senior VP of engineering, TIBCO. “This allows decision-making teams to choose the algorithm they want, work from any cloud service, and run it safely, securely, and at scale. This is a bold step to enabling business users to take AI out of the lab and out on the road.”

AI operations teams are tasked with building and managing AI models into production environments quickly and efficiently, but problems can arise, especially with large scale projects. TIBCO says its ModelOps solution “aids AI teams in confronting critical deployment hurdles like ease-of-applying analytics to applications, identification and mitigation of bias, and transparency and manageability of an algorithm’s behavior within business-critical applications.” The product is format-agnostic and supports all common model formats, whether in the cloud or on premises, including API-based models. Governed models can be added to the company’s other solutions such as its Spotfire analytics platform, its on-demand Data Virtualization tool, or its streaming analytics platform, TIBCO Streaming.

TIBCO surveyed its own customers and found that many organizations are managing hundreds or even thousands of analytic models and workflows. The company asserts its ModelOps uses low or no-code tooling and is suitable for all users to manage and deploy models, whether they are data scientists or analysts, IT or business users, with total governance and management capabilities. The product features model performance observability options through customizable Spotfire dashboards, and TIBCO says that problems are addressed before automation failure occurs, ensuring more safety and security of deployment.

South Korean memory chipmaker SK Hynix was part of TIBCO’s design and beta testing program for ModelOps: “As the world’s second-largest memory chipmaker, we have aggressive growth goals as we expand our fabrication capacity. Optimizing the yield of our processes, predicting when problems are about to occur, and fixing them before they occur, is a huge competitive advantage for us,” said InSoo Ryu, technical leader, SK Hynix. “The ability to quickly deploy, measure, and adjust models of any kind – machine learning models, python code, rules and more—is essential to our success. TIBCO ModelOps is the right platform to scale our data science efforts with a more governed, process-oriented approach to data science operationalization.”

This chart shows the process of the ModelOps workflow. Click to enlarge. Source: TIBCO

TIBCO also released a master data management SaaS solution, TIBCO Cloud EBX. Cloud EBX users can manage their corporate data, including master data, reference data, and metadata, from anywhere. “The solution is part of TIBCO Cloud Passport, a new consumption-based pricing plan, which enables flexible FinOps (financial operations) and access to all TIBCO SaaS capabilities under a single model. This allows companies to quickly scale their MDM needs without operational complexity,” the company said.

Additionally, TIBCO has announced a significant expansion of its TIBCO Cloud Integration iPaaS product which it says broadens capabilities for integrating applications, data, devices, or other digital assets across hybrid environments. Much like the emphasis on speed seen with ModelOps, Cloud Integration can help businesses accelerate and simplify their application development to stay ahead of the competition.

“It’s essential for organizations to focus on data to overcome today’s many business challenges. Properly leveraging data can empower businesses to turn those challenges into opportunities,” said Randy Menon, senior vice president and general manager, Connect and TIBCO Cloud, TIBCO. “TIBCO Cloud delivers scalable, adaptable solutions that drive integration between all systems, operations, and processes. Together, we enable our customers to unlock the power of real-time data.”

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Embedded Analytics market Global, analyzes and researches the Instant Payments development status and forecast in United States, EU, Japan, China, India and Southeast Asia. This report focuses on the top players in global market. Top Key Players are – Sisense, Inc., SAS Institute, Microsoft Corporation, Qliktech International Ab, Information Builders, Tibco Software, Inc., BIRST, Inc., Microstrategy Incorporated, Yellowfin International Pty Ltd, Oracle Corporation, Opentext Corporation, SAP SE, Logi Analytics, Tableau Software Inc..

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Embedded Analytics Market Research Report is spread across 99 pages and provides exclusive data, information, crucial statistics, top trends, and competitive landscape details in this niche sector

The Embedded Analytics market has witnessed growth from Million USD to Multimillion USD from 2017 to 2022. With the magnificent CAGR, this market is estimated to reach Multimillion USD in 2029.

This report will help you in making informed business decisions and navigate the innovations taken place in the Embedded Analytics market at one place. The report has applied appropriate methods to analyse the Embedded Analytics market. The report has evaluated the data collecting primary and secondary data. The relevant market information is collected from government databases, newspapers, personal interviews, project reports official websites.

The Embedded Analytics market report provides a detailed analysis of global market size, regional and country-level market size, segmentation market growth, market share, competitive Landscape, sales analysis, impact of domestic and global market players, value chain optimization, trade regulations, exact developments, opportunities analysis, strategic market growth analysis, product launches, area marketplace expanding, and technological innovations.

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Insights and Tools:

• Project product values and regional Embedded Analytics markets are estimated by market analyst, data analyst and people from related industry, based on company’s’ revenue and applications market respectively.
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• Analyses of global market trends, with historical data, estimates for 2022 and projections of compound annual growth rates (CAGRs) through 2029
• The market research includes historical and forecast data from like demand, application details, price trends, and company shares by geography, especially focuses on the key regions like United States, European Union, China, Japan, and other regions.
• In addition, the report provides insight into main Embedded Analytics drivers, challenges, opportunities and risk of the market and strategies of suppliers. Key players are profiled as well with their market shares in the global market discussed.

Embedded Analytics Market – Competitive and Segmentation Analysis:

Furthermore, providing an overview of successful top marketing strategies, industry opportunities, contributions, and exact developments of top leading companies, the report also offers a complete overview of leading companies’ past and present performance. Several methodologies and analyses are used in the research report to provide in-depth and accurate information about the Embedded Analytics Market

List of TOP KEY PLAYERS in Embedded Analytics Market Report are

• Sisense, Inc.
• SAS Institute
• Microsoft Corporation
• Qliktech International Ab
• Information Builders
• Tibco Software, Inc.
• BIRST, Inc.
• Microstrategy Incorporated
• Yellowfin International Pty Ltd
• Oracle Corporation
• Opentext Corporation
• SAP SE
• Logi Analytics
• Tableau Software Inc.

Embedded Analytics Market Forecast report gives required information regarding the total valuation that this industry holds presently, and it also lists the segmentation of the market along with the growth opportunities present across this business vertical. The Global Embedded Analytics market growth report 2022 research provides a basic overview of the industry including definitions, classifications, applications and industry chain structure. Moreover, Consumer behaviour analysis and market dynamics like drivers, restraints, opportunities and provides crucial information for knowing the Embedded Analytics market. The impact of the COVID-19 pandemic on Embedded Analytics market share, global consumer prices, and annual growth rate was also examined in the study.

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The Global Embedded Analytics market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2029. In 2021, the market is growing at a steady rate and with the rising adoption of strategies by leading players, the market is expected to rise over the projected horizon.

Final Report will add the analysis of the impact of COVID-19 on this industry.

COVID-19 Impact:

Report covers Impact of Coronavirus COVID-19: Since the COVID-19 virus outbreak in December 2019, the disease has spread to almost every country around the globe with the World Health Organization declaring it a public health emergency. The global impacts of the coronavirus disease 2019 (COVID-19) are already starting to be felt, and will significantly affect the Fiberglass Tanks market in 2021. The outbreak of COVID-19 has brought effects on many aspects, like flight cancellations; travel bans and quarantines; restaurants closed; all indoor/outdoor events restricted; over forty countries state of emergency declared; massive slowing of the supply chain; stock market volatility; falling business confidence, growing panic among the population, and uncertainty about future.

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On the basis of product, this report displays the production, revenue, price, market share and growth rate of each type, primarily split into

On the basis of the end users/applications, this report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including

• Banking, Financial Services, and Insurance
• Healthcare and Life Sciences
• Manufacturing
• Retail and Consumer Goods
• Energy and Utilities
• Telecommunications and IT
• Transportation and Logistics

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This Embedded Analytics Market Report Provides Comprehensive Analysis:

• The points that are discussed within the report are the major Embedded Analytics market players that are involved in the market such as market players, raw material suppliers, equipment suppliers, end users, traders, distributors and etc.
• The complete profile of the companies is mentioned. And the capacity, production, price, revenue, cost, gross, gross margin, sales volume, sales revenue, consumption, growth rate, import, export, supply, future strategies, and the technological developments that they are making are also included within the report. This report analysed data history and forecast.
• The growth factors of the market are discussed in detail wherein the different end users of the market are explained in detail.
• Data and information by market player, by region, by type, by application and etc., and custom research can be added according to specific requirements.
• The report contains the SWOT analysis of the market. Finally, the report contains the conclusion part where the opinions of the industrial experts are included.

Key Reasons to Buy this Embedded Analytics Industry Report:

• To gain insightful analyses of the market and have comprehensive understanding of the global Embedded Analytics market and its commercial landscape.
• Assess the production processes, major issues, and solutions to mitigate the development risk.
• To understand the most affecting driving and restraining forces in the market and its impact in the global market.
• Learn about the Embedded Analytics market strategies that are being adopted by leading respective organizations.
• To understand the future Embedded Analytics market outlook and prospects for the market.
• Besides the standard structure reports, we also provide custom research according to specific requirements.

Geographically,the report includes the research on production, consumption, revenue, market share and growth rate, and forecast (2017 -2029) of the following regions:

• United States
• Europe (Germany, UK, France, Italy, Spain, Russia, Poland)
• China
• Japan
• India
• Southeast Asia (Malaysia, Singapore, Philippines, Indonesia, Thailand, Vietnam)
• Latin America (Brazil, Mexico, Colombia)
• Middle East and Africa (Saudi Arabia, United Arab Emirates, Turkey, Egypt, South Africa, Nigeria)
• Other Regions

Years considered for this report:

Historical Years: 2017-2021

Base Year: 2021

Estimated Year: 2022

Forecast Period: 2022-2029

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Major Points from Table of Contents:

1 Embedded Analytics Market Overview1.1 Product Overview and Scope of Embedded Analytics
1.2 Embedded Analytics Segment by Type
1.2.1 Global Embedded Analytics Sales and CAGR Comparison by Type (2017-2029)
1.2.2 The Market Profile of Fluid Management system
1.2.3 The Market Profile of Fluid Management Disposables and Accessories
1.2.4 The Market Profile of Visualization System and Accessories Market
1.3 Global Embedded Analytics Segment by Application
1.3.1 Embedded Analytics Consumption (Sales) Comparison by Application (2017-2029)
1.3.2 The Market Profile of Neurology
1.3.3 The Market Profile of Laparoscopy
1.3.4 The Market Profile of Urology
1.3.5 The Market Profile of Arthroscopy

2 Global Embedded Analytics Market Landscape by Player
2.1 Global Embedded Analytics Sales and Share by Player (2017-2022)
2.2 Global Embedded Analytics Revenue and Market Share by Player (2017-2022)
2.3 Global Embedded Analytics Average Price by Player (2017-2022)
2.4 Global Embedded Analytics Gross Margin by Player (2017-2022)
2.5 Embedded Analytics Manufacturing Base Distribution, Sales Area and Product Type by Player
2.6 Embedded Analytics Market Competitive Situation and Trends
2.6.1 Embedded Analytics Market Concentration Rate
2.6.2 Embedded Analytics Market Share of Top 3 and Top 6 Players
2.6.3 Mergers and Acquisitions, Expansion

3 Embedded Analytics Upstream and Downstream Analysis
3.1 Embedded Analytics Industrial Chain Analysis
3.2 Key Raw Materials Suppliers and Price Analysis
3.3 Key Raw Materials Supply and Demand Analysis
3.4 Manufacturing Process Analysis
3.5 Market Concentration Rate of Raw Materials
3.6 Downstream Buyers
3.7 Value Chain Status Under COVID-19

4 Embedded Analytics Manufacturing Cost Analysis
4.1 Manufacturing Cost Structure Analysis
4.2 Embedded Analytics Key Raw Materials Cost Analysis
4.2.1 Key Raw Materials Introduction
4.2.2 Price Trend of Key Raw Materials
4.3 Labor Cost Analysis
4.3.1 Labor Cost of Embedded Analytics Under COVID-19
4.4 Energy Costs Analysis
4.5 RandD Costs Analysis

Get a trial Copy of the Embedded Analytics Market Report 2022

5 Market Dynamics
5.1 Drivers
5.2 Restraints and Challenges
5.3 Opportunities

6 Players Profiles
6.1.1 Basic Information, Manufacturing Base, Sales Area and Competitors
6.1.2 Embedded Analytics Product Profiles, Application and Specification
6.1.3 Embedded Analytics Market Performance (2017-2022)
6.1.4 Business Overview

7 Global Embedded Analytics Sales and Revenue Region Wise (2017-2022
7.1 Global Embedded Analytics Sales and Market Share, Region Wise (2017-2022)
7.2 Global Embedded Analytics Revenue (Revenue) and Market Share, Region Wise (2017-2022)
7.3 Global Embedded Analytics Sales, Revenue, Price and Gross Margin (2017-2022)
7.4 United States Embedded Analytics Sales, Revenue, Price and Gross Margin (2017-2022)
7.4.1 United States Embedded Analytics Market Under COVID-19
7.5 Europe Embedded Analytics Sales, Revenue, Price and Gross Margin (2017-2022)
7.5.1 Europe Embedded Analytics Market Under COVID-19
7.6 China Embedded Analytics Sales, Revenue, Price and Gross Margin (2017-2022)

8 Global Embedded Analytics Sales, Revenue (Revenue), Price Trend by Type
8.1 Global Embedded Analytics Sales and Market Share by Type (2017-2022)
8.2 Global Embedded Analytics Revenue and Market Share by Type (2017-2022)
8.3 Global Embedded Analytics Price by Type (2017-2022)
8.4 Global Embedded Analytics Sales Growth Rate by Type (2017-2022)

9 Global Embedded Analytics Market Analysis by Application
9.1 Global Embedded Analytics Consumption and Market Share by Application (2017-2022)
9.2 Global Embedded Analytics Consumption Growth Rate by Application (2017-2022)
9.2.1 Global Embedded Analytics Consumption Growth Rate of Neurology (2017-2022)
9.2.2 Global Embedded Analytics Consumption Growth Rate of Laparoscopy (2017-2022)
9.2.3 Global Embedded Analytics Consumption Growth Rate of Urology (2017-2022)
9.2.4 Global Embedded Analytics Consumption Growth Rate of Arthroscopy (2017-2022)

10 Global Embedded Analytics Market Forecast (2022-2029)
10.1 Global Embedded Analytics Sales, Revenue Forecast (2022-2029)
10.1.1 Global Embedded Analytics Sales and Growth Rate Forecast (2022-2029)
10.1.2 Global Embedded Analytics Revenue and Growth Rate Forecast (2022-2029)
10.1.3 Global Embedded Analytics Price and Trend Forecast (2022-2029)
10.2 Global Embedded Analytics Sales and Revenue Forecast, Region Wise (2022-2029)

11 Research Findings and Conclusion

12 Appendix
12.1 Methodology
12.2 Research Data Source

…………Continued

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To view the original version on The Express Wire visit Embedded Analytics Market Future Trends, Size, Share, Growth Factors, 2022 Top Leaders, Competitive Landscape and Regional Forecast 2029

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

Aug 04, 2022 (Alliance News via COMTEX) -- Key Companies Covered in the Blockchain for Supply Chain Research are Auxesis Group, Omnichain, Transchain, Blockverify, Bitfury, Vechain Foundation, Oracle, Huawei, Tibco Software, Nodalblock, Openxcell, Peer Ledger, Accenture, IBM, Datex Corporation, Applied Blockchain, Chainvine, BTL Group, AWS, Digital Treasury Corporation, Ownest, Microsoft, Recordskeeper, Guardtime, SAP SE and other key market players.

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

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

Jul 27, 2022 (Alliance News via COMTEX) -- New York (US) - Key Companies Covered in the Function-as-a-Service Market Research are IBM (US), Google (US), Microsoft (US), Amazon Web Services(US), SAP (Germany), Dynatrace (US), Infosys (India), Rogue Wave Software (US), TIBCO Software (US), Fiorano Software and Affiliates (US) and other key market players.

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

(Bloomberg) -- Tom Krause, who stepped down Monday as president of Broadcom Inc.’s software group, has been named chief executive officer of the company being formed via the merger of Citrix Systems Inc. and Tibco Software.

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Citrix said Monday that Krause is to become CEO after that deal closes, confirming a report by Bloomberg News. The transaction is slated to close in the third quarter.

Krause, 44, was one of the chief negotiators in Broadcom’s $61 billion acquisition of cloud-computing company VMware Inc. He joined Broadcom in 2012 and became its chief financial officer in 2016. Since 2020, he’s led the chip firm’s six software divisions.

Elliott Investment Management and Vista Equity Partners agreed to buy Citrix in January for about $13 billion, with plans to merge it with Vista portfolio company Tibco.

“Tom is the right leader for the combined company, bringing decades of deep industry experience and an unparalleled track record of building companies and setting them up for sustainable growth and value creation,” Elliott’s head of North American private equity David Kerko, said in a statement.

Vista Equity Partners Managing Director John Stalder said the firm has the “highest confidence in Tom’s ability to lead the combined teams.”

Citrix makes software that workers use to log onto to their corporate programs virtually. Tibco is an enterprise data management firm. The combination will create one of the world’s largest software providers, serving 400,000 customers, according to a statement announcing the merger.

“I am excited to partner with the leadership teams and talented employees from Citrix and Tibco around the world to drive growth and ensure a successful path forward for the combined company,” Krause said.

Story continues

(Updates with confirmation from press releases started in first paragraph)

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