Category Archives: Cloud Computing
SAP admits attempt to adapt on-prem security for its cloud flopped – The Register
SAP has revealed that its attempts to create an Endpoint Detection and Response (EDR) tool for its cloud "was abandoned after a year and a half as a failure."
That admission came in a Wednesday post penned by Jay Thoden van Velzen a strategic advisor to SAP chief security officer Sebastian Lange.
Thoden van Velzen's post is titled "Don't Lift & Shift Legacy: Securing Public Cloud Requires Cloud-Friendly Security Tooling" and explains SAP's own cloud migration efforts.
The theme of his post is that security tools and practices developed for applications written to run on-prem probably won't apply to the cloud.
"Legacy security tooling lifted & shifted from datacenters may still provide value higher up the stack," he wrote, adding "But without monitoring and detection that is cloud-aware you leave yourself vulnerable to common cloud threats that legacy tooling cannot see."
For example, he points out that corporate datacenters run stable large open networks that need threat monitoring, and that sort of tool is often agent-based. In public clouds, by contrast, networks mostly carry encrypted API calls, while VMs, containers, and the networks that connect them may not operate for long. Even if attackers get in, they can struggle to gain persistent access.
Attackers that do get in may try to create new VMs to do things like mine crypto. Those VMs will not use your templates and will not therefore run your security agents. Thus, you'll struggle to see them.
Developers are another factor that erodes the effectiveness of on-prem infosec regimes.
"Developers have more autonomy than ever in the cloud and can deploy resources at will," Thoden van Velzen observed. "Therefore, you need the active collaboration of those teams to install an agent on each of their end points." But developers expect friction-free access to resources so asking them to test and deploy agents won't be well received,
He therefore recommends a cloud-native approach to implementing security mostly using APIs, and done at an organizational level.
"That way onboarding can be done centrally and applied to all cloud accounts in the organization without any effort on the developer teams," he suggested.
SAP learned that the hard way.
"Our Cloud-native Application Protection Platform (CNAPP) was deployed and rolled out to most of the organization in about three months. Our first central agent-based EDR solution adoption was abandoned after a year and a half as a failure," he admitted.
Thoden van Velzen also worries about the complexities involved when using security tools designed for on-prem use in the cloud. He also observed that security software is licensed for on-prem use. "Many vendors use per-seat licensing," he noted, before asking "how do you calculate a seat when it only was around for a few hours?"
SAP, he wrote, creates "30,000 VMs every 24 hours. Do all 30,000 count as a seat? Do we average the number of VMs over a time period? This is not always clear."
The ERP emperor now runs an agent-less Cloud Native Application Protection Platform (CNAPP) that Thoden van Velzen wrote "monitors cloud-native infrastructure and managed services, as well as VMs and container-based workloads through side scanning.
"It contextualizes both findings into risk-based alerts for misconfigurations, vulnerabilities, IAM alerts and file-based malware that facilitate prioritization within the organization. The CNAPP even supports asset discovery, important in a fast-growing, dynamic environment."
SAP is so confident it's performing that in October 2023 the CNAPP tool replaced an in-house developed cloud security posture management solution, "and in early 2024 [it] will replace the existing network-based vulnerability scanner entirely for public cloud landscapes."
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SAP admits attempt to adapt on-prem security for its cloud flopped - The Register
Equinix highlight the most significant conversations shaping the world of cloud computing in 2023 Intelligent CIO … – Intelligent CIO
A look at the latest changes and opportunities arising in the world of cloud computing.
In 2023, cloud computing continued to evolve to keep up with the changing priorities of customers. All this change has created additional complexityand new terminology to go along with it. To help keep track of everything, Equinix takes a look back at some of the biggest cloud topics they covered this year.
1. The next step in the evolution of private cloud
As customers looked to leverage the full power of cloud while avoiding high costs and vendor lock-in, many of them turned to private cloud. Dedicated cloud is the next step in the evolution of private cloud: Just like traditional private cloud, it includes single-tenant compute, storage or analytics infrastructure deployed outside a traditional on-premises environment. The difference is that dedicated cloud pairs this single-tenant infrastructure with multicloud access on demand.
2. Supercloud
Hybrid multicloud is a simple idea that has proven to be surprisingly difficult to execute. You could even argue that true hybrid multicloudwhere applications distribute themselves across clouds automatically to achieve the best possible balance of performance, costs and reliabilityisnt even possible today. Supercloud could be the next development that helps make it possible. Supercloud would use a neutral, interconnected staging ground to enable quick and flexible movement of data and workloads among different clouds.
3. Expansion of cloud hyperscalers
Major cloud hyperscalers like Amazon Web Services (AWS), Microsoft Azure and Google Cloud have traditionally focused on operating large compute and storage facilities in core metros. However, their enterprise customers are increasingly looking for infrastructure in edge locations, so hyperscalers are expanding to those locations to meet the demand. To do this, theyre taking a two-pronged approach: building their own private facilities and acquiring space in colocation data centers.
4. Bare metal emerges as a public cloud alternative
In the early days of cloud computing, many businesses took a simplistic lift-and-shift approach to migrating their workloads to cloud. Since these businesses werent migrating workloads based on a holistic business strategy, they frequently ended up with a cloud environment that didnt meet the unique requirements of their different workloads. As a result, its no surprise that many businesses are considering post-cloud deployment (also known as cloud repatriation) to move away from public cloud environments that havent lived up to expectations. Theyre often moving toward hybrid cloud environments that incorporate Bare Metal as a Service (BMaaS) compute and storage. BMaaS can offer a cloud-like experience while also helping you avoid cloud complexity and high costs.
5. Cloud adjacent data storage helps effectively balance cloud priorities
So many of the problems that commonly arise around public cloudthe high egress fees, vendor lock-in and loss of control over datacan be avoided by placing data near the cloud, but not in the cloud. Enterprises can achieve this by building a cloud-adjacent data architecture centered around a core data storage environment with private network connectivity to multiple cloud and edge environments. This allows data and workloads to flow wherever theyre needed most, without cost and complexity standing in the way.
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Equinix highlight the most significant conversations shaping the world of cloud computing in 2023 Intelligent CIO ... - Intelligent CIO
Cloud Computing Challenges and Opportunities Drive Business Strategy in 2024 – PR Web
The cloud offers critical benefits, from driving innovation to providing real-time access to data. But it also introduces risk. Proactive businesses carefully evaluate cloud computing challenges and opportunities, tailoring their approach to align with business needs.
"The cloud offers critical benefits, from driving innovation to providing real-time access to data," stated Jennifer Mazzanti, CEO, eMazzanti Technologies. "But it also introduces risk. Proactive businesses carefully evaluate cloud computing challenges and opportunities, tailoring their approach to align with business needs."
Below are a few excerpts from the article, "Cloud Computing Challenges and Opportunities Drive Business Strategy in 2024."
Security and Compliance
"Multi-cloud environments add complexity, and cloud services generally entail passing data to a third party service provider. At the same time, privacy regulations, particularly in highly-regulated industries, impose strict controls. Organizations must update their security and compliance strategies accordingly, as traditional approaches will no longer prove effective."
Multi-Cloud and Hybrid Cloud Strategies Bring Both Benefits and Risks
"Multi-cloud and hybrid cloud solutions provide several key benefits, including cost reductions, reduced risk, and increased flexibility. However, they also add complexity to information governance, as data resides in multiple locations, with multiple service providers. This situation can lead to data silos and compliance issues."
Empowering Innovation
"Cloud computing opens the door for transformative technologies and exciting innovations by making emerging technologies accessible at scale. For instance, with the cloud, businesses can access AI, machine learning, and big data analytics without having to make substantial infrastructure investments. This allows even small businesses to gain a competitive edge."
Ability to Leverage Real-time Data
"The cloud delivers up-to-the-minute information. This allows businesses to react quickly to changes in the market. It also enables manufacturers to monitor any changes in complex factory equipment in real time, streamlining maintenance and reducing downtime."
Strategic Cloud Computing Experts
Harnessing the powerful benefits of cloud computing while mitigating the risks imposed by increased complexity and evolving security threats requires a balanced approach. Businesses will need to implement security and information governance best practices. With a full range of cloud services, the cloud computing experts at eMazzanti can help.
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Cyber Security Risk Factors to Address in 2024 - eMazzanti Technologies
Microsoft Copilot Delivers Powerful Creativity and Productivity - eMazzanti Technologies
About eMazzanti Technologies
eMazzanti's team of trained, certified IT experts rapidly deliver increased revenue growth, data security and productivity for clients ranging from law firms to high-end global retailers, expertly providing advanced business cyber security, retail and payment technology, digital marketing services, AI, cloud and mobile solutions, multi-site implementations, 247 outsourced network management, remote monitoring, and support.
eMazzanti's consistent growth landed them on the Inc. 5000 list 9X. Recognized as a 4X Microsoft Partner of the Year, the #1 ranked NYC area MSP, NJ Business of the Year, and 5X WatchGuard Partner of the Year, the company excels as a trusted outsourced IT partner! Contact: 1-866-362-9926, [emailprotected] or http://www.emazzanti.net Twitter: @emazzanti Facebook: Facebook.com/emazzantitechnologies.
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Cloud Computing Challenges and Opportunities Drive Business Strategy in 2024 - PR Web
Cloud threat detection and response priorities for 2024 – TechTarget
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Published: 13 Dec 2023
Cloud proliferation grew precipitously in 2023 and will continue to do so in 2024. This growth has led to several security difficulties, such as increased change velocity making it hard to keep up with security requirements, an increasingly complex attack surface and more vulnerabilities to patch or remediate.
As we move into next year, TechTarget's Enterprise Strategy Group (ESG) analysts expect a lot of activity as organizations attempt to bridge the cloud security gap. ESG research found a vast majority (89%) of organizations said they plan to increase cloud threat detection and response (CDR) spending in 2024, with more than one-third (36%) of firms claiming their cloud security budgets will grow substantially.
When asked to identify which aspects of CDR need improvement moving forward, survey respondents tended to focus on aligning security with cloud-native applications and software development. The following were the top five areas indicated for improvement:
This research indicated security professionals are focused on the right places. Lacking traditional security staples, such as servers and IP addresses, cloud security depends on much greater understanding and oversight of cloud security applications while keeping up with the pace and processes of cloud-native development.
There's a lot of work ahead, but security pros seem intent on shifting left while improving the effectiveness of everything right of boom -- threat detection and response. That's a good mindset for cloud security in 2024.
Jon Oltsik is a distinguished analyst, fellow and the founder of TechTarget's Enterprise Strategy Group cybersecurity service. With more than 30 years of technology industry experience, Oltsik is widely recognized as an expert in all aspects of cybersecurity.
Enterprise Strategy Group is a division of TechTarget. Its analysts have business relationships with technology vendors.
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Cloud threat detection and response priorities for 2024 - TechTarget
Companies arent ready to succeed with AI – InfoWorld
How ready are we to harness AI, be it in the cloud or elsewhere? Pluralsight, the technology workforce development company, has released new research on the topic, the Pluralsight AI Skills Report: The Gap Between AI Investments and Worker Readiness, where we can find some answers.
Full disclosure: I have many personal friends at Pluralsight, but that did not drive me to write this post, and they were not informed I was doing so. I dont work for or with Pluralsight, in case you are wondering.
The research covers the AI landscape and its impact on talent based on a survey of 1,200 decision-makers and practitioners in technology, IT, cloud, cybersecurity, and related fields.
Pluralsight found a gap between the pace of AI investments occurring now and the readiness of the workforce to implement and use AI. According to the study, 90% of executives admit to not completely understanding their teams AI skills and proficiencies. This means they have not done a skills gap analysis. That translates into a fundamental disconnect between organizational AI strategies and the skill sets in-house.
Companies need to start prioritizing a few things:
Pluralsight is not as pessimistic as I am. I predict that failure will likely occur, including growing technical debt when enterprises are bathing in technical debt already. Too many organizations are hiring so-called AI experts who make a good number of poor decisions. By the time companies discover this, its too late.
We saw something similar happen with initial cloud efforts. However, AI issues will come quicker and be 10 times as harmful to the business. Again, as I stated in my 2024 predictions, we need to focus on fixing this, and we need to do so through innovative approaches and an understanding of the talent supply chain.
Of course, some overlook this as just another challenge that can be overcome. Perhaps. The core difference is that were not implementing a technology transformation that will save the business 20% in operational costs and shift from capex to opex. Generative AI systems could make or break many businesses, and getting this right the first time is imperative.
The Pluralsight report outlines the broader implications for organizational success with AI and other digital transformation technologies. Failure to close the AI skills gap could impede companies ability to achieve returns on their AI investments and lose the opportunity to capitalize on the competitive advantages offered by AI-driven innovations.
This could kill your business. Thats bad.
This is not one of those things you wait for the market to fix. Many hiring managers are sitting with their arms folded, complaining about how bad the colleges and universities are at turning out graduates with AI skills. They might as well give up now. Educational institutions move far too slowly and arent the best way of learning these days.
Its up to you to fix the talent supply chain. Work with existing employees to find out who is willing and able to become an AI expert. Figure out what courses and on-the-job training they will need. This does not mean sending people back to college, but providing innovative and dynamic training that is laser-focused on the what, whys, and how of AI and the cloudespecially the how, which is largely missing today.
I dont want people who can explain generative AI to me. I want someone who understands how it can be applied to the specific business to ensure its ultimate success. Not much to ask for.
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Companies arent ready to succeed with AI - InfoWorld
Controversial AI image platform Civitai dropped by its cloud computing provider after reports of possible CSAM – Engadget
OctoML says it has ended its business relationship with Civitai days after an investigation by 404 Media revealed the text-to-image platform was being used to generate images that could be categorized as child pornography. Civitai previously relied on OctoMLs OctoAI for image generation. While OctoML initially indicated it would continue working with Civitai and introduced new measures to curb the creation of harmful images, 404 Media reported on Saturday that it has now decided to cut ties with the platform altogether.
According to 404 Medias December 5 report, internal communications showed that OctoML was aware some Civitai users were creating sexually explicit material that included nonconsensual images of real peopleand pornographic depictions of children. In a followup report this weekend, the publication noted that OctoML rolled out a filter to block the generation of all NSFW content on Civitai before announcing its decision to pull out. Civitai also added new moderation methods in response to the investigation earlier this week, including a mandatory embedding called Civitai Safe Helper (Minor) that bars the model from generating images of children if a mature theme or keyword is detected, according to 404.
Andreessen Horowitz-backed Civitai has previously come under scrutiny for its bounties feature that challenges users to generate realistic images of real people for rewards. In November, 404 Media found it was being used to make nonconsensual deepfakes of celebrities, influencers and even a private citizen that were, in many cases, sexual in nature. The subjects were primarily women. According to 404 Media, Civitai has since added a filter to prevent the creation of NSFW content featuring certain celebrities.
Nevertheless, OctoML which uses Amazon Web Services servers no longer wants to be involved. In a statement to 404 Media on Saturday, OctoML said, We have decided to terminate our business relationship with Civitai. This decision aligns with our commitment to ensuring the safe and responsible use of AI.
Amazon Cloud Optimization Was a Key Topic at AWS Re:Invent 2023 – Business Insider
Depending on whom you ask, corporate cost cutting on cloud computing is either a waning symptom of pandemic-era overspending or the hottest trend hitting IT departments in 2024.
Either way, one thing is certain: Companies are getting serious about cloud spend.
Cost savings and "optimization" getting the most value out of what you're already spending on cloud services were consistent, overlapping themes at the Amazon Web Services re:Invent conference, Amazon's annual cloud conference, which took place from November 27 to December 1 in Las Vegas.
In his keynote address, Adam Selipsky, the CEO of AWS, mentioned cost savings multiple times, pointing to new products, including the Graviton4 chip and EC2 UltraClusters server resources, as opportunities to save money. Werner Vogels, the chief technology officer of AWS, named his keynote address "The Frugal Architect" after a set of guidelines he created to help developers prioritize cost savings.
AWS, the world's biggest cloud provider, saw growth rates slow to a historical low this year, which the company has blamed on customers scrutinizing their cloud budgets amid concerns over a weakening economy. And while Wall Street analysts hope the excitement over generative AI will drive customers to spend more money on cloud services next year, it's clear that optimization won't go away.
Microsoft and Google also saw slowed growth rates in cloud sales.
"There's a clear trend for organizations to be more discerning and careful about their spend on cloud," Sid Nag, the vice president and analyst in the technology and service-provider group at the research and consulting firm Gartner, said.
Nag said he thought the "cost-cutting narrative" of the past year was "a bit overblown" but did exist.
"I'm not seeing any wholesale shutdown of projects as an outcome of any sort of cost-cutting sentiment, but I should say in the same breath that CIOs are being very careful on where they spend their dollars," Nag said.
At the beginning of the coronavirus pandemic, companies rushed to spend on cloud-computing storage and services as they transitioned to remote work. Leaders hastily made decisions, and now almost four years later companies are still reckoning with the financial consequences.
"Everybody got the bill from their cloud providers from all the massive, random movements into the cloud during the pandemic, and it was about 2 times what they thought it was going to be, and in many instances, the board of directors wasn't aware of it," Dave Linthicum, the chief cloud-strategy officer at Deloitte, said. "So now they're tasked with optimizing, and that's what you're seeing with all the FinOps and cloud-governance stuff."
The FinOps Foundation is a nonprofit organization promoting a series of "best practices" for cloud spending. In October, AWS became a member, the last of the three big cloud providers with Google and Microsoft being founding members to join the foundation.
Some AWS customers saw this as a sign that the cloud giant would take customer concerns about cost cutting more seriously.
A decade ago, when companies began to move to the cloud, budget wasn't a big concern, said J.R. Storment, the founder and executive director of the FinOps Foundation. He added that that had changed in the past few years with more companies having moved more data to the cloud.
"Cloud spend got big enough at most of the Fortune 500s that it's actually material now," Storment said. "The numbers are hitting the CFOs."
To save money on cloud services, customers often must first spend money.
The Venetian Convention & Expo Center, where re:Invent took place, was packed with cloud-optimization companies, including Zesty and DoiT, hawking cost-cutting services.
Craig Lowell, the product-marketing manager at DoiT, said most of his conversations at re:Invent revolved around cost allocation.
"It's about figuring out who's spending what and getting engineering and development teams to take ownership of their own costs and have kind of a wider understanding about how their costs affect the rest of the business," Lowell said.
Even though "generative AI is the new sexy thing that everyone is exploring," the technology didn't come up in many conversations about budget, Lowell said.
That could be because companies are still figuring out what they're going to do with generative AI let alone how much to spend on it.
Companies must consider many factors before deciding how much to spend on generative AI, Nag said, including issues around data privacy and access to GPUs.
"We're in a watch-and-wait period," Nag said.
Linthicum agreed, adding that he expected many companies to readjust budgets in 2024.
"Generative AI is going to take the news cycles, but the real work is in optimization," Linthicum said. "Or, in other words normalizing technical debt and the ability to kind of get these cloud workloads in some state where they're not going to eat us alive."
Meanwhile, cloud growth has bottomed, Bernstein analysts said this week in a quarterly cloud research note.
"The real question is: How fast will it accelerate?" Mark Schilsky, a Bernstein analyst, wrote in his newsletter last week.
Do you have information or insight to share about AWS or other large cloud providers? Contact Ellen Thomas at ethomas@insider.com or on the encrypted messaging app Signal at +1 (646) 847-9416. Reach out using a nonwork device.
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Amazon Cloud Optimization Was a Key Topic at AWS Re:Invent 2023 - Business Insider
Generative AI is off to a rough start – InfoWorld
Its been a rough month for generative AI (genAI). First, AWS launched Amazon Q, its answer to Microsofts Copilot, only to have its own employees warnof severe hallucinationsand data leaks. Then Google launched Gemini, its answer to ChatGPT, to much fanfare and an incredible demo, only to acknowledge after the factthat the demo was fake. Oh, andMeta releasednew open source tools for AI safety(hurray!) yet somehow failed to acknowledge the most egregiously unsafe aspect of genAI tools: their susceptibility to prompt injection attacks.
I could go on, but what would be the point? These and other failures dont suggest that genAI is vacuous or a hype-plagued dumpster fire. Theyre signs that we as an industry have allowed the promise of AI to overshadow current reality. That reality is pretty darn good. We dont need to keep overselling it.
What we might need, despite its imperfect fit for genAI, is open source.
I recently wrote that AWSs release of Amazon Q is a watershed moment for the company: an opportunity to close the gap or, in some cases, outpace competitors. Mission accomplished.
Almost. One big problem, among several others that Duckbill Chief Economist Corey Quinn highlights, is that although AWS felt compelled to position Q as significantly more secure than competitors like ChatGPT, its not. I dont know that its worse, but it doesnt help AWSs cause to position itself as better and then not actually be better. Quinn argues this comes from AWS going after the application space, an area in which it hasnt traditionally demonstrated strength:
As soon as AWS attempts to move up the stack into the application space, the wheels fall off in major ways. It requires a competency that AWS does not have and has not built up since its inception.
Perhaps. But even if we accept that as true, the larger issue is that theres so much pressure to deliver on the hype of AI that great companies like AWS may feel compelled to take shortcuts to get there (or to appear to get there).
The same seems to be true of Google. The company has spent years doing impressive work with AI yet still felt compelled to take shortcuts with a demo. As Parmy Olson captures, Googles video made it look like you could show different things to Gemini Ultra in real time and talk to it. You cant.Grady Booch says, That demo was incredibly edited to suggest that Gemini is far more capable than it is.
Why would these companies pretend their capabilities are greater than they actually are? The reasons arent hard to discern. The pressure to position oneself as the future of AI is tremendous. And its not just AWS and Google. Listen in on recent earnings calls for public companies; every executive cant seem to say AI enough. The AI gold rush is on, and everyone wants to stake their claim.
GenAI is still nascent in its capabilities. For all the breathless reporting of this or that new model and all that it offers, the reality always dramatically lags behind the hype. Instead of fixing GenAIs most pressing problemprompt injectionwere exacerbating the problem by inducing more enterprises to use fundamentally non-secure software.
We may need open source to help.
I dont mean that if we just open source everything, AI will magically be perfect. That hasnt happened for cloud or any other area of enterprise IT, so why would genAI be any different? Not to mention that as much as we like to throw around the term open source in the context of AI, its not even clear what we mean, as Ive written.
Its likely that the industry, as Meta has done with its Purple Llama initiative, will focus on comparatively unimportant challenges. Simon Willison laments, The lack of acknowledgment of the threat of prompt injection attacks in this new Purple Llama initiative from Meta AI Is baffling to me.
In addition, systems like Gemini are multifaceted and complex. There must be lots of engineering tricks and hard-coded rules, and we would never know how many models are inside the systems before open sourcing, notesProfessor Xin Eric Wang. This complexity means open sourcing a large language model or genAI system currently raises as many questions as it answers.
The Open Source Initiative (OSI) is grappling with these issues. OSI Executive Director Stefano Maffulli stresses: What does it mean for a developer to have access to a model, and what are the rights that should be exercis[ed], and what do you need in order to have the possibility to modify [and redistribute] that model?
Its all unclear.
What is clear is that the efforts to make open source relevant for genAI are incredibly important. We need more transparency and less black-box opacity. Microsoft, AWS, Google, and others will still feel compelled to position themselves as leaders, but open source separates fact from fiction. Code doesnt lie.
Lets rewind those Q, Copilot, and Gemini announcements, but imagine if instead of just private previews and demos, there was code. Think about how that would change the dynamic. Think about the humility it would compel. Given that by far the most common early adopters of genAI within the enterprise are developers,as an OReilly survey uncovered, companies should speak their language: code. Most developers never look at the code for an open source project, but making it available so some do is important. It earns trust in ways that overzealous announcements dont.
Open source isnt a perfect answer to the troubles genAI vendors are having. But the aspiration to greater transparency, which open source fosters, is desperately needed.
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Generative AI is off to a rough start - InfoWorld
World Bank names UAE to lead cloud computing working group – ZAWYA
The UAE has been appointed to chair the World Banks Cloud Computing Working Group, in recognition of the countrys digital transformation efforts.
Dr. Bushra AlBlooshi, Senior Consultant Research and Innovation at Dubai Electronic Security Centre (DESC), an affiliate of Digital Dubai, led the working groups meeting on November 28, according to a statement issued by Dubai Media Office late Thursday.
Previously co-lead by Singapore and the United Kingdom, the working group brings together 27 countries, international groups and top companies with an aim to advance global standards and practices in cloud computing.
According to Hamad Obaid Al Mansoori, Director General of Digital Dubai, the UAEs selection to lead the World Bank body reflects the exceptional reputation of the country in the fields of new technology and cloud computing.
Al Mansoori noted that cloud computing is a key pillar of smart cities and digitalised knowledge societies.
The UAEs appointment to chair the [working group] demonstrates the leading position that the country has come to occupy in the field of future technologies in general, and cloud computing in particular, AlBlooshi said.
The UAE has succeeded in asserting its presence on the world stage as a technological innovation hub, an inspiring model for digital transformation.
The World Banks working groups convene experts from stakeholders in the public and private sectors worldwide.
They co-develop knowledge products, which may include playbooks, how-to notes, surveys and benchmarks, according to the World Bank website.
(Writing by Cleofe Maceda; editing by Seban Scaria) seban.scaria@lseg.com
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World Bank names UAE to lead cloud computing working group - ZAWYA
Big Data Market worth $273.4 billion by 2026, growing at a CAGR of 11.0%: Report by MarketsandMarkets – Yahoo Finance
MarketsandMarkets Research Pvt. Ltd.
Chicago, Dec. 12, 2023 (GLOBE NEWSWIRE) -- The Big Data Market size is projected to grow from USD 162.6 billion in 2021 to 273.4 USD billion in 2026, at a Compound Annual Growth Rate (CAGR) of 11.0% during the forecast period, according to a new report by MarketsandMarkets. The Big Data industry is driven by sharp increase in data volume. However, rise in data connectivity through cloud computing and incorporation of digital transformation in top-level strategies.
Browse in-depth TOC on "Big Data Market"
354 - Tables68 - Figures426 - Pages
Big Data Market Dynamics:
Drivers:
Sharp increase in data volume
Rise in data connectivity through cloud computing
Incorporation of digital transformation in top-level strategies
Restraints:
Data security concerns and stringent data security regulations
High big data handling costs
Opportunities:
Rise in adoption of technologies and big data analytics
The growth of investment in IT sectors by the businesses
List of Key Players in Big Data Market:
IBM(US)
Google(US)
Oracle(US)
Microsoft(US)
SAS(US)
SAP(Germany)
Alteryx(US)
TIBCO(US)
Cloudera(US)
Teradata(US)
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According to SAS Institute, big data refers to the large volume of databoth structured and unstructuredthat inundates a business on a day-to-day basis. But it is not the amount of data that is important; it is what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. Big data solutions include big data analytics, data discovery, data visualization, and data management solutions. Various organizations are deploying big data solutions to harness the power of big data by managing it efficiently and analyzing it to get actionable insights. The massive growth of data and an increase in the number of mobile apps and Internet of Things (IoT) devices are the major factors driving the Big Data Market.
Story continues
The Big Data Market has been segmented by component into solutions and services. The services segment comprises professional services and managed services. Solution type is segmented into Solution Big Data Analytics, Data Discovery, Data Visualization, Data Management. The business function includes Finance, Marketing and Sales, Human Resources, Operations. The deployment type is segmented into cloud (public cloud, private cloud and hybrid cloud) and on-premises. Organization size is segmented into SMEs and large enterprises. Verticals in the report include BFSI, Government and Defense, Healthcare and Life Sciences, Manufacturing, Retail and Consumer Goods, Media and Entertainment, Telecommunications and IT, Transportation and Logistics, Other Verticals (real estate, energy and utilities, travel and hospitality, and education and research). The regional analysis of the Big Data Market covers North America, Europe, APAC, MEA and Latin America.
Among the component segment, the services segment in the Big Data Market is expected to witness the highest CAGR during the forecast period. The demand for professional services is seen to drive the market for Big Data solutions. Among deployment type, the cloud Big Data segment is estimated to grow with the highest CAGR during the forecast period. The increasing generation of data leads to various challenges for several organizations. These challenges include storage, privacy, and affordability.
Among solution, big data analytics segment to grow at a higher CAGR during the forecast period. The adoption of Big Data analytics among large enterprises is high as it provides an almost limitless source of business and informational knowledge, which can lead to operational improvements and new income prospects for businesses in practically any industry. The value hidden in company data has firms trying to develop a cutting-edge analytics operation for use cases like consumer personalization, risk reduction, fraud detection, internal operations analysis, and other new use cases arising on a near-daily basis.
Among the organization size, the large enterprises are projected to dominate the market, while the SMEs segment is projected to record a higher growth rate during the forecast period. The adoption of Big Data software and services among large enterprises is high due to the ever-increasing adoption of the cloud, and the trend is expected to continue during the forecast period. Large enterprises accumulate huge chunks of data that can be attributed to the widespread client base. In large enterprises, data plays a major role in evaluating the overall performance of organizations. Large enterprises are leveraging real-time data coming from various sources; for instance, social media feeds or sensors and cameras, each record needs to be processed in a way that preserves its relation to other data and sequence in time.
Based on vertical, the healthcare and life science segment is expected to grow at a higher CAGR during the forecast period, big Data are gaining acceptance among all verticals to improve profitability and reduce overall costs. The major verticals adopting Big Data software are BFSI, Government and Defense, Healthcare and Life Sciences, Manufacturing, Retail and Consumer Goods, Media and Entertainment, Telecommunications and IT, Transportation and Logistics, Other Verticals (real estate, energy and utilities, travel and hospitality, and education and research). Healthcare and life science, by vertical segment, is expected to grow at a higher CAGR during the forecast period.
The Big Data Market is studied across five major regions: North America, Europe, MEA, APAC, and Latin America. North America is estimated to account for the largest market share during the forecast period. In North America, big data analytics and data discovery solutions are considered highly effective by most organizations and verticals. On the other hand, Europe is gradually incorporating these advanced solutions within its enterprises. APAC is expected to grow at the highest CAGR.
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Big Data Market worth $273.4 billion by 2026, growing at a CAGR of 11.0%: Report by MarketsandMarkets - Yahoo Finance