The next SMB Editor for Data Analytics and AI
Managing obsolescence in traditional Business Intelligence and identifying the next editor for Data Analytics and AI is increasingly complex.
It is a significant challenge to simultaneously manage 1) Moving to the cloud, 2) Keeping up-to-date Analytics, and 3) Being ready for AI and ML.
Gartner has created three quadrants for evaluating vendors in the following areas:
When trying to help Small and Medium Businesses aiming for top Data & Analytics, it is challenging to use several tools to manage ABI, DSML, and Cloud DBMS. The cost, complexity and ability to execute when using several tools is vastly impacted.
Looking at the must-have, standard, and optional capabilities from the Gartner report in each quadrant is a good way to understand the scope of the evaluations.
I represented the tools we usually use or see with our clients and their classification by Gartner.
Company choices will factor in other parameters, such as current Hyperscaler or existing reporting tools and needs; nevertheless, the above table is a good starting point!
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A word of conclusion
Microsoft is Gartner's big favorite in those three categories combined due to its integration into an existing ecosystem, the efficiency of its licensing, and its ability to execute with excellent tools such as PowerBI, One Lake, Copilote, Fabric, Azure ML, and more.
Google would be shortly second if it weren't for ABI.
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