Making CRISP-DM Work for Embedded Analytics

Embedded analytics is key for companies aiming to become data driven. Gartner defines embedded analytics as “a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application” . In other words, analytics are hidden in the business processes and within existing applications. A bank advisor sees which clients to contact in her advisory tool for specific product offerings. She does not have to bother and start another application to see this list. Similar, customers seen directly in web-shops product suggestions such as “customers who buy A, buy B”. They do not have to switch to a different app or website for getting shopping suggestions. Embedded analytics are a great investment for both customers and business users. It is also a way for data scientists to become essential for the organization – if they adapt their collaboration model.

You can read the full article how data scientists can adapt CRISP-DM to work for embedded analytics as published by the TDNA.com here. If you prefer a pdf version, you can download this as well from my homepage here.