ThoughtSpot defines shape of the modern data stack

We are now being sold so-called ‘modern cloud’ systems, modern application platforms, modern approaches to AI and modern data and modern data analytics - so what makes data analytics modern and what ingredients go into this new mix?

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Data is modern. In a sense of course, it’s not i.e. data has been around since people were carving notches into rocks and caves to create some kind of historical record or note. But when we talk about data today we are obviously talking about digitally created information assets that we use in contemporary IT systems.

It’s important to note this basic truism because the data business (as a subset trade inside the IT industry at large) is always ripe for reinvention. Just as companies are now talking about so-called ‘modern cloud’ systems (quite what old fashioned cloud was nobody seems to know), we are also hearing vendors lay claims to modern application platforms, modern approaches to AI and, perhaps most over-arching of all,  modern data and modern data analytics.

What is modern data analytics?

Modern data analytics is all about ease-of-use and ubiquity of access. This is data analytics built by data analytics engineers, but designed to be used by almost anyone in the business, often through the use of natural language search functions.

Cloud data analytics firm ThoughtSpot CEO Sudheesh Nair explains the modern age of analytics as a progression point onwards from the way we did things before the turn of the century. This was a time when enterprises started with their database (Oracle, SAP, IBM or other), then moved copies of data that they needed to analyse to a specialised analytics service (Alteryx is one example, but there are many others) and then presented that analytics to business managers in a visualisation dashboard (Tableau and Qlik are obvious examples, but again there are others).

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