IBM has published details on a collection of techniques it hopes will usher in quantum advantage, the inflection point at which the utility of quantum computers exceeds that of traditional machines.
The focus is on a process known as error mitigation, which is designed to Excellerate the consistency and reliability of circuits running on quantum processors by eliminating sources of noise.
IBM says that advances in error mitigation will allow quantum computers to scale steadily in performance, in a similar pattern exhibited over the years in the field of classical computing.
Although plenty has been said about the potential of quantum computers, which exploit a phenomenon known as superposition to perform calculations extremely quickly, the reality is that current systems are incapable of outstripping traditional supercomputers on a consistent basis.
A lot of work is going into improving performance by increasing the number of qubits on a quantum processor, but researchers are also investigating opportunities related to qubit design, the pairing of quantum and classical computers, new refrigeration techniques and more.
IBM, for its part, has now said it believes an investment in error mitigation will bear the most fruit at this stage in the development of quantum computing.
“Indeed, it is widely accepted that one must first build a large fault-tolerant quantum processor before any of the quantum algorithms with proven super-polynomial speed-up can be implemented. Building such a processor therefore is the central goal for our development,” explained IBM, in a blog post (opens in new tab).
“However, exact advances in techniques we refer to broadly as quantum error mitigation allow us to lay out a smoother path towards this goal. Along this path, advances in qubit coherence, gate fidelities, and speed immediately translate to measurable advantage in computation, akin to the steady progress historically observed with classical computers.”
The post is geared towards a highly technical audience and goes into great detail, but the main takeaway is this: the ability to quiet certain sources of error will allow for increasingly complex quantum workloads to be executed with reliable results.
According to IBM, the latest error mitigation techniques go “beyond just theory”, with the advantage of these methods having already been demonstrated on some of the most powerful quantum hardware currently available.
“At IBM Quantum, we plan to continue developing our hardware and software with this path in mind,” the company added.
“At the same time, together with our partners and the growing quantum community, we will continue expanding the list of problems that we can map to quantum circuits and develop better ways of comparing quantum circuit approaches to traditional classical methods to determine if a problem can demonstrate quantum advantage. We fully expect that this continuous path that we have outlined will bring us practical quantum computing.”
The latest research report on the Enterprise Search Market from Coherent Market Insights aims to provide a complete and accurate analysis of the market, taking into account market prediction, competitive intelligence, technical risks, developments, and other relevant data. Its meticulously designed market intelligence allows market participants to understand the most essential market trends that affect their organisation. Significant prospects in the global Enterprise Search market, as well as important issues driving and hindering growth, will be discussed for readers. It provides information on key production, revenue, and consumption trends that businesses can use to boost sales and growth in the global Market.
global enterprise search market is estimated to be valued at US$ 4,583.3 million in 2021 and is expected to exhibit a CAGR of 11.5% over the forecast period (2021-2028)
𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗮 𝘀𝗮𝗺𝗽𝗹𝗲 𝘁𝗼 𝗼𝗯𝘁𝗮𝗶𝗻 𝗮𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗺𝗮𝗿𝗸𝗲𝘁 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗮𝘁-
The analysts of the Enterprise Search Market Report have done a fantastic job of exploring important advancements, pricing and business techniques, and future plans of prominent businesses using a detailed analysis of the competitive environment. Analysts revealed production, serving area, gross margin, and other vital elements in addition to the player’s Enterprise Search market performance in terms of revenue and sales. In addition, the Enterprise Search Report examines rivals’ market positioning, market growth, and product portfolios in depth to assist firms in gaining a competitive advantage. The study evaluates each company’s strengths and weaknesses using a SWOT analysis. It also assesses the parent market’s tendencies, as well as macroeconomic statistics, prevalent forces, and market appeal according to various segments. The research also forecasts the impact of several industry factors on key Enterprise Search market segments and regions.
The degree of competition among significant global corporations has been illuminated through an examination of various key global players. The expert team of research analysts throws light on many aspects of the Enterprise Search market, including global market competition, share, current industry developments, innovative product launches, partnerships, mergers, and acquisitions by key firms. Research approaches were used to analyse the leading players in order to gain insight into global competition.
𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗜𝗻𝗰𝗹𝘂𝗱𝗲: IBM Corporation, Lucid Work Incorporation, Microsoft Corporation, Dassault Systems S.A., Oracle Corporation, X1 Technologies Inc., SAP AG, Coveo Corporation, and Attivio Software Incorporation
» 𝗡𝗼𝗿𝘁𝗵 𝗔𝗺𝗲𝗿𝗶𝗰𝗮: United States, Canada, and Mexico
» 𝗦𝗼𝘂𝘁𝗵 & 𝗖𝗲𝗻𝘁𝗿𝗮𝗹 𝗔𝗺𝗲𝗿𝗶𝗰𝗮: Argentina, Chile, Brazil and Others
» 𝗠𝗶𝗱𝗱𝗹𝗲 𝗘𝗮𝘀𝘁 & 𝗔𝗳𝗿𝗶𝗰𝗮: Saudi Arabia, UAE, Israel, Turkey, Egypt, South Africa & Rest of MEA.
» 𝗘𝘂𝗿𝗼𝗽𝗲: UK, France, Italy, Germany, Spain, BeNeLux, Russia, NORDIC Nations and Rest of Europe.
» 𝗔𝘀𝗶𝗮-𝗣𝗮𝗰𝗶𝗳𝗶𝗰: India, China, Japan, South Korea, Indonesia, Thailand, Singapore, Australia and Rest of APAC.
𝗚𝗲𝘁 𝗣𝗗𝗙 𝗕𝗿𝗼𝗰𝗵𝘂𝗿𝗲: https://www.coherentmarketinsights.com/insight/request-pdf/4756
The Enterprise Search Market is primarily driven by a few important aspects, including increasing product appeal among consumers, effective promotional techniques in previously untapped markets, and significant investments in product development. Furthermore, businesses are attempting to keep up with rising demand and deliver the appropriate volume of products to the market.
There are a few trends in the Enterprise Search market that may assist organisations in developing more effective strategies. The research covers the most exact information about current events. This information is useful for businesses planning to produce significantly improved things, as well as for customers gaining an idea of what will be available in the future.
Reasons to Buy:
• Save time and effort while conducting entry-level research by determining the global Enterprise Search Market’s growth, size, key players, and segments.
• Highlights major business priorities to assist businesses in reforming their business strategy and establishing themselves throughout a broad geographic area.
• The major findings and suggestions in this report highlight important progressive industry trends in the Enterprise Search Market, helping players to devise effective long-term strategies for maximising market income.
• Develop/modify business expansion strategies that take advantage of significant growth opportunities in developed and emerging regions.
• Examine worldwide market trends and outlook in depth, as well as market drivers and restraints.
• Excellerate decision-making by learning about the techniques that support commercial interest in terms of products, segmentation, and industry verticals.
𝗚𝗲𝘁 𝟮𝟬𝟬𝟬 𝗨𝗦𝗗 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁 𝗼𝗻 𝗕𝘂𝘆𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗥𝗲𝗽𝗼𝗿𝘁: https://www.coherentmarketinsights.com/promo/buynow/4756
➣ What is the size of the Enterprise Search market, and what is the predicted rate of growth?
➣ What are the major variables that are propelling the Enterprise Search Market forward?
➣ What are the leading companies in the Enterprise Search industry?
➣ What are the numerous types of the Enterprise Search Market?
➣ Which segment or region will grow the fastest?
➣ What role do critical players play in the value chain?
➣ Over the forecast period, which applications and product segments are expected to be the most profitable?
➣ What factors are expected to hamper the global Enterprise Search market’s expansion?
➣ What will be the Enterprise Search market’s CAGR and size during the forecast period?
Table Of Content:
1. Research Objectives and Assumptions
2. Market Purview
3. Market Dynamics, Regulations, and Trends Analysis
About Coherent Market Insights:
Coherent Market Insights is a global market intelligence and consulting organization that provides syndicated research reports, customized research reports, and consulting services. We are known for our actionable insights and authentic reports in various domains including aerospace and defense, agriculture, food and beverages, automotive, chemicals and materials, and virtually all domains and an exhaustive list of sub-domains under the sun. We create value for clients through our highly reliable and accurate reports. We are also committed in playing a leading role in offering insights in various sectors post-COVID-19 and continue to deliver measurable, sustainable results for our clients.
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The post Enterprise Search Market to Witness Massive Growth by 2028 | IBM Corporation, Lucid Work Incorporation, Microsoft Corporation, Dassault Systems S.A. appeared first on Gatorledger.
IBM’s Watson is being used by the All England Lawn Tennis Club (AELTC) as it strives to attract and retain digital audiences to the 154-year-old Wimbledon tennis championship.
After more than 30 years of providing the AELTC with technology for collecting statistics, as well as the IT foundations underpinning them, IBM is constantly working to help the organisation automate digital services and engage with fans.
Today, IBM Watson artificial intelligence (AI), sitting in IBM Cloud, is personalising content to encourage fans who try out digital platforms to do so again and again.
“Our main goal is to ensure we are maintaining Wimbledon’s relevance, attracting online audiences and providing them with the opportunity to engage with the event and keep coming back,” she told Computer Weekly.
The partnership with IBM, also a sponsor, has come a long way since the original agreement in 1990 saw IBM generate rudimentary stats for the AELTC. “IBM has helped us ensure we have the foundations to do that from a broader technology perspective, and [with IBM] we are continually challenging ourselves to innovate on what we have today and that we are adapting the way we provide for fans,” added Willis.
Watson is the nucleus of much of the latest innovation, with personalised services. For instance, today Watson is automatically creating highlight reels tailored for individual fans, using a combination of structured and unstructured data.
The ability of AI to automate the creation of personalised reels of match action is perhaps the most overt example of progress. In the past, the creation of highlight reels for broadcasters required humans to manually go through matches and pick out the key moments, which was very time-consuming. But today, Watson can create a reel automatically that is personalised for individual fans.
“These two-minute reels are automatically created by Watson through a combination of stats, listening to the crowd reaction and looking at the gestures of the players,” said Kevin Farrar, IBM UK sports partnership lead. “We then make it available to the Wimbledon digital team.”
Kevin Farrar, IBM
A huge amount of data is generated across the 18 courts at Wimbledon, and without in-depth knowledge, it is difficult for the average digital fan to fully appreciate a game. “It’s all reaching slightly different audiences, which was our goal, rather than preaching to the converted,” said Willis.
This is where IBM data scientists, combined with tennis experts, come in. “We take the tennis stats and combine it with other data sources, such as the Hawkeye system tracking the player and ball movements throughout a rally. We then create insights which are shared to different audiences,” said Farrar.
“We work with the club to bring the beauty and drama of Wimbledon to life for digital fans around the world,” he added. “It is essentially a massive data operation. It all starts with the data. Turning it into meaningful and engaging insights that we can put out on digital global platforms.”
Another popular digital offering is the IBM Power Index which ranks player momentum, form and performance of players in the lead-up to and during the championships. It looks at structured data such as results, but also unstructured data, including the buzz is in the media. It then applies an AI algorithm which comes up with a ranking for players.
“The Power Index was designed to help fans work out who to follow, and there has been good engagement with that,” said Willis. “Then, once fans have taken an interest in a player, we wanted to educate them on what to look out for in a match.” Another tool, Match Insights, presents fans with facts and allows them to challenge Watson and other users in making match predictions based on the detailed stats they receive.
There has been success in building audiences through digital platforms like these, according to Willis. “We have seen steady growth of digital platforms,” she said. “When I started here about 10 years ago, we were getting an audience of about 11 million unique devices. In 2016, we had a record of 21 million unique devices connect, when Andy Murray won. We are on course for a very successful tournament this year.”
“Beyond scale, it is about demographics and location. We are proud to be a global brand and our audience reflects that,” she added. “In terms of a younger audience, we are developing things using AI to help young people better understand tennis, so when they stumble upon it they are fans for life.”
Wimbledon is part of IBM’s global sports portfolio, which includes the Masters golf and the US Open tennis. It has teams that work all year around from the UK and Atlanta, US.
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As the world becomes increasingly data-driven, businesses must find suitable solutions to help them achieve their desired outcomes. Data lake storage has garnered the attention of many organizations that need to store large amounts of unstructured, raw information until it can be used in analytics applications.
The data lake solution market is expected to grow rapidly in the coming years and is driven by vendors that offer cost-effective, scalable solutions for their customers.
Learn more about data lake solutions, what key features they should have and some of the top vendors to consider this year.
A data lake is defined as a single, centralized repository that can store massive amounts of unstructured and semi-structured information in its native, raw form.
It’s common for an organization to store unstructured data in a data lake if it hasn’t decided how that information will be used. Some examples of unstructured data include images, documents, videos and audio. These data types are useful in today’s advanced machine learning (ML) and advanced analytics applications.
Data lakes differ from data warehouses, which store structured, filtered information for specific purposes in files or folders. Data lakes were created in response to some of the limitations of data warehouses. For example, data warehouses are expensive and proprietary, cannot handle certain business use cases an organization must address, and may lead to unwanted information homogeneity.
On-premise data lake solutions were commonly used before the widespread adoption of the cloud. Now, it’s understood that some of the best hosts for data lakes are cloud-based platforms on the edge because of their inherent scalability and considerably modular services.
A 2019 report from the Government Accountability Office (GAO) highlights several business benefits of using the cloud, including better customer service and the acquisition of cost-effective options for IT management services.
Cloud data lakes and on-premise data lakes have pros and cons. Businesses should consider cost, scale and available technical resources to decide which type is best.
Read more about data lakes: What is a data lake? Definition, benefits, architecture and best practices
It’s critical to understand what features a data lake offers. Most solutions come with the same core components, but each vendor may have specific offerings or unique selling points (USPs) that could influence a business’s decision.
Below are five key features every data lake should have:
Data lakes that offer diverse interfaces, APIs and endpoints can make it much easier to upload, access and move information. These capabilities are important for a data lake because it allows unstructured data for a wide range of use cases, depending on a business’s desired outcome.
ML engineers, data scientists, decision-makers and analysts benefit most from a centralized data lake solution that stores information for easy access and availability. This characteristic can help data professionals and IT managers work with data more seamlessly and efficiently, thus improving productivity and helping companies reach their goals.
Imagine a data lake with large amounts of information but no sense of organization. A viable data lake solution must incorporate generic organizational methods and search capabilities, which provide the most value for its users. Other features might include key-value storage, tagging, metadata, or tools to classify and collect subsets of information.
Security and access control are two must-have features with any digital tool. The current cybersecurity landscape is expanding, making it easier for threat actors to exploit a company’s data and cause irreparable damage. Only certain users should have access to a data lake, and the solution must have strong security to protect sensitive information.
More organizations are growing larger and operating at a much faster rate. Data lake solutions must be flexible and scalable to meet the ever-changing needs of modern businesses working with information.
Also read: Unlocking analytics with data lake and graph analysis
Some data lake solutions are best suited for businesses in certain industries. In contrast, others may work well for a company of a particular size or with a specific number of employees or customers. This can make choosing a potential data lake solution vendor challenging.
Companies considering investing in a data lake solution this year should check out some of the vendors below.
The AWS Cloud provides many essential tools and services that allow companies to build a data lake that meets their needs. The AWS data lake solution is widely used, cost-effective and user-friendly. It leverages the security, durability, flexibility and scalability that Amazon S3 object storage offers to its users.
The data lake also features Amazon DynamoDB to handle and manage metadata. AWS data lake offers an intuitive, web-based console user interface (UI) to manage the data lake easily. It also forms data lake policies, removes or adds data packages, creates manifests of datasets for analytics purposes, and features search data packages.
Cloudera is another top data lake vendor that will create and maintain safe, secure storage for all data types. Some of Cloudera SDX’s Data Lake Service capabilities include:
Other benefits of Cloudera’s data lake include product support, downloads, community and documentation. GSK and Toyota leveraged Cloudera’s data lake to garner critical business intelligence (BI) insights and manage data analytics processes.
Databricks is another viable vendor, and it also offers a handful of data lake alternatives. The Databricks Lakehouse Platform combines the best elements of data lakes and warehouses to provide reliability, governance, security and performance.
Databricks’ platform helps break down silos that normally separate and complicate data, which frustrates data scientists, ML engineers and other IT professionals. Aside from the platform, Databricks also offers its Delta Lake solution, an open-format storage layer that can Excellerate data lake management processes.
Domo is a cloud-based software company that can provide big data solutions to all companies. Users have the freedom to choose a cloud architecture that works for their business. Domo is an open platform that can augment existing data lakes, whether it’s in the cloud or on-premise. Users can use combined cloud options, including:
Domo offers advanced security features, such as BYOK (bring your own key) encryption, control data access and governance capabilities. Well-known corporations such as Nestle, DHL, Cisco and Comcast leverage the Domo Cloud to better manage their needs.
Google is another big tech player offering customers data lake solutions. Companies can use Google Cloud’s data lake to analyze any data securely and cost-effectively. It can handle large volumes of information and IT professionals’ various processing tasks. Companies that don’t want to rebuild their on-premise data lakes in the cloud can easily lift and shift their information to Google Cloud.
Some key features of Google’s data lakes include Apache Spark and Hadoop migration, which are fully managed services, integrated data science and analytics, and cost management tools. Major companies like Twitter, Vodafone, Pandora and Metro have benefited from Google Cloud’s data lakes.
Hewlett Packard Enterprise (HPE) is another data lake solution vendor that can help businesses harness the power of their big data. HPE’s solution is called GreenLake — it offers organizations a truly scalable, cloud-based solution that simplifies their Hadoop experiences.
HPE GreenLake is an end-to-end solution that includes software, hardware and HPE Pointnext Services. These services can help businesses overcome IT challenges and spend more time on meaningful tasks.
Business technology leader IBM also offers data lake solutions for companies. IBM is well-known for its cloud computing and data analytics solutions. It’s a great choice if an operation is looking for a suitable data lake solution. IBM’s cloud-based approach operates on three key principles: embedded governance, automated integration and virtualization.
These are some data lake solutions from IBM:
With so many data lakes available, there’s surely one to fit a company’s unique needs. Financial services, healthcare and communications businesses often use IBM data lakes for various purposes.
Microsoft offers its Azure Data Lake solution, which features easy storage methods, processing, and analytics using various languages and platforms. Azure Data Lake also works with a company’s existing IT investments and infrastructure to make IT management seamless.
The Azure Data Lake solution is affordable, comprehensive, secure and supported by Microsoft. Companies benefit from 24/7 support and expertise to help them overcome any big data challenges they may face. Microsoft is a leader in business analytics and tech solutions, making it a popular choice for many organizations.
Companies can use Oracle’s Big Data Service to build data lakes to manage the influx of information needed to power their business decisions. The Big Data Service is automated and will provide users with an affordable and comprehensive Hadoop data lake platform based on Cloudera Enterprise.
This solution can be used as a data lake or an ML platform. Another important feature of Oracle is it is one of the best open-source data lakes available. It also comes with Oracle-based tools to add even more value. Oracle’s Big Data Service is scalable, flexible, secure and will meet data storage requirements at a low cost.
Snowflake’s data lake solution is secure, reliable and accessible and helps businesses break down silos to Excellerate their strategies. The top features of Snowflake’s data lake include a central platform for all information, fast querying and secure collaboration.
Siemens and Devon Energy are two companies that provide testimonials regarding Snowflake’s data lake solutions and offer positive feedback. Another benefit of Snowflake is its extensive partner ecosystem, including AWS, Microsoft Azure, Accenture, Deloitte and Google Cloud.
Companies that spend extra time researching which vendors will offer the best enterprise data lake solutions for them can manage their information better. Rather than choose any vendor, it’s best to consider all options available and determine which solutions will meet the specific needs of an organization.
Every business uses information, some more than others. However, the world is becoming highly data-driven — therefore, leveraging the right data solutions will only grow more important in the coming years. This list will help companies decide which data lake solution vendor is right for their operations.
Read next: Get the most value from your data with data lakehouse architecture
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IBM is a leading U.S.-based provider of enterprise IT hardware, software and services. In November 2021, IBM spun off the managed infrastructure assets of its former Global Technology Services business into Kyndryl (NYSE: KD). To align with its platform-centric approach, IBM has revised its segment reporting into four major categories: Consulting, Software, Infrastructure, and Global Financing.
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‘Given its ability to boost innovation, productivity, resilience, and help organizations scale, IT has become a high priority in a company’s budget. As such, there is every reason to believe technology spending in the B2B space will continue to surpass GDP growth,’ says IBM CEO Arvind Krishna.
A strengthening IT environment that is playing into IBM AI and hybrid cloud capabilities means a rosy future for IBM and its B2B business, CEO Arvind Krishna told investors Monday.
Krishna, in his prepared remarks for IBM’s second fiscal quarter 2022 financial analyst conference call, said that technology serves as a fundamental source of competitive advantage for businesses.
“It serves as both a deflationary force and a force multiplier, and is especially critical as clients face challenges on multiple fronts from supply chain bottlenecks to demographic shifts,” he said. “Given its ability to boost innovation, productivity, resilience, and help organizations scale, IT has become a high priority in a company’s budget. As such, there is every reason to believe technology spending in the B2B space will continue to surpass GDP growth.”
[Related: IBM STARTS ‘ORDERLY WIND-DOWN’ OF RUSSIA BUSINESS]
That plays well with IBM’s hybrid cloud and AI strategy where the company is investing in its offerings, technical talent, ecosystem, and go-to-market model, Krishna said.
“Demand for our solutions remains strong,” he said. “We continued to have double-digit performance in IBM Consulting, broad-based strength in software, and with the z16 [mainframe] platform launch, our infrastructure business had a good quarter. By integrating technology and expertise from IBM and our partners, our clients will continue to see our hybrid cloud and AI solutions as a crucial source of business opportunity and growth.”
Krishna said hybrid clouds are about offering clients a platform to straddle multiple public clouds, private clouds, on-premises infrastructures, and the edge, which is where Red Hat, which IBM acquired in 2019, comes into play, Krishna said.
“Our software has been optimized to run on that platform, and includes advanced data and AI, automation, and the security capabilities our clients need,” he said. “Our global team of consultants offers deep business expertise and co-creates with clients to accelerate their digital transformation journeys. Our infrastructure allows clients to take full advantage of an extended hybrid cloud environment.”
As a result, IBM now has over 4,000 hybrid cloud platform clients, with over 250 new clients added during the second fiscal quarter, Krishna said.
“Those who adopt our platform tend to consume more of our solutions across software, consulting, and infrastructure, [and] expanding our footprint within those clients,” he said.
IBM is also benefitting from the steady adoption by businesses of artificial intelligence technologies as those businesses try to process the enormous amount of data generated from hybrid cloud environments all the way to the edge, Krishna said. An IBM study released during the second fiscal quarter found that 35 percent of companies are now using some form of AI with automation in their business to address demographic shifts and move their employees to higher value work, he said.
“This is one of the many reasons we are investing heavily in both AI and automation,” he said. “These investments are paying off.”
IBM is also moving to develop leadership in quantum computing, Krishna said. The company currently has a 127-qubit quantum computer it its cloud, and is committed to demonstrate the first 400-plus-qubit system before year-end as part of its path to deliver a 1,000-plus-qubit system next year and a 4,000-plus-qubit system in 2025, he said.
“One of the implications of quantum computing will be the need to change how information is encrypted,” he said. “We are proud that technology developed by IBM and our collaborators has been selected by NIST (National Institute of Standards and Technology) as the basis of the next generation of quantum-safe encryption protocols.”
IBM during the quarter also move forward in its mainframe technology with the release of its new z16 mainframe, Krishna said.
“The z16 is designed for cloud-native development, cybersecurity resilience, [and] quantum-safe encryption, and includes an on-chip AI accelerator, which allows clients to reduce fraud within real-time transactions,” he said.
IBM also made two acquisitions during the quarter related to cybersecurity, Krishna said. The first was Randori, an attack surface management and offensive cybersecurity provider. That acquisition built on IBM’s November acquisition of ReaQta, an endpoint security firm, he said.
While analysts during the question and answer part of Monday’s financial analyst conference call did not ask about the news that IBM has brought in Matt Hicks as the new CEO of Red Hat, they did seem concerned about how the 17-percent growth in Red Had revenue over last year missed expectations.
When asked about Red Hat revenue, Krishna said IBM feels very good about the Red Hat business and expect continued strong demand.
“That said, we had said late last year that we expect growth in Red Hat to be in the upper teens,” he said. “That expectation is what we are going to continue with. … Deferred revenue accounts for the bulk of what has been the difference in the growth rates coming down from last year to this year.”
IBM CFO James Kavanaugh followed by saying that while IBM saw 17 percent growth overall for Red Hat, the company took market share with its core REL (Red Hat Enterprise Linux) and in its Red Hat OpenShift hybrid cloud platform foundation. Red Hat OpenShift revenue is now four-and-a-half times the revenue before IBM acquired Red Hat, and Red Hat OpenShift bookings were up over 50 percent, Kavanaugh said.
“So we feel pretty good about our Red Hat portfolio overall. … Remember, we‘re three years into this acquisition right now,” he said. “And we couldn’t be more pleased as we move forward.”
When asked about the potential impact from an economic downturn, Krishna said IBM’s pipelines remain healthy and consistent with what the company saw in the first half of fiscal 2022, making him more optimistic than many of his peers.
“In an inflationary environment, when clients take our technology, deploy it, leverage our consulting, it acts as a counterbalance to all of the inflation and all of the labor demographics that people are facing all over the globe,” he said.
Krishna also said IBM’s consulting business is less likely than most vendors’ business to be impacted by the economic cycle as it involves a lot of work around deploying the kinds of applications critical to clients’ need to optimize their costs. Furthermore, he said. Because consulting is very labor-intensive, it is easy to hire or let go tens of thousands of employees as needed, he said.
For its second fiscal quarter 2022, which ended June 30, IBM reported total revenue of $15.5 billion, up about 9 percent from the $14.2 billion the company reported for its second fiscal quarter 2021.
This includes software revenue of $6.2 billion, up from $5.9 billion; consulting revenue of $4.8 billion, up from $4.4 billion; infrastructure revenue of $4.2 billion, up from $3.6 billion; financing revenue of $146 million, down from $209 million; and other revenue of $180 million, down from $277 million.
On the software side, IBM reported annual recurring revenue of $12.9 billion, which was up 8 percent over last year. Software revenue from its Red Hat business was up 17 percent over last year, while automation software was up 8 percent, data and AI software up 4 percent, and security software up 5 percent.
On the consulting side, technology consulting revenue was up 23 percent over last year, applications operations up 17 percent, and business transformation up 16 percent.
Infrastructure revenue growth was driven by hybrid infrastructure sales, which rose 7 percent over last year, and infrastructure support, which grew 5 percent. Hybrid infrastructure revenue saw a significant boost from zSystems mainframe sales, which rose 77 percent over last year.
IBM also reported revenue of $8.1 billion from sales to the Americas, up 15 percent over last year; sales to Europe, Middle East, and Africa of $4.5 billion, up 17 percent; and $2.9 billion to the Asia Pacific area, up 16 percent.
Sales to Kyndryl, which late last year was spun out of IBM, accounted for about 5 percent of revenue, including 3 percent of IBM’s Americas revenue.
IBM also reported net income for the quarter on a GAAP basis of $1.39 billion, or $1.53 per share, up from last year’s $1.33 billion, or $1.47 per share.
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ТАMPA, Fla., July 13, 2022 (GLOBE NEWSWIRE) -- MANTA , the data lineage platform, today announced it is working with IBM to drive data-driven success for enterprise-level customers. MANTA's data lineage platform is now available with IBM Cloud Pak for Data to provide businesses with historical, indirect and technical data lineage capabilities.
Data is among an organization's most critical assets, yet the volume and complexity of today's data ecosystems are rife with blind spots that result in slower data delivery, increased number of incidents and unreliable business insights. Having a clear and comprehensive view of all data flows is critical for organizations to help ensure they are maximizing the value of their data governance frameworks and reinforcing overall data management strategies.
MANTA's automated data lineage platform is designed to provide a line of sight into data environments by building a powerful map of all data flows, sources, transformations and dependencies to help Excellerate data governance, streamline migration projects and accelerate incident resolution.
Through this new agreement with IBM, MANTA Automated Data Lineage for IBM Cloud Pak for Data is now available to clients who are using IBM's data fabric solution for data governance and privacy . This enables clients to add MANTA's capabilities for historical, indirect, and technical data lineage to Watson Knowledge Catalog in IBM Cloud Pak for Data to help them perform effective impact and root cause analyses, meet common regulatory compliance standards, and gain deeper insights into data quality issues.
“By integrating with IBM Cloud Pak for Data through Watson Knowledge Catalog, this ensures that customers have the tools needed to make informed, data-driven decisions that drive their business forward,” said Petr Stipek, vice president of partnerships at MANTA.“This integration enables customers to harness the power of their data to adapt quickly to changing needs, address challenges as they occur and capture new opportunities as businesses evolve.”
“Businesses rely on data and AI, but many struggle with data silos that make it difficult to ensure their teams have access to high-quality data without jeopardizing governance and privacy. That's why clients are turning to IBM to help them adopt a data fabric architecture designed so they can get the right data in the right hands at the right time, regardless of where it resides,” said Michael Gilfix, vice president of product management for data and AI, IBM.“The launch of MANTA Automated Data Lineage on Cloud Pak for Data is the latest example of how IBM is delivering new data fabric capabilities so businesses can build a trusted, business-ready data foundation.”
Click here to learn more about MANTA Automated Data Lineage for IBM Cloud Pak for Data.
MANTA is a world-class data lineage platform that helps fix your blind spots and offers a line of sight into your data environment. By automatically scanning your data environment, MANTA builds a powerful map of all data flows and delivers it through a native UI and other channels to both technical and non-technical users. With MANTA, everyone gets full visibility and control of their data pipeline. Visit getmanta.com to learn how MANTA can help your company leverage data as a true corporate asset.
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