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Blogs by

Ashish C Morzaria

On behalf of the entire team, it is with great pleasure that we announce the general availability of SAP BusinessObjects Predictive Analytics 3.1!  😀 Existing customers can immediately download the latest version from SAP Service Marketplace.

Imagine what a “typical data scientist” looks like in your mind right now (or think about a real, live one that you already know). (In reality, many types of people do data science work, so

At SAPPHIRE NOW 2016, we took the next step in an exciting transformational journey by announcing SAP BusinessObjects Predictive Analytics 3.0 to the world.   On behalf of the entire team, I am happy to announce

March is an exciting time for people all around the world – for many, it means winter is melting into spring and Easter (along with the requisite holidays, chocolate eggs, and of course bunnies) are

As part of the SAP Predictive Analytics team, I am very proud to announce the immediate availability of  SAP HCP predictive services (HCPps).  Continuing our strategy of “enabling predictive analytics everywhere for everyone”, our Product

In the United States, the cliché “Christmas comes early” is often applied to the American Thanksgiving holiday, which occurs each year on the last Thursday of November.  However in the case of SAP Predictive Analytics,

This is part 2 of the Person of Interest series – you can find part one here: The Predictive Science Behind TV’s “Person of Interest” “You are being watched The government has a secret system

Spoiler Alert: This blog series talks about the TV show Person of Interest but does not aim to give away any “spoilers” – however it is impossible to talk about it without giving away its

Any time a (relatively) specialized or obscure topic gets subjected to worldwide hype and before finally becoming part of the mainstream, there is an interesting phenomena that occurs between those “original believers” and the “newcomers”.  

Predictive Analytics is getting more and more mainstream – the advantages of being able to understand  trends by algorithmically analyzing historical data are so obvious, the question of whether to use predictive is not “Why?”,