We quickly run through three major data evolutions and the impact on analytics architectures and business expectations


The Modern Data Evolution


7 Requirements for Business-Driven Analytics

We discuss in detail seven requirements for modern analytics platforms and why they are needed



We summarize the gaps we see and why analytics platforms need to "catch up" so they can fully complement to modern data architectures

About the Author
Kim has been around data for over 20 years.  Her primary roles have involved integrating data for analytics or operational use across enterprise systems.  Before joining Knowi, Kim was at Informatica where she led product marketing for B2B Data Exchange and Data Integration Hub product lines.  She also has managed cloud integration and B2B e-commerce operational systems for McKesson and Axway.

Kim Loughead
VP Product Marketing, Knowi

Copyright 2017 Knowi


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Business-Driven Analytics in the Modern Data Age

A Best Practices Guide

About this paper

While other technologies advanced to optimize processing of unstructured data, traditional BI analytics tools require moving, flattening and aggregating unstructured data so it can be loaded into relational tables.  We discuss why this is not a sustainable approach as more organizations shift from IT-driven to business-driven analytics as well as 6 other key capabilities to think about as you modernize your analytics platform.

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