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Analytical tools should be able to support today’s current needs, while accommodating future growth. To gain powerful business intelligence, organizations need tools to offer a lot more functionality. Defining the parts of the job is not the same as defining the whole job While Tableau and MicroStrategy are working to broaden their capabilities, we can see an example of the integrated approach in platforms like Looker, which aim to provide the UI and governance needed for near real-time, self-service data discovery that both analysts and business teams can access together. MicroStrategy primarily focuses on governance, maintenance, and scalability, yet it lacks the flexibility to respond to changing business needs and data sources. Tableau provides end-users with the raw beauty of data visualizations and ease of use in making them, but lacks support for data governance, collaboration, and multiplatform accessibility. There is no question the years of development that have gone into their approaches have paid off. We can look at the examples of Tableau and MicroStrategy for their exceptional support in their specific arenas-accessibility or data governance, respectively-but not for both elements. And even small hurdles to using the best tool can nudge people to using an inferior one. People, however, specialize and develop habits, too. This would be perfect, if humans were perfect.

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Get a free trial today and find answers on the fly, or master something new and useful. Join the O'Reilly online learning platform. The past decade or so have seen the development of powerful tools that handle specific needs extremely well, so the “modern” data stack consists of a jigsaw puzzle of purpose-built tools, each of which does its own piece extremely well. Establishing broad access and a governance structure that creates a “single source of truth” allowing effective cross-team communication, and healthy competition in analysis (disagreement about what the numbers mean, which can be resolved with experiment, is much better than disagreement about what the numbers are) builds the foundation of a data-driven business.īut there is another, more hidden, type of siloization to worry about as well: the “siloization” of data analytics tools.

Much has been made of the importance of “tearing down silos”-giving everyone in the organization broad access to data.

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