Why the 2021 Gartner's Critical Capabilities for Analytics and Business Intelligence Platforms is a must-read 

May 27, 2021 | 5 minute read
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Everyone knows about the 2021 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms research. But few know that its companion piece — Critical Capabilities for Analytics and Business Intelligence Platforms — is truly critical, as it appraises each Magic Quadrant vendor’s product portfolio by 12 “critical capabilities.” 
Buyers usually evaluate a product based on what it does and how well it does it.  At the end of the day, little else matters. But as technology changes and analytics shift from visual data to augmented, platforms need to shift as well in order to continue to satisfy these basic consumer customer needs. The 12 critical capabilities laid out in this report offer a comprehensive set of benchmark functionalities that every Analytics and BI (ABI) platform should have.       

They include:       
●    Security: This includes administering users and auditing platform access and authentication. 
●    Manageability: Tracking usage and how information is shared and promoted. 
●    Cloud-Enabled Analytics: Supporting building, deploying, and managing analytics and applications in the cloud, based on data both in the cloud, on-premises, and across multi-cloud. 
●    Data- Source Connectivity: Enabling users to connect to and ingest data contained in various types of storage platforms, both on-premises and in the cloud.
●    Data Preparation: Supporting combinations of data from a variety of sources, as well as the creation of analytic models.     
●    Catalogs: Making it easy to find and consume analytic content via search and recommendations. 
●    Automated Insights: Ensuring the ability to apply machine-learning techniques to automatically generate insights for end-users.
●    Data Visualization: Supporting highly interactive dashboards and the exploration of data through the manipulation of chart images.
●    Natural Language Query: Enabling users to ask questions of the data using terms that are either typed into a search box or spoken.      
●    Data Storytelling: Combining interactive visualizations with narrative techniques in order to package and deliver insights. 
●    Natural Language Generation: Automatically creating linguistically rich descriptions of insights found in data.      
●    Reporting: Providing pixel-perfect, paginated reports that can be scheduled and burst to large user communities.       

No two use cases are the same, so each evaluator will prioritize certain capabilities over others. That’s fine. The list is not a recipe to follow; it is a toolbox from which you can build your own success. And Gartner helps you get started on selecting which tools to utilize by providing four different high-level use cases with different weightings (which you can customize online if you’re a subscriber):      

The report gives you the weightings for each use case and the respective scores for each vendor. The importance of each depends on your situation. General Analytics and Augmented Analytics reflect the most important and widely applicable capabilities across companies, industries, and regions, and all deserve a look.

General Analytics is the most utilitarian, with capabilities for centralized control and decentralized empowerment clocking in at the same value.
For those focused on data visualization and data preparation, Visual Self-Service Analytics has the highest weights. Those focused on manageability, catalogs, reporting, and security will want to look at Enterprise Analytics, while Augmented Analytics has the highest weights assigned to Automated Insights, Natural Language Query, Data Storytelling, and Natural Language Generation.                    

Oracle Recognized as #1 in General Analytics

Oracle Analytics received the highest overall score for the General Analytics use case. We believe that any analytics platform must blend governed analysis and reporting with self-service business-user-driven data discovery. Existing reporting and analysis requirements don’t disappear; they expand to include more people, more data, and more insights.  As such, augmented analytics — the ability to employ machine learning and AI to uncover insights, ask questions of the data in your own language, tell more compelling stories and generate narratives to explain what’s happening in your business — propel the next wave of innovation. They expand the community of people in an organization who can actually interact with data, rather than simply receiving results on a static scheduled basis. This is why Oracle Analytics tops the vendor evaluation in this category.  The product does it all.      

As more organizations also consider a move to modernize their ABI platforms in the Cloud, pay special attention to Oracle’s individual capability score for Cloud-Enabled Analytics.  Cloud is becoming a top priority. Whether you’re ready for cloud (or not), Oracle Analytics has a solution that suits your needs now… and into the future. 

Use the Critical Capabilities report for your use case

Looking at the report, you’ll probably notice something else: being a visionary in the Magic Quadrant does not always transfer to the highest scores in use cases. That’s what makes this secondary report so valuable. It sheds light on what an ABI platform should do, and how well each vendor performs.      

I hope you take the time to read this important research note from Gartner. Digging into the next level of detail to understand the strengths and cautions of each product and provides you with more data points. And it is data — and the insights that data brings — that will help you make the right decision for your organization. 
Any questions, please feel free to reach out to me at john.hagerty@oracle.com. Happy reading! 
To get information about our solutions, go to Oracle.com/analytics, and follow us on Twitter@OracleAnalytics 


Source: Critical Capabilities for Analytics and Business Intelligence Platforms , Kurt Schlegel ,  James Richardson ,  Rita Sallam ,  Austin Kronz ,  Julian Sun, 15 March 2021 

Gartner Disclaimer
Gartner does not endorse any vendor, product, or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

The graphics (above) were published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Oracle.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.


John Hagerty

A veteran of nearly 30 years in the business intelligence and analytics market, John is part of the outbound product management team for Oracle Analytics. A former business user and industry analyst, he works with customers, prospects, and industry influencers on anything analytics.

Connect with John on LinkedIn.

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