The rise of modern business intelligence (BI) has seen the emergence of a number of component parts designed to support the different analytical functions necessary to deliver what enterprises require.
Perhaps the most fundamental component of the BI movement is the traditional frontend or visualization application. Companies like Tableau, Qlik, Birst, Domo and Periscope provide these. There are dozens more — all with essentially equivalent capabilities: the ability to make spreadsheets look beautiful. Some of these companies have been tremendously successful, primarily differentiating themselves on the axis of usability.
Another, equally critical component of the BI equation is the database. Here, too, there are the usual suspects: Redshift, Impala, Vertica, Netezza and others. Some of these databases are fully featured, system-of-record worthy solutions, while others focus on a particular performance axis, streaming, for instance, and do it well.
Finally, there is the emergence, across BI and database players, more advanced analytics tools, driven by the explosion of interest in and development of machine learning, deep learning and artificial intelligence. This market has its stars, starting with the big boys — Google, Facebook, Amazon, Microsoft, IBM, Baidu, Tesla — as well as a host of highly credentialed startups, like Sentient, Ayasdi, Bonsai and H2O.ai.
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