TDWI Upside - Where Data Means Business

Contributor: William McKnight


McKnight Consulting Group is led by William McKnight. He serves as strategist, lead enterprise information architect, and program manager for sites worldwide utilizing the disciplines of data warehousing, master data management, business intelligence, and big data. Many of his clients have gone public with their success stories. McKnight has published hundreds of articles and white papers and given hundreds of international keynotes and public seminars. His teams’ implementations from both IT and consultant positions have won awards for best practices. William is a former IT VP of a Fortune 50 company and a former engineer of DB2 at IBM, and holds an MBA. He is author of the book Information Management: Strategies for Gaining a Competitive Advantage with Data.

  


All articles by William McKnight


An Introduction to Graph Databases

Graph databases are one of the fastest growing categories in data management, yet they remain an enigma to many. What can these workhorses do for your enterprise?

A Spike Takes the Pressure Off Agile

Transitioning to agile development methods can be easier said than done. One way to facilitate the transition is to schedule "spike" stories for planning and discovery.

Get More Out of Hadoop by Building Your User Community

If you are launching Hadoop in your enterprise, you'll want to get the most out of its rich data. Users across the enterprise have important roles to play in your eventual Hadoop user community.

Running a BI Organization in 2016 (Part 2 of 2)

How your team can determine which BI projects to support and what development is needed.

Running a BI Organization in 2016 (Part 1 of 2)

To improve your service, you must determine whom you actually serve. Creating a charter can help you clarify your responsibilities.

The Best Job in America: Data Scientist

Glassdoor recently released their review of the 25 best jobs for 2016. At the top of the list is the vaunted data scientist. What does it take to be a successful data scientist?

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