Gartner 2021 Magic Quadrant For Analytics As Well As Business Intelligence Systems

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Gartner 2021 Magic Quadrant For Analytics As Well As Business Intelligence Systems – For more than 10 years, Gartner has published its popular Magic Quadrant for Analytics and Business Intelligence platforms, and 2023 is no exception. Over the years, both Salesforce Tableau and Microsoft Power BI have demonstrated consistent performance and strong capabilities in the Leaders Quadrant. Tableau has always had a high score and Microsoft has done a great job positioning itself ahead of Tableau. Not only the result of fast development cycles and regular addition of new features, but also by redefining the benchmarks based on these annual Magic Quadrants.

Below, I review Gartner’s market definition and overview, key platform capabilities, evaluation criteria, and summarize the strengths and caveats of the following vendors:

Gartner 2021 Magic Quadrant For Analytics As Well As Business Intelligence Systems

Get a full copy of the Gartner Reprint via the Tableau page: You must register to access the report.

Gartner’s Mqs And G2 Grids ’21 Highlights Of Analytics & Business Intelligence (abi) And Data Science

Analytics and Business Intelligence (ABI) platforms enable less technical users, including business people, to model, analyze, explore, share and manage data, and collaborate and share findings enhanced by IT and artificial intelligence (AI).

The availability of major cloud ERP and CRM application providers also influences ABI platform selection. On the one hand, cloud resources raise inevitable concerns about the lock-in and unexpected costs of a portfolio of data and analytics. On the other hand, cloud service providers are embracing the importance of openness in their software stacks and the growing importance of “multi-cloud” approaches, which has resulted in organizations relying on multiple cloud offerings such as Databricks and Snowflake and ylab launches applications.

As expected, especially in the Netherlands, one vendor – Microsoft – dominates the market in terms of user adoption. The great growth of Microsoft Power BI continued, which was mainly ensured by the integration of this product with Office 365 (at the E5 license level) at a greatly reduced price and ease of installation through the Windows Store. However, similar to platform openness and portability, these should not be the only considerations when choosing an ABI platform, as the strengths and weaknesses of selected vendors are outlined below.

According to Gartner, ABI’s platform functionality includes the following 12 key capabilities that have been updated to reflect market change, differentiation and areas of customer demand:

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Three critical capabilities were removed from Gartner’s evaluation criteria: security, natural language generation (NLG; data storytelling), and cloud analytics (henceforth a go-to-market strategy). And one of the sub-criteria of security, the accuracy of authorization (such as string-based security) has been transferred to enterprise reporting capabilities.

Tableau’s products are primarily focused on visual-based search, enabling business users to access, prepare, analyze, and present findings from their data. CRM Analytics, formerly Tableau CRM, provides advanced analytics capabilities for analysts and citizen data scientists. In 2022, Tableau leverages enhanced consumer insights to deliver contextualized insights while integrating deeper with Salesforce Data Cloud.

Microsoft’s core ABI platform has massive market penetration and speed through Power BI, Microsoft 365, Azure and Teams integrations, flexible pricing, above-average functionality and a huge product roadmap.

Google Cloud’s Looker is a cloud-architected ABI platform that offers highly managed analytics, including self-service visualizations and dashboards, and a code-first semantic modeling layer based on LookML. Looker’s developer-focused analytics platform provides a version-controlled, collaborative framework for building internal BI and enabling customers to build applications.

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SAP Analytics Cloud is a multi-tenant cloud platform with an extensive set of capabilities for data visualization, reporting and advanced analytics. It combines analytics and enterprise planning to build end-to-end processes from concepts to business actions. Analytical applications’ low-code and advanced coding capabilities offer scalable analytic applications for lines of business. This has enhanced data integration and modeling capabilities, especially when leveraging the full context of SAP’s data and application ecosystems.

Qlik’s core product is Qlik Sense Enterprise SaaS, which includes Qlik Sense, Qlik AutoML, and Qlik Application Automation. Qlik is a cloud-agnostic vendor with top-tier partnerships with all three major cloud service providers (AWS, Microsoft, and Google), as well as Databricks and Snowflake. For the uninitiated, Gartner’s Magic Quadrants are market research reports. Published by IT consulting firm Gartner. They use qualitative research to rank and evaluate technology vendors and help buyers understand the competitive environment.

First, a short disclaimer. We are not in the Gartner Magic Quadrant. One day we will be there and look forward to moving from the players corner to the “leaders”. At the same time, we love these reports because they are a great benchmark for the analytics and business intelligence industry.

As we read this year’s Magic Quadrant report, we thought we’d share our thoughts and offer four insights…

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You can turn on a podcast or read a tweet without hearing the phrase “data-driven decision making.” While COVID has undeniably accelerated companies’ digital transformation efforts (well, digitization and the digital workplace…), they now want to put the power of data in everyone’s hands. We love, love, love it. Enterprise-wide ease of use based on embedded, advanced analytics is absolutely the goal. It’s a world where people use BI without even knowing they’re using it.

But (this is a big BUT) this is definitely a look into the future. We’re doing some work in this area right now, but the nirvana of voice-activated sophisticated BI queries is a long way off. Although we can use “Hey Siri! For customers with more than 15% revenue growth, what is the percentage change in the top 30% product grouping market share for the current six-month period compared to the same period last year? holding our breath.

The truth is, we need people to create dashboards and reports. And, of course, you’ll need SQL expertise, complete with layers of data modeling, to help make the magic happen behind the scenes.

We found that nearly all of the seven largest cloud infrastructure and platform service vendors have an analytics/business intelligence offering. This is not surprising, as the inevitable clouding of data and software continues. Locked-in technology buyers are still looking for alternatives, preferring hybrid or multi-cloud providers. And research shows that two-thirds of CIOs prefer to use cloud services from multiple vendors.

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While COVID has accelerated the move to the cloud, there will be on-premises requirements for some time. Most companies, especially in the healthcare and financial services industries, store a lot of local data.

In this context, there is a need in the market for cloud-agnostic business intelligence platforms. Customers never need to move data. Ideally, a BI platform should support on-premise, cloud and migration.

For another year, there is light between Microsoft Power BI and other BI vendors in terms of user adoption. With Office 365’s 40 percent market share and more than 200 million monthly active users, we bow to the 80,000-pound gorilla of our industry.

But, taking us aside for a moment, it’s important to note that Power BI can only be installed on Azure. This limits your ability to use the services of other cloud providers and may also result in higher switching costs.

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If Power BI users need more than a simple dashboard, analysts are required to learn a complex language called DAX, which requires significant training. Alternatively, the SQL-based data modeling layer allows you to create visual data models without learning a new language.

Once you’ve defined your data models, business users can explore the data independently, create dashboards, trust visualizations, and easily filter them in real-time.

Gartner talks about a “…collision course…” where the ABI, data science, and ML platform markets will collide like asteroids between Mars and Jupiter. That was the genesis of a crash course (see our stories here), but that’s a tale for another time.

Given the increasingly widespread BI needs, the sheer volume of data, and the complexity of connecting countless data sources, the expansion of AI-powered analytics is inevitable. The opportunity to remove bias from pre-existing data, as well as help non-technical users gain real insights, is very attractive.

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Even as asteroids accelerate, it will be critical to consider how to build confidence in the exit. Ensuring that “augmented” is not replaced by “artificial” will be important as companies begin to rely on machine-generated insights. Also, it will never be 100 percent automated. There will continue to be hard-working BI and data analysts writing SQL queries in the engine room.

This is our quick take on Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms. right? Don’t you agree? Do you have other ideas? Let us know on LinkedIn or Twitter. Microsoft remains “up and to the right” in Gartner’s new Magic Quadrant for Analytics and Business Intelligence platforms, while major competitors have actually moved down and to the left. We spoke with Amir Netz, the “father” of Microsoft’s Power BI, to learn about his product’s success.

The new Gartner Magic Quadrant for Analytics and Business Intelligence (BI) is out, and Microsoft is back in the “Leaders” quadrant (see image above). In fact, according to Microsoft, that’s 14 years as a BI leader. Although Microsoft is in virtual

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