“Our raison d’être has been to deliver a new type of on-premises infrastructure, which we call True Private Cloud,” he told me. “Our position has been that to be able to do that, you need to take care of both the hardware and the software stack, and that’s what we have in our product HyperCloud, which we designed from the ground up. We manufactured those motherboards in-house and assembled the final product in our facilities.”

Why Custom Motherboards and Hardware?

I was curious why, with the wide range of motherboards and hardware off the shelf, the company didn’t just go with that approach.

“Our view has been that you want to have control of the entire piece of hardware,” Van der Schyff said. “In reality, today you can’t get that if you buy something off the shelf. You’re dealing with many vendors; they don’t always play nicely with each other, and you end up with this compatibility matrix nightmare.”

Van der Schyff pointed to hyperscalers like AWS that have been building custom hardware for specific purposes for some time.

SoftIron’s VM Squared Offering

So, what does the SoftIron VM Squared solution look like?

SoftIron designed VM Squared as an alternative to VMware’s legacy complexity:

• Installation: The company says VM Squared can install in a half hour or less.
• User interface: The company says it streamlined the UI with no config settings more than a couple of clicks away.
• Reducing complexity: SoftIron says VM Squared automates provisioning and deploying so a company can scale more efficiently without adding management overhead.
• Path to private cloud: The company’s private cloud offering, HyperCloud, sits alongside VM Squared, and there’s a simple private cloud upgrade path.
• Migration from VMware: The company offers a migration tool to shift a VMware vSphere estate.

Running Private Cloud Features from VM Squared

A number of HyperCloud features can run within VM Squared, gaining access to a virtualized environment, including:

• Multitenancy that can be ready to go out of the box, with the simple addition of new tenants, MSP-ready security compliance, and the ability to work at the edge.
• Centralized, integrated cloud billing with a chargeback dashboard and role-based access control.
• Cloud scalability with automated provisioning and deployment, lower overhead, a simpler deployment, and node-add process, the ability to scale out, and elastic resource allocation.
• Cloud resiliency that comes with high availability built-in, a distributed control plane and storage, and the ability to move VMs between hosts without downtime.

The company also touted simpler licensing and its marketplace, which it says includes “click-and-go images ready from Day 1” with installs of Linux, Windows, and partner appliances.

Bottom Line: SoftIron’s Ambitions are Considerable

SoftIron has taken a novel approach. Sometimes, a novel approach is good. Sometimes, it’s just a new way that might become accepted somewhere down the road. I’m not sure where SoftIron is. The company is taking on a lot. Custom hardware is something left to the big guys, so SoftIron must think it can punch way above its weight if it’s intent on playing that game.

But I applaud their audacity here and think the concepts are sound. Given Broadcom is changing everything about how customers buy and operate vSphere, IT pros are looking for alternatives, making the timing right for SoftIron.

For a deeper understanding of the cloud computing market, read our guide: Top Cloud Companies

The post SoftIron To Simplify Virtualization With VM Squared appeared first on eWEEK.

A new study from Tangoe delves into IT expense management practices, comparing fully in-house programs, external third-party solutions, and hybrid models.

The study, conducted in partnership with Vanson Bourne, is based on responses from 500 senior IT and finance professionals in the U.S. and UK, who work for organizations with annual global revenues ranging from $500 million to $50 billion. All the organizations have an IT expense management solution in place. Below are some of the study’s key findings.

Moving Forward Requires Investment

The challenge is that businesses need to move forward, and that requires continued investment.

As IT spending continues to climb, driven by the escalating costs of artificial intelligence, cloud, and mobile tools, organizations are feeling even more pressure on their budgets. This makes the ability to track and manage spending, govern expenses, and adjust IT budgets effectively a must.

The Tangoe study uncovered that third-party information technology expense management (ITEM) solutions foster more mature financial operations (FinOps) programs and offer faster business insights and savings than alternative approaches.

Furthermore, such solutions often incorporate automated processes that help reduce the risk and costs associated with IT outages. According to the data, this approach has proven to be five times more cost-effective than its alternatives, offering a superior method for managing IT expenses.

Cost Efficiency Disparity

One of the standout findings is the cost disparity between different expense management approaches.

Organizations using a fully external ITEM solution reported spending approximately $442,000 on average, which is remarkably lower than the $2.35 million incurred by those with a hybrid approach. By outsourcing, organizations not only save money but also free up internal resources.

Unlike in-house programs, which typically rely on vendor-provided tools, third-party providers offer specialized analytics platforms to identify cost optimization opportunities and managed services that help companies act on them quickly. This allows organizations to focus on critical investments and decision-making, rather than mundane tasks like invoice processing, expenditure analysis, and service adjustments.

Advanced FinOps Programs

Organizations that employ third-party solutions for managing IT expenses are more likely to have a mature FinOps practice, with 94 percent of organizations having a dedicated team for optimizing cloud spending.

Those using an external provider are more successful in deploying their FinOps practices, with 61 percent achieving full deployment compared to 53 percent of those using other methods. Having a FinOps program in place has also been shown to reduce spending on cloud infrastructure and software by 20 percent and 28 percent, respectively.

Improved Insights and Savings

Nearly all (99 percent) senior IT and finance decision-makers experienced significant benefits from outsourcing. Third-party ITEM solutions tackle common challenges related to data analysis, IT service inventory management, and manual processes.

Organizations using these solutions reported a 90 percent improvement in productivity and process efficiency, with 88 percent experiencing faster access to business insights and cost savings.

On average, organizations saved more than $10.5 million annually by outsourcing to third-party providers. Additionally, 88% of those with fully outsourced solutions achieved business insights and savings faster.

Automation is Necessary

Approximately 43 percent of IT expense management tasks are still performed manually. The consequences of manual dependency include service outages due to late payments, experienced by 85 percent of organizations. This can lead to substantial revenue losses and potentially halt operations completely.

According to the findings, automation decreased the frequency of regular outages from 41 percent in environments with mostly manual processes to 32 percent in those with automated processes—a 22 percent reduction.

Bottom Line: Third-Party ITEM Supports Cost Savings

As businesses expand and grow, IT expense management is a critical tool to boost profitability. Third-party ITEM solutions help organizations manage the complexities of modern IT expense management by supporting advanced FinOps practices, decreasing manual workloads, and providing considerable cost savings.

To learn more about how companies are driving digital transformation, see our guide: Digital Transformation Guide

The post Study: IT Expense Management Drives FinOps Maturity appeared first on eWEEK.

In this TweetChat, held on the X platform, experts will share practical advice about how business users can derive the most competitive advantage from generative AI. Clearly, generative AI is a technology with enormous potential, yet also one with considerable challenges and risks. How can businesses navigate the pros and cons of generative AI, even as it constantly changes?

See below for the resources you need to participate in the eWeek Tweetchat.

Participants List: Optimizing Generative AI

The list of experts for this month’s TweetChat currently includes the following – please check back for additional expert guests:

• Bernard Golden, Executive Technical Advisor, VMware  
• Marinela Profi, Global Product Strategy for AI and Generative AI, SAS
• Rob Lee, Chief Curriculum Director and Faculty Lead, SANS Institute
• Saurabh Vij, CEO of Monster, API
• Brian Wald, Field CTO, GitLab
• Jitender Aswani, VP, Engineering, StarTree
• Aaron Rosenmund, Director of Security Research and Curriculum, Pluralsight
• Jignesh Patel, Computer Science Professor, Carnegie Mellon University, Co-Founder, DataChat
• Dave Jenkins, VP of Product and Research, Iterate
• Shipra Sharma, Head of AI and Analytics, Bristlecone
• Andi Mann, Global CTO and Founder, Sageable
• Zeus Kerravala, Founder and Principal Analyst, ZK Research
• James Maguire, Editor-in-Chief, eWeek [moderator]

TweetChat Questions: Optimizing Generative AI

The questions we’ll tweet about will include the following – check back for more/revised questions:

1. First, the big question: do you believe the hype about generative AI? That it will disrupt everything in its path and completely reshape business?
2. Okay, about you personally: Where are you with your use of generative AI? Occasional use, researching, real work support?
3. Assuming you don’t use gen AI non-stop, what keeps you from using it more? What’s the biggest weakness in gen AI in your view?
4. What advice would you give to businesses to get more value from generative AI?
5. What’s your sense of how receptive companies are to using gen AI more?
6. What about security and generative AI? Is gen AI the security quagmire it appears to be? How to address these concerns?
7. Other concerns about generative AI? Accuracy of response, job losses? What’s your advice to companies?
8. Looking ahead, what business sectors will most immediately be changed/reshaped by gen AI? Any recommendations for these sectors’ managers?
9. What’s one last big thought that your tech colleagues should know about optimizing the benefit of generative AI?

How to Participate in the TweetChat

The chat begins promptly at 11 AM PT on May 14th. To participate:

1. Open Twitter in your browser. You’ll use this browser to Tweet your replies to the moderator’s questions.

2. Open Twitter in a second browser. On the menu to the left, click on Explore. In the search box at the top, type in #eweekchat. This will open a column that displays all the questions and all the panelists’ replies.

Remember: you must manually include the hashtag #eweekchat for your replies to be seen by that day’s tweetchat panel of experts.

That’s it — you’re ready to go. Be ready at 8 AM PST to participate in the tweetchat.

NOTE: There is sometimes a few seconds of delay between when you tweet and when your tweet shows up in the #eWeekchat column.

#eWEEKchat Tentative Schedule for 2024*

January 16: Governing Generative AI
February 13: Data Analytics Best Practices
March 12: How Tech Pros Get the Most From AI
April 16: Managing Multicloud Computing
May 14: Optimizing Generative AI
June 18: Mid-Year Look Ahead: Future of Tech

*all topics subject to change

The post eWEEK TweetChat, May 14th: Optimizing Generative AI appeared first on eWEEK.

Using the X platform (formerly known as Twitter), we’ll discuss the enormous upside of multicloud, and also cover the sometimes frustrating and expensive challenges of a multicloud deployment. How to best handle this complex enterprise infrastructure? And how can companies optimize their ever-changing multicloud platform?

See below for the resources you need to participate in the eWeek Tweetchat.

Participants List: Managing Multicloud Computing

The list of experts for this month’s TweetChat currently includes the following – please check back for additional expert guests:

• Bernard Golden, Executive Technical Advisor, VMware
• Lee Caswell, SVP, Nutanix
• Jay Litkey, Executive VP of the Cloud Management, Snow Software
• Evan Kirtstel, Chief Digital Evangelist, Cofounder, eVIRa Health
• Carm Taglienti,  Chief Data Officer, Insight
• Nate Brady, Sr. Enterprise Architect at Skyhigh Security
• Scott Wheeler, Cloud Practice Lead at Asperitas
• Kerrie Jordan, Group Vice President, Product Management, Epicor
• Andi Mann, Global CTO and Founder, Sageable
• Zeus Kerravala, Founder and Principal Analyst, ZK Research
• James Maguire, Editor-in-Chief, eWeek [moderator]

TweetChat Questions: Managing Multicloud Computing

The questions we’ll tweet about will include the following – check back for more/revised questions:

1.  Multicloud has been the default enterprise strategy for years now. Has it lived up to its potential?
2. What key trends are boosting the multicloud sector here in 2024?
3. What are the most frustrating multicloud challenges today? Cost, security, accountability?
4. How do you recommend addressing these challenges?
5. What Best Practices advice would you give to companies to optimize a multicloud deployment?
6. What’s about multicloud and a related technology? How about AI? How is multicloud interacting/driving that related technology?
7. It turns out the data center is alive and well in 2024. Won’t cloud – and now multicloud – even make the datacenter obsolete?
8. The future of multicloud? What will it look like 2-4 years from now?
9. A last Big Thought about multicloud – what else should managers/buyers/providers know about cloud?

How to Participate in the TweetChat

The chat begins promptly at 11 AM PT on April 16th. To participate:

1. Open X (previously called Twitter) in your browser. You’ll use this browser to Tweet your replies to the moderator’s questions.

2. Open X in a second browser. On the menu to the left, click on Explore. In the search box at the top, type in #eweekchat. This will open a column that displays all the questions and all the panelists’ replies.

Remember: you must manually include the hashtag #eweekchat for your replies to be seen by that day’s tweetchat panel of experts.

That’s it — you’re ready to go. Be ready at 11 AM PST to participate in the tweetchat.

NOTE: There is sometimes a few seconds of delay between when you tweet and when your tweet shows up in the #eWeekchat column.

#eWEEKchat Tentative Schedule for 2024*

January 16: Governing Generative AI
February 13: Data Analytics Best Practices
March 12: How Tech Pros Get the Most From AI
April 16: Managing Multicloud Computing
May 14: Optimizing Generative AI
June 11: Mid-Year Look Ahead: Future of Tech

*all topics subject to change

The post eWEEK TweetChat, April 16: Managing Multicloud Computing appeared first on eWEEK.

The survey targeted 300 senior IT, information security, and software development and operations (DevOps) managers working in organizations with more than 1,000 employees across North America, Europe, and Asia-Pacific. The survey findings were published in the 2024 State of Digital Trust report, highlighting a stark contrast between top-performing companies (leaders) and lower-performing ones (laggards).

Higher Revenue and Increased Employee Productivity

The survey indicated that digital trust leaders, representing the top 33 percent of the respondents, have higher revenue, digital innovation, and increased employee productivity.

These leaders excel in responding to outages and incidents, show readiness for post-quantum computing, and effectively utilize the Internet of Things (IoT). They demonstrate a mature approach to administering digital trust through centralized certificate management and the use of email authentication and encryption (S/MIME) technology.

Conversely, the bottom 33 percent—the laggards—struggle in these areas, facing challenges in leveraging digital innovation and maintaining robust digital infrastructure and security practices. Notably, while leaders experienced few system outages, data breaches, and compliance issues, half of the laggards reported problems with IoT standards compliance, and many suffered from software trust mishaps.

Only one in 100 companies surveyed claimed to have highly developed digital trust practices, indicating a common problem in maintaining enterprise digital trust. Furthermore, 98 percent of reported outages and brownouts were attributed to digital trust issues like expired certificates or domain name system (DNS) problems. None of the respondents were confident in their ability to react promptly to such incidents.

For more information about how digital transformation is driving progress, see our coverage: Digital Transformation Guide

The Challenge of Quantum Computing

The looming growth of quantum computing adds another layer of complexity. Quantum capabilities are rapidly accelerating, driven by tech advancements like generative artificial intelligence.

The report uncovers a gap in preparedness for quantum-resistant technologies and the need for strategic action in the face of this evolving threat. According to the data, 61 percent of organizations find themselves underprepared for the post-quantum transition.

Leaders estimate a two-year timeframe to fully respond to the quantum shift, whereas laggards project three years or more. This discrepancy highlights the urgency of developing actionable plans, especially given the current five-year window before quantum computing becomes a more pressing concern. Therefore, immediate and strategic action is necessary in the face of uncertainty, said Brian Trzupek, Senior VP of Product at DigiCert.

“This quantum thing is a big deal. People are starting to get the visibility that this is a looming challenge. It’s greater than just a digital certificate replacement because it’s fundamentally the algorithm that has been attacked. All the libraries for the dependent client software, for the web servers, for the app servers, for the databases—all those things will need updates, including a certificate, to make that work,” said Trzupek.

Concerns Around SSH Protocols

Survey respondents are concerned on the reliance on the secure shell (SSH) protocol based on the Rivest-Shamir-Adleman (RSA) public-key encryption, which is used ubiquitously across cloud services for secure communication and authentication.

Additionally, hardware implementations of RSA, such as secure sockets layer (SSL) offloading and accelerators, present a significant challenge. Trzupek shared an example of one cloud provider that reported having 200,000 such devices, all potentially rendered obsolete by the shift to quantum-resistant algorithms.

Another surprising finding is that 87 percent of the respondents reported that their IoT devices transmitted personally identifiable information (PII) over unencrypted channels. This security loophole in IoT devices poses a threat to user privacy. Fortunately, businesses are now recognizing the significance of upgrading their digital infrastructure to protect users.

Issues in Software Trust

There are major developments happening in the realm of software trust, mainly in implementing software bills of materials (SBOMs) or detailed inventories of software components.

In the previous report, approximately three percent of organizations were aware of or working on SBOMs. In this report, the number has increased monumentally to 99 percent. While organizations recognize the importance of SBOMs, the actual deployment and meaningful use of SBOMs may not be as widespread as the numbers suggest.

Electronic signatures (e-signatures) have also emerged as a key area of interest, with a low percentage of respondents saying their e-signature practices are extremely mature. The business teams, such as legal, human resources, and procurement, usually handle them, not the IT department.

Only about one in eight organizations understand the difference between simple e-signatures and the more secure ones that use certificates. Nearly half (48 percent) use electronic seals on their documents, and most (86 percent) use digital signatures with certificates issued by trusted third parties.

“There are business processes for how you apply those signatures. We see a lot of customers still struggling to make use of cryptographically secure signatures on content like mortgage documents and healthcare documents. They’re definitely looking at making those processes very easy to use. From our survey here, you can see that that’s something they’re still trying to work on,” said Trzupek.

Bottom Line: How to Enhance Digital Trust

To enhance digital trust, DigiCert recommends that organizations thoroughly inventory their digital assets, define clear policies, centralize public key infrastructure (PKI) management, and prioritize their efforts based on business impact.

This can help mitigate security issues, build confidence among customers and partners, and improve operations. Effective digital trust management enables organizations to navigate regulatory challenges, ensuring compliance while protecting sensitive data and adapting to cyber threats.

To learn about the companies leading the way in digital transformation, see our guide: Top Digital Transformation Companies

The post Report: Digital Trust Boosts Productivity and Revenue appeared first on eWEEK.

Hosted by Brian Tobia, ThousandEyes’ Lead Technical Marketing Engineer, the webcast included a look at the anatomy of an outage. “It’s important to understand the different types of outages we see,” he said. “Understanding them can help you understand how to mitigate some of their impact.” He said outages could vary in the blast radius, whether they’re planned or unplanned, and their mean time to recovery.

Let’s take a look at what caused the year’s major cloud outages – and what we can learn from these unfortunate incidents.

Different Types of Cloud Outages

“The distributed architecture of today’s applications means there are a lot of different moving parts that need to be orchestrated for something to actually work,” Tobia said. “And a lot of these parts are often single points of failure. Because they’re reused in multiple applications, like an API or a common service, we can see the impact of an outage more widely felt, despite it being a single service.”

Tobia noted that tracking cloud computing outages can help teams identify patterns and prevent customer service disruptions.

Looking at the ThousandEyes report from 2023, Tobia said there were many different types of outages. “Overall, we still saw the most common type being ISP-related outages,” he said. “But we saw that there was an increase in CSP outages in 2023 compared to the previous years.”

In 2023, the number of US-centric outages increased from 34% to 37% and minor outages became more common. “We’re seeing that these smaller, more contained outages are becoming more common,” he said. “Before, there were traditionally a lot of bigger network outages—like really big ones—that would take down a whole bunch of services. But now we’re also seeing smaller ones.”

But even a cloud outage that starts in the US due to maintenance activity at night can cascade into other geographies in the middle of their business days.

Application Outages On the Rise

Tobia said that application outages, which continued to rise in 2023, can have a greater impact. A network outage will affect a single provider, but not so for applications. “The application outage really cascades because a bunch of people are relying on that one application,” he said. “It doesn’t matter what network you’re coming from.”

He then moved on to look at some outage examples from 2023, focusing on how ThousandEyes works. “We’re able to collect all this data through ThousandEyes,” he said. “Being able to correlate that and collect all this data, it’s really important to get the end-to-end picture of where an outage might occur. And then, also really important, correlate that across every layer.”

He added that ThousandEyes can show users every layer of a connection, whether it’s related to border gateway protocol (BGP), networks, applications, HTTP errors, or page load times.

Top Cloud Outages of 2023

Tobia detailed the list of 2023 outages, including:

• A 90-minute outage for Microsoft on January 25: This was due to BGP changes that caused network issues. “This was total chaos from a BGP perspective,” Tobia said.
• A two-hour outage for Outlook on February 7: This resulted in service unavailable/application errors. “The last outage was more around some changes on their ISP routers and other WAN routers,” he said. “This may have been more on the application side.”
• A seven-hour Virgin Media outage on April 4: This outage arose because of a BGP route withdrawal that caused network traffic loss. “It was kind of similar to what we saw on the on the Microsoft side, when those BGP changes were occurring,” he said. “Without a route to the Virgin Media UK network, a lot of the Internet and transit providers dropped the traffic.”
• A two-hour AWS cloud outage on June 14: This outage caused latency, server timeouts, and HTTP errors. “They eventually identified the issue as being part of their capacity management system located within US-EAST-1,” he said. “And this impacted services like Lambda API gateway, and the actual management console itself, Global Accelerator.”
• A two-hour Slack cloud outage on August 2: As a result of this outage, users couldn’t send or receive messages. “Network paths were totally fine,” he said. “We didn’t see any packet loss, latency, or anything like that. So it was purely an application or client issue.”
• An 18-hour Square cloud outage on September 8: This outage resulted in app errors and backend transactions failing. “This outage prevented it from processing transactions,” he said. “So end users were actually able to submit a transaction – some sellers who were using this to receive payments were successful, [but some users] reported connections dropping out or things not working.”
• A 36-hour Workday/Cloudflare outage that started on November 2: A complete power failure at a Cloudflare data center caused application and service issues. “Cloudflare was the provider and Workday was an application that runs on Cloudflare infrastructure,” he said. He noted that DR resources took 6 hours to come online. “So there was a complete outage until that facility came online,” he added. “It was able to serve requests at a diminished rate and then full resolution didn’t happen until more than 36 hours later.”

Bottom Line: Need for Monitoring to Prevent Cloud Outages

It was a busy year! Clearly, Tobia’s examples of cloud outages were sobering. Who thought a full power outage was possible today with the sophisticated data centers that providers like Cloudflare run? But they still had to deal with the arduous process of getting their DR up and running and working with a power company that may not move at the fastest pace.

Tobia’s presentation also underscored the importance of monitoring resources to understand what happens when a service goes down so that one can learn and avoid repeating the same mistakes.

Unfortunately, for most businesses, having a backup for every cloud service the organization uses would be fiscally challenging. For support, IT leaders can use data from companies like ThousandEyes to make uptime part of the evaluation criteria.

For a complete guide to the cloud computing sector, see our in-depth coverage: Top Cloud Service Providers and Companies

The post ThousandEyes Report: Top Cloud Outages of 2023 appeared first on eWEEK.

To explore this trend, Cisco recently surveyed 3,500 employees and 1,050 employers from companies of all sizes across seven European countries: France, Germany, Italy, The Netherlands, Poland, Spain, and the UK. The findings were published in a report, The Race to Reimagine Workplaces and Workspaces for a Hybrid Future, released as part of the company’s Cisco Live EMEA activities.

Enthusiasm is High But Readiness Lags

The report sheds light on the current state of hybrid workspaces and work in Europe, revealing both enthusiasm and challenges. It also examines differences in responses to the technologies used by Baby Boomers, Gen X, Millennials, and Gen Z, debunking common misconceptions about employee attitudes toward hybrid work.

The enthusiasm for returning to the office is clear, driven by the potential for enhanced productivity, collaboration, and a sense of belonging. However, the readiness of office spaces to support hybrid workspaces is lagging, with only a fraction of employers and employees considering their offices well-prepared for this new way of working. The report highlights a pressing need for office redesigns to accommodate a multi-generational workforce’s demands better.

Currently, nearly 80 percent of organizations in Europe employ at least 10 percent of their workforce in hybrid roles, with half reporting over 30 percent of their staff coming to the office three to four days a week. A significant aspect of this shift is that a third of all office interactions now involve remote workers, highlighting the need for collaboration technology. As we advance, 83 percent of employers anticipate that hybrid work will become the norm within two years.

The desire for personal flexibility and comfort largely drives employees’ preference to work from home. Notably, work preference varies by generation. Baby Boomers prefer office-based work, while Gen Z and Millennials prefer remote and hybrid arrangements. According to the findings, 68 percent of employers have received positive feedback on mandates for returning to the office, and 74 percent of employees express a positive view.

For more information about how companies are modernizing the workplace, see our article: Digital Transformation Guide

The Need for Collaborative Spaces and Tech Infrastructure

There’s a significant gap between what employees expect from their office environment and what is currently available, especially in areas critical for hybrid work, such as collaborative spaces and tech infrastructure.

Only 32 percent of employers and 37 percent of employees consider their office spaces well-prepared for hybrid work. The reason is that current office setups do not adequately promote in-office productivity, with most spaces consisting of workstations. Employees and employers find personal workstations and meeting rooms only moderately effective, highlighting the need for updated office space designs. This data should not be a shock as many European office spaces have not seen a significant technology upgrade in decades.

Redesigning office spaces to meet the expectations of a multi-generational workforce can be challenging due to varying perceptions of the effectiveness of meeting rooms. The key reasons for the perceived ineffectiveness of meeting rooms include:

• The absence of video and audio (42 percent)
• Poor audio-visual quality (37 percent)
• A lack of inclusivity and consistency for remote participants (26 percent)

Shockingly, less than half of the meeting rooms in office buildings are equipped with video and audio capabilities. Furthermore, employees and employers are concerned about the lack of seamless integration among collaboration tools, with only 10 percent of Gen Z employees considering the current tools seamless.

The report also points out a surprising underemphasis on sustainability in office redesigns despite the growing importance of eco-friendly practices in corporate strategy. Only 45 percent of employers and 36 percent of employees view eco-friendly practices as top priorities in workspace redesign. This lack of oversight may be contributing to the trend of increasing office footprints.

Despite this trend, employers remain focused on improving the employee experience through office redesigns. Most employers (90 percent) and employees (87 percent) believe a positive link exists between workspace design and employee satisfaction. Furthermore, over two-thirds of employers try to ensure a smooth transition between home and office environments.

Common support measures include:

• Flexible work arrangements (50 percent)
• Technology usage training (48 percent)
• Enhanced network infrastructure at both home and office (42 percent)

The technology tools provided to employees primarily include:

• Video conferencing platforms (54 percent)
• Instant messaging/team chats (52 percent)
• Cloud-based document sharing (49 percent)
• Project management (43 percent)
• Virtual meeting rooms (33 percent)

Simplifying the user experience remains a significant challenge in ensuring employees can effectively use these tools. In fact, 75 percent of employees lack proficiency with project management and collaboration tools, while 71 percent are deficient in video conferencing and 70 percent in cloud-based document sharing.

Advice for Hybrid Work Upgrades

Cisco makes several recommendations to companies with hybrid work models. This includes rejuvenating meeting spaces, implementing hybrid-friendly technology and network solutions, refreshing office layouts for improved collaboration, and embedding sustainability into workspace designs.

Companies of all sizes should be addressing connectivity issues and ensuring interoperability to provide a seamless, stress-free work experience. Moreover, Cisco recommends fast-tracking hybrid work strategies to align with technological advancements, workspace aesthetics, and corporate culture.

Companies must understand that technology alone is not enough. Adequate training and support are also necessary to ensure ease of use and improved productivity. Achieving an optimal hybrid environment requires a balanced approach that’s both productive and sustainable, where employees can thrive in the new era of work.

Bottom Line: The Need to Modernize Hybrid Workspaces

Over the past year, many businesses have mandated employees return to the office only to have to repeal the mandate a short time later. Before organizations lay the hammer down, they should look at the office’s technology to ensure it facilitates a best-in-class experience. Investing in this area will go a long way toward employee happiness, which cuts churn, improves morale, and makes everyone more productive.

For an in-depth list of today’s digital transformation leaders, see our guide: Top Digital Transformation Companies

The post Report: Europeans Return To The Office But Hybrid Workspaces Need Modernization appeared first on eWEEK.

Cloud has taken every industry by storm. But the report shows that, despite the apparent benefits, “a variety of challenges still get in their way, mostly around cost control, security expertise, and a skills gap.” Furthermore, the ongoing “cloud sprawl” has not helped these issues. In fact, they’ve gotten worse. There’s a lack of visibility, accountability, and governance of the costs of SaaS and IaaS.

The report, based on a survey by Foundry of 200 enterprise IT decision-makers in a number of industries, looked at the benefits of FinOps, which is a framework that maximizes the business value of cloud computing. 

Overcoming Cloud Challenges with FinOps

FinOps can be a path to overcoming cloud cost challenges, with respondents reporting these are the main drivers for using FinOps:

• 70% say they’re interested in increasing cloud resource performance.
• 60% say they want to make budget cuts.
• 58% say they want to manage rising costs and macroeconomic pressures.

When it comes to the benefits, the survey showed increased productivity (44%), cost savings (43%), and reduced security risk (43%) at the top of the list.

Implementations vary widely, but there are three factors, according to Foundry, that increase the likelihood of success: implementation approach, the use of artificial intelligence, and wide-reaching optimization programs spanning both IaaS and SaaS.

For a deeper portrait of the cloud market, read our in-depth overview: Top Cloud Service Providers and Companies

In-House vs. Outsourced

When it comes to in-house vs. outsourced implementations, outsourced is the clear winner, with in-house FinOps solutions fetching less than 10% in savings and outsourced solutions bringing in 20% savings.

Tangoe’s chief product officer, Chris Ortbals, quoted in the report, says that although DIY is the way most companies go, they’re not best suited to optimize those implementations. “Strategic partners are essential because they look at usage and expenses from a different perspective,” he said. This diverse vantage point provides them with “the context of understanding how hundreds of companies optimize millions of dollars in IT spending.”

AI in FinOps

With AI top-of-mind for everyone these days, this report doesn’t disappoint. The survey shows that 71% of respondents use or plan to use AI in their programs.

That makes sense when you see that companies that use AI in FinOps are 53% more likely to save more than 20%. On the other side of the ledger, companies that don’t use AI will get savings of only 6% to 10%.

Ortbals adds that every FinOps practitioner should include AI in their bag of tricks. “Without AI it’s simply impossible to evaluate massive amounts of data against all possible configuration options, playing out what-if scenarios to quickly determine which action will yield the highest savings,” he said.

“AI can do this at enterprise scale. Plus, it can help IT engineers implement cost-saving recommendations once approved. This results in faster time-to-savings and programs that can achieve higher returns.”

The report says 63% of respondents think analytics is the top use case for AI in FinOps, with 50% saying it eases the FinOps management burden and 48% saying they have seen productivity gains from AI automation.

Also see: 100+ Top AI Companies 2024

SaaS and IaaS

When it comes to SaaS and IaaS, the report shows SaaS users can save 20% or more while IaaS users save less than 10%.

Ortbals said that savings add up with one high-volume application or a few smaller applications that can break a budget.

“But CIOs and CFOs should drive broader cloud ROI,” he said. “FinOps is designed to maximize the benefits of SaaS and IaaS. Start with applications, expand into cloud infrastructure, and consider how you can apply FinOps principles to other areas of IT spending like mobile and telecom.”

Choosing a FinOps Solution

So, what should you consider when selecting a solution? The report says that these are the top five criteria:

• 70%: Industry expertise. Customers want a partner who is versed in the complexities of cloud optimization but also understands the specific insights of each vertical, as mapping them to FinOps is mandatory for success.
• 69%: AI and automation capabilities. There is no bigger transformative technology today than AI, which will have a massive impact on FinOps. Basic use cases include automation of basic tasks, but long-term, generative AI will enable users to access information via natural language.
• 68%: Fully managed services. Not all businesses have the desire to operate FinOps themselves, particularly with AI accelerating the pace of change. Managed services are an excellent option for companies that want to take advantage of FinOps but do not want to go through the deployment and management process.
• 63%: Flexibility of solution. Businesses want choices, and vendors that offer optimization for only one or two cloud service providers or a limited number of applications are quickly outgrown as customers look to cut costs across their rapidly changing multicloud estates.
• 62%: Certifications, licenses, awards. These validate that the vendor solutions work as advertised and have the leading features to give customers a competitive advantage.

Bottom Line: The Value of FinOps

This report provides some fascinating insights for cloud users. FinOps is a great use case for AI, and managing cloud resource utilization could be one of the more intriguing implementations of the technology, with significant savings for enterprises possible in the near term.

To learn more about how companies are modernizing their IT processes, read our in-depth article: Digital Transformation Guide

The post How FinOps and AI Curb Escalating Cloud Costs appeared first on eWEEK.

An observability solution monitors a company’s IT infrastructure by constantly monitoring its outputs. In most cases, the most important outputs are those that track the performance of the core applications that enable the company to keep running.

Historically, this monitoring task has been handled by humans, and still is, largely. Yet as tech infrastructure grows ever more complex, humans need ever more help to keep up. Hence the growth of observability solutions.

In fact, observability is increasingly important as IT infrastructure grows increasingly complex – and companies know that.

Chronosphere focuses on cloud native observability, which is well-suited  to contemporary IT deployments that include elements like microservices and multicloud deployments.

See below for a podcast and video version of the interview.

What’s Driving Observability Adoption

 As recently as 2021, just 61 percent of companies had a centralized observability solution. By 2023, that number had risen to about 70 percent. So certainly observability has room for growth – and yet there’s still some skepticism about this emerging tech.

As Smith noted, the doubting companies ask, “‘well, what am I getting beyond the high-level marketing message?’”

The answer, ultimately, is that observability is far more than cobbling together an array of  interoperating tools. What drives companies to adopt this technology is how observability can assist engineering to facilitate what a business needs, and also – especially – observability’s ability to help control costs, including the expense of multicloud computing.

It’s also about growth. Smith has heard companies say, “’When we previously settled on our observability tooling, we were a much smaller company. We had a really big focus on observability, used by our most senior resources – and they drove the evaluation. Now we have maybe 10, 15 times more engineers and it’s a very broad spread of experiences.”

Observability Strategy

Everything in enterprise IT requires planning, but observability, due to its complexity, requires truly deliberate planning.

A company needs to understand, Smith noted, “Who’s using [the observability tool], what are they using it for, how much are they utilizing it? And be able to compare across those data sets.”

For instance, “Maybe you have some data that’s only used once every three months for a capacity plan, but it’s very, very small in its footprint. But there’s data over here, it’s used every day, for instance for [important] investigations.” It’s essential to know where your data is – and what data is needed at all time to answer essential business questions.

The most important element of creating an observability strategy is deciding precisely what your goal is – and agreeing on that goal across the company.

So ask, “What is the problem we’re actually trying to solve?” Smith said. Some companies aren’t all on the same page. “And so how can you possibly buy something thinking it’s a solution for a problem if you haven’t actually completely defined that [data] problem upfront?

“Maybe it is, for instance, that we need to direct a large portion of observability data into some other area, maybe a data lake because we’ve been abusing our observability tooling. And these are all strategic initiatives that come out of really stepping back and looking at that bigger picture.”

AI and the Future of Observability  

There is, in Smith’s view, a major industry hope that that AI can simply swoop down and answer all of the thorny issues involved with monitoring IT infrastructure. While that belief is unrealistic, certainly the growth of AI has major ramifications for IT – particularly due to AI’s assistance with communication between humans and the system.

In short, the future of observability will enable IT admins to simply talk to their systems. “Wouldn’t it be great to be able, in natural language, to really just ask what is going on with this particular part of the system? Then having a way for the observability system to distill down, ‘these are things you should be focusing on, and here’s an explanation for why.’”

This process is a realistic expectation for observability users. “It’s rooted in data and it’s rooted in building up [data] over time and understanding a model of what these things mean.”

Listen to the podcast:

Also available on Apple Podcasts

Watch the video:

The post Chronosphere’s Ian Smith on Cloud Native Observability appeared first on eWEEK.

Both of these application and service suites are in heavy demand, as organizations seek to harness real-time repositories of big data for various enterprise use cases, including artificial intelligence and machine learning model development and deployment.

When choosing between two of the most highly regarded data platforms on the market, users often have difficulty differentiating between Cognos and Power BI and weighing each of the platform’s pros and cons. In this in-depth comparison guide, we’ll compare these two platforms across a variety of qualities and variables to assess where their strengths lie.

But first, here’s a glance at the areas where each tool excels most:

• Cognos Analytics: Best for advanced data analytics and on-premises deployment. Compared to Power BI, Cognos is particularly effective for advanced enterprise data analytics use cases that require more administrative controls over security and governance. Additionally, it is more reliable when it comes to processing large quantities of data quickly and accurately.
• Power BI: Best for affordable, easy-to-use, integrable BI technology in the cloud. Compared to Cognos Analytics, Power BI is much more versatile and will fit into the budget, skill sets, and other requirements of a wider range of teams. Most significant, this platform offers free access versions that are great for teams that are just getting started with this type of technology.

Cognos vs. Power BI at a Glance

What Is Cognos?

Cognos Analytics is a business intelligence suite of solutions from IBM that combines AI-driven assistance, advanced reporting and analytics, and other tools to support various enterprise data management requirements. The platform is available both in the cloud and on demand for on-premises and custom enterprise network configurations.

With its range of features, Cognos enables users to connect, verify, and combine data and offers plenty of dashboard and visualization options. Cognos is particularly good at pulling and analyzing corporate data, providing detailed reports, and assisting in corporate governance. It is built on a strong data science foundation and is supported by heavy-duty analytics and recommendations, courtesy of IBM Watson.

Also see: Top Business Intelligence Software

Key Features of Cognos

• AI-driven insights: The platform benefits from veteran AI support in the form of Watson, which helps with data visualization design, dashboard builds, forecasting, and data explainability. This is particularly helpful for users with limited data science and coding experience who need to pull in-depth analyses from complex datasets.
• Data democratization through natural language: Advanced natural language capabilities make it possible for citizen data scientists and less-experienced tech professionals to create accurate and detailed data visualizations.
• Advanced reporting and dashboarding: Multi-user reports and dashboards, personalized report generation, AI-powered dashboard design, and easy shareability make this a great platform for organizations that require different levels of data visibility and granularity for different stakeholders.
• Automation and governance: Extensive automation and governance capabilities help power users scale their operations without compromising data security. The platform’s robust governance and security features are important to highly regulated businesses and large enterprises in particular.

Pros

• The platform is well integrated with other business tools, like Slack and various email inboxes, making it easier to collaborate and share insights across a team.
• Its AI assistant works well for a variety of data analytics and management tasks, even for users with no data science experience, because of its natural language interface.
• Cognos comes with flexible deployment options, including on-demand cloud, hosted cloud, and client hosting for either on-premises or IaaS infrastructure.

Cons

• The platform is not particularly mobile-friendly compared to similar competitors.
• While a range of visuals are available on the platform, many user reviews indicate that the platform’s visuals are limited and not very customizable.
• Depending on your exact requirements, Cognos Analytics can become quite expensive, especially if you have a high user count or require more advanced features like security and user management.

What Is Power BI?

Microsoft Power BI is a business intelligence and data visualization software solution that acts as one part of the Microsoft Power Platform. Because of its unification with other Power Platform products like Power Automate, Power Apps, and Power Pages, this BI tool gives users diverse low-code and AI-driven operations for more streamlined data analytics and management. Additional integrations with the likes of Microsoft 365, Teams, Azure, and SharePoint are a major selling point, as many business users are already highly invested in these business applications and are familiar with the Microsoft approach to UX/UI.

Specific to analytics functions, Power BI focuses most heavily on data preparation, data discovery, dashboards, and data visualization. Its core features enable users to take visualizations to the next level and empower them to make data-driven decisions, collaborate on reports, and share insights across popular applications. They can also create and modify data reports and dashboards easily and share them securely across applications.

Key Features of Power BI

• Rapidly expanding AI analytics: AI-powered data analysis and report creation have already been established in this platform, but recently, the generative AI Copilot tool has also come into preview for Power BI. This expands the platform’s ability to create reports more quickly, summarize and explain data in real time, and generate DAX calculations.
• CRM integration: Power BI integrates relatively well with Microsoft Dynamics CRM, which makes it a great option for in-depth marketing and sales analytics tasks. Many similar data platforms do not offer such smooth CRM integration capabilities.
• Embedded and integrated analytics: The platform is available in many different formats, including as an embedded analytics product. This makes it possible for users of other Microsoft products to easily incorporate advanced analytics into their other most-used Microsoft products. You can also embed detailed reports in other apps for key stakeholders who need information in a digestible format.
• Comprehensive visualizations: Adjustable dashboards, AI-generated and templated reports, and a variety of self-service features enable users to set up visuals that can be alphanumeric, graphical, or even include geographic regions and maps. Power BI’s many native visualization options mean users won’t have to spend too much time trying to custom-fit their dashboards and reports to their company’s specific needs.

Pros

• Power BI is one of the more mobile-friendly data platforms on the market today.
• In addition to its user-friendly and easy-to-learn interface, Microsoft offers a range of learning resources and is praised for its customer support.
• Its AI-powered capabilities continue to grow, especially through the company’s close partnership with OpenAI.

Cons

• Some users have commented on the tool’s outdated interface and how data updates, especially for large amounts of data, can be slow and buggy.
• The platform, especially the Desktop tool, uses a lot of processing power, which can occasionally lead to slower load times and platform crashes.
• Shareability and collaboration features are incredibly limited outside of its highest paid plan tier.

Best for Core Features: It Depends

It’s a toss-up when it comes to the core features Cognos Analytics and Power BI bring to the table.

Microsoft Power BI’s core features include a capable mobile interface, AI-powered analytics, democratized report-building tools and templates, and intuitive integrations with other Microsoft products.

IBM Cognos Analytics’ core features include a web-based report authoring tool, natural-language and AI-powered analytics, customizable dashboards, and security and access management capabilities. Both tools offer a variety of core features that work to balance robustness and accessibility for analytics tasks.

To truly differentiate itself, Microsoft consistently releases updates to its cloud-based services, with notable updates and feature additions over the past couple of years including AI-infused experiences, smart narratives (NLG), and anomaly detection capabilities. Additionally, a Power BI Premium version enables multi-geography capabilities and the ability to deploy capacity to one of dozens of data centers worldwide.

On the other hand, IBM has done extensive work to update the Cognos home screen, simplifying the user experience and giving it a more modern look and feel. Onboarding for new users has been streamlined with video tutorials and accelerator content organized in an easy-to-consume format. Additionally, improved search capabilities and enhancements to the Cognos AI Assistant and Watson features help generate dashboards automatically, recommend the best visualizations, and suggest questions to ask — via natural language query — to dive deeper into data exploration.

Taking these core capabilities and recent additions into account, which product wins on core features? Well, it depends on the user’s needs. For most users, Power BI is a stronger option for general cloud and mobility features, while Cognos takes the lead on advanced reporting, data governance, and security.

Also see: Top Dashboard Software & Tools

Best for Ease of Use and Implementation: Power BI

Although it’s close, new users of these tools seem to find Power BI a little easier to use and set up than Cognos Analytics.

As the complexity of your requirements rises, though, the Power BI platform grows more difficult to navigate. Users who are familiar with Microsoft tools will be in the best position to use the platform seamlessly, as they can take advantage of skills from applications they already use, such as Microsoft Excel, to move from building to analyzing to presenting with less data preparation. Further, all Power BI users have access to plenty of free learning opportunities that enable them to rapidly start building reports and dashboards.

Cognos, on the other hand, has a more challenging learning curve, but IBM has been working on this, particularly with recent user interface updates, guided UI for dashboard builds, and assistive AI. The tool’s AI-powered and Watson-backed analytics capabilities in particular lower the barrier of entry to employing advanced data science techniques.

The conclusion: Power BI wins on broad usage by a non-technical audience, whereas IBM has the edge with technical users and continues to improve its stance with less-technical users. Overall, Power BI wins in this category due to generally more favorable user reviews and commentary about ease of use.

Also see: Top AI Software

Best for Advanced Analytics Capabilities: Cognos

Cognos Analytics surpasses Power BI for its variety of in-depth and advanced analytics operations.

Cognos integrates nicely with other IBM solutions, like the IBM Cloud Pak for Data platform, which extends the tool’s already robust data analysis and management features. It also brings together a multitude of data sources as well as an AI Assistant tool that can communicate in plain English, sharing fast recommendations that are easy to understand and implement. Additionally, the platform generates an extensive collection of visualizations. This includes geospatial mapping and dashboards that enable the user to drill down, rise, or move horizontally through visuals that are updated in real time.

Recent updates to Cognos’s analytical capabilities include a display of narrative insights in dashboard visualizations to show meaningful aspects of a chart’s data in natural language, the ability to specify the zoom level for dashboard viewing and horizontal scrolling in visualizations, as well as other visualization improvements.

On the modeling side of Cognos, data modules can be dynamically redirected to different data server connections, schemas, or catalogs at run-time. Further, the Convert and Relink options are available for all types of referenced tables, and better web-based modeling has been added.

However, it’s important to note that Cognos still takes a comparatively rigid, templated approach to visualization, which makes custom configurations difficult or even impossible for certain use cases. Additionally, some users say it takes extensive technical aptitude to do more complex analysis.

Power BI’s strength is out-of-the-box analytics that doesn’t require extensive integration or data science smarts. It regularly adds to its feature set. More recently, it has added new features for embedded analytics that enable users to embed an interactive data exploration and report creation experience in applications such as Dynamics 365 and SharePoint.

For modeling, Microsoft has added two new statistical DAX functions, making it possible to simultaneously filter more than one table in a remote source group. It also offers an Optimize ribbon in Power BI Desktop to streamline the process of authoring reports (especially in DirectQuery mode) and more conveniently launch Performance Analyzer to analyze queries and generate report visuals. And while Copilot is still in preview at this time, this tool shows promise for advancing the platform’s advanced analytics capabilities without negatively impacting its ease of use.

In summary, Power BI is good at crunching and analyzing real-time data and continues to grow its capabilities, but Cognos Analytics maintains its edge, especially because Cognos can conduct far deeper analytics explorations on larger amounts of data without as many reported performance issues.

Also see: Data Analytics Trends

Best for Cloud Users: Power BI; Best for On-Prem Users: Cognos

Both platforms offer cloud and on-premises options for users, but each one has a clear niche: Power BI is most successful on the cloud, while Cognos has its roots in on-prem setups.

Power BI has a fully functional SaaS version running in Azure as well as an on-premises version in the form of Power BI Report Server. Power BI Desktop is also offered for free as a standalone personal analysis tool.

Although Power BI does offer on-prem capabilities, power users who are engaged in complex analysis of multiple on-premises data sources typically still need to download Power BI Desktop in addition to working with Power BI Report Server. The on-premises product is incredibly limited when it comes to dashboards, streaming analytics, natural language, and alerting.

Cognos also offers both cloud and on-premises versions, with on-demand, hosted, and flexible on-premises deployment options that support reporting, dashboarding, visualizations, alters and monitoring, AI, and security and user management, regardless of which deployment you choose. However, Cognos’ DNA is rooted in on-prem, so it lags behind Microsoft on cloud-based bells and whistles.

Therefore, Microsoft gets the nod for cloud analytics, and Cognos for on-prem, but both are capable of operating in either format.

Also see: Top Data Visualization Tools

Best for Integrations: It Depends

Both Cognos Analytics and Power BI offer a range of helpful data storage, SaaS, and operational tool integrations that users find helpful. Ultimately, neither tool wins this category because they each have different strengths here.

Microsoft offers an extensive array of integration options natively, as well as APIs and partnerships that help to make Power BI more extensible. Power BI is tightly embedded into much of the Microsoft ecosystem, which makes it ideally suited for current Azure, Dynamics, Microsoft 365, and other Microsoft customers. However, the company is facing some challenges when it comes to integrations beyond this ecosystem, and some user reviews have reflected frustrations with that challenge.

IBM Cognos connects to a large number of data sources, including spreadsheets. It is well integrated into several parts of the vast IBM portfolio. It integrates nicely, for example, with the IBM Cloud Pak for Data platform and more recently has added integration with Jupyter notebooks. This means users can create and upload notebooks into Cognos Analytics and work with Cognos Analytics data in a notebook using Python scripts. The platform also comes with useful third-party integrations and connectors for tools like Slack, which help to extend the tool’s collaborative usage capabilities.

This category is all about which platform and IT ecosystem you live within, so it’s hard to say which tool offers the best integration options for your needs. Those invested in Microsoft will enjoy tight integration within that sphere if they select Power BI. Similarly, those who are committed to all things IBM will enjoy the many ways IBM’s diverse product and service set fit with Cognos.

Also see: Digital Transformation Guide: Definition, Types & Strategy

Best for Pricing: Power BI

While Cognos Analytics offers some lower-level tool features at a low price point, Power BI offers more comprehensive and affordable entry-level packages to its users.

Microsoft is very good at keeping prices low as a tactic for growing market share. It offers a lot of features at a relatively low price. Power BI Pro, for example, costs approximately $10 per user per month, while the Premium plan is $20 per user per month. Free, somewhat limited versions of the platform are also available via Power BI Desktop and free Power BI accounts in Microsoft Fabric.

The bottom line for any rival is that it is hard to compete with Microsoft Power BI on price, especially because many of its most advanced features — including automated ML capabilities and AI-powered services — are available in affordable plan options.

IBM Cognos Analytics, on the other hand, has a reputation for being expensive. It is hard for IBM to compete with Power BI on price alone.

IBM Cognos Analytics pricing starts at $10 per user per month for on-demand cloud access and $5 per user per month for limited mobile user access to visuals and alerts on the cloud-hosted or client-hosted versions. For users who want more than viewer access and the most basic of capabilities, pricing can be anywhere from $40 to $450 per user per month.

Because of the major differences in what each product offers in its affordable plans, Microsoft wins on pricing.

Also see: Data Mining Techniques

Why Shouldn’t You Use Cognos or Power BI?

While both data and BI platforms offer extensive capabilities and useful features to users, it’s possible that these tools won’t meet your particular needs or align with industry-specific use cases in your field. If any of the following points are true for your business, you may want to consider an alternative to Cognos or Power BI:

Who Shouldn’t Use Cognos

The following types of users and companies should consider alternatives to Cognos Analytics:

• Users or companies with smaller budgets or who want a straightforward, single pricing package; Cognos tends to have up-charges and add-ons that are only available at an additional cost.
• Users who require extensive customization capabilities, particularly for data visualizations, dashboards, and data exploration.
• Users who want a more advanced cloud deployment option.
• Users who have limited experience with BI and data analytics technology; this tool has a higher learning curve than many of its competitors and limited templates for getting started.
• Users who are already well established with another vendor ecosystem, like Microsoft or Google.

Who Shouldn’t Use Power BI

The following types of users and companies should consider alternatives to Power BI:

• Users who prefer to do their work online rather than on a mobile device; certain features are buggy outside of the mobile interface.
• Users who are not already well acquainted and integrated with the Microsoft ecosystem may face a steep learning curve.
• Users who prefer to manage their data in data warehouses rather than spreadsheets; while data warehouse and data lake integrations are available, including for Microsoft’s OneLake, many users run into issues with data quality in Excel.
• Users who prefer a more modern UI that updates in real time.
• Users who primarily use Macs and Apple products; some users have reported bugs when attempting to use Power BI Desktop on these devices.

Also see: Best Data Analytics Tools

If Cognos or Power BI Isn’t Ideal for You, Check Out These Alternatives

While Cognos and Power BI offer extensive features that will meet the needs of many BI teams and projects, they may not be the best fit for your particular use case. The following alternatives may prove a better fit:

Domo

Domo puts data to work for everyone so they can extend their data’s impact on the business. Underpinned by a secure data foundation, the platform’s cloud-native data experience makes data visible and actionable with user-friendly dashboards and apps. Domo is highly praised for its ability to help companies optimize critical business processes at scale and quickly.

Yellowfin

Yellowfin is a leading embedded analytics platform that offers intuitive self-service BI options. It is particularly successful at accelerating data discovery. Additionally, the platform allows anyone, from an experienced data analyst to a non-technical business user, to create reports in a governed way.

Wyn Enterprise

Wyn Enterprise offers a scalable embedded business intelligence platform without hidden costs. It provides BI reporting, interactive dashboards, alerts and notifications, localization, multitenancy, and white-labeling in a variety of internal and commercial apps. Built for self-service BI, Wyn offers extensive visual data exploration capabilities, creating a data-driven mindset for the everyday user. Wyn’s scalable, server-based licensing model allows room for your business to grow without user fees or limits on data size.

Zoho Analytics

Zoho Analytics is a top BI and data analytics platform that works particularly well for users who want self-service capabilities for data visualizations, reporting, and dashboarding. The platform is designed to work with a wide range of data formats and sources, and most significantly, it is well integrated with a Zoho software suite that includes tools for sales and marketing, HR, security and IT management, project management, and finance.

Sigma

Sigma is a cloud-native analytics platform that delivers real-time insights, interactive dashboards, and reports, so you can make data-driven decisions on the fly. With Sigma’s intuitive interface, you don’t need to be a data expert to dive into your data, as no coding or SQL is required to use this tool. Sigma has also recently brought forth Sigma AI features for early access preview.

Review Methodology

The two products in this comparison guide were assessed through a combination of reading product materials on vendor sites, watching demo videos and explanations, reviewing customer reviews across key metrics, and directly comparing each product’s core features through a comparison graph.

Below, you will see four key review categories that we focused on in our research. The percentages used for each of these categories represent the weight of the categorical score for each product.

User experience – 30%

Our review placed a heavy emphasis on user experience, considering both ease of use and implementation as well as the maturity and reliability of product features. We looked for features like AI assistance and low-code/no-code capabilities that lessened the learning curve, as well as learning materials, tutorials, and consistent customer support resources. Additionally, we paid attention to user reviews that commented on the product’s reliability and any issues with bugs, processing times, product crashes, or other performance issues.

Advanced analytics and scalability – 30%

To truly do business intelligence well, especially for modern data analytics requirements, BI tools need to offer advanced capabilities that scale well. For this review, we emphasized AI-driven insights, visuals that are configurable and updated in real time, shareable and collaborative reports and dashboards, and comprehensive features for data preparation, data modeling, and data explainability. As far as scalability goes, we not only looked at the quality of each of these tools but also assessed how well they perform and process data on larger-scale operations. We particularly highlighted any user reviews that mentioned performance lag times or other issues when processing large amounts of data.

Integrations and platform flexibility – 20%

Because these platforms need to be well integrated into a business’s data sources and most-used business applications to be useful, our assessment also paid attention to how integrable and flexible each platform was for different use cases. We considered not only how each tool integrates with other tools from the same vendor but also which data sources, collaboration and communication applications, and other third-party tools are easy to integrate with native integrations and connectors. We also considered the quality of each tool’s APIs and other custom opportunities for integration, configuration, and extensibility.

Affordability – 20%

While affordability is not the be-all-end-all when it comes to BI tools, it’s important to many users that they find a tool that balances an accessible price point with a robust feature set. That’s why we also looked at each tool’s affordability, focusing on entry price points, what key features are and are not included in lower-tier pricing packages, and the jumps in pricing that occur as you switch from tier to tier. We also considered the cost of any additional add-ons that users might need, as well as the potential cost of partnering with a third-party expert to implement the software successfully.

Bottom Line: Cognos vs. Power BI

Microsoft is committed to investing heavily in Power BI and enhancing its integrations across other Microsoft platforms and a growing number of third-party solutions. Any organization that is a heavy user of Office 365, Teams, Dynamics, and/or Azure will find it hard to resist the advantages of deploying Power BI.

And those advantages are only going to increase. On the AI front, for example, the company boasts around 100,000 customers using Power BI’s AI services. It is also putting effort into expanding its AI capabilities, with the generative AI-driven Copilot now in preview for Power BI users. For users with an eye on their budget who don’t want to compromise on advanced analytics and BI features, Power BI is an excellent option.

But IBM isn’t called Big Blue for nothing. It boasts a massive sales and services team and global reach into large enterprise markets. It has also vastly expanded its platform’s AI capabilities, making it a strong tool for democratized data analytics and advanced analytics tasks across the board.

Where Cognos Analytics has its most distinct advantage is at the high end of the market. Microsoft offers most of the features that small, midsize, and larger enterprises need for analytics. However, at the very high end of the analytics market, and in corporate environments with hefty governance and reporting requirements or legacy and on-premises tooling, Cognos has carved out a strategic niche that it serves well.

Ultimately, either tool could work for your organization, depending on your budget, requirements, and previous BI tooling experience. The most important step you can take is to speak directly with representatives from each of these vendors, demo these tools, and determine which product includes the most advantageous capabilities for your team.

Read next: 10 Best Machine Learning Platforms

The post Cognos vs. Power BI: 2024 Data Platform Comparison appeared first on eWEEK.