Ten Mistakes to Avoid
The Ten Mistakes to Avoid series, published quarterly, addresses the 10 most common mistakes managers and teams make—from data modeling to building an operational data store—and gives you inside knowledge on how to avoid these common pitfalls. Ten Mistakes to Avoid is exclusively for TDWI Premium Members.
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August 18, 2014
By Mark Giesbrecht
Presented in this issue are the 10 mistakes to avoid as you take your agile BI practice to the next level.
May 12, 2014
By Fern Halper
This Ten Mistakes to Avoid covers what works and doesn’t work when it comes to big data analytics projects.
February 18, 2014
By Lyndsay Wise
This Ten Mistakes to Avoid addresses how to overcome communication gaps and use successful collaboration to help ensure successful BI implementations.
November 12, 2013
By Mark Madsen
Data strategy focuses on how data can be used as a resource to further the goals of a business strategy. This means building capabilities: treating data as an asset, organizing to make better use of it, and building the necessary management and technology infrastructure. There are many ways to build capabilities. Choices impose constraints and trade-offs, which are the essence of crafting a set of policies, procedures, and plans that make up a data strategy. This Ten Mistakes to Avoid focuses on many common mistakes we make when crafting a data strategy.
August 19, 2013
By Laura Reeves
The most successful BI solutions are those whose design and subsequent use are driven by the business itself. This is much easier said than done. Too often, what is delivered is not well received by the business community, or worse, met with disappointment or resistance. The most common mistakes, and tips for avoiding them, are explained here.
May 13, 2013
By Ken Collier, Ph.D.
In my work with dozens of BI teams attempting to “go agile,” I’ve
seen lots of mistakes. This Ten Mistakes to Avoid outlines the
most common and recurring errors to help you avoid repeating the
mistakes of others.
February 19, 2013
By Krish Krishnan
In this Ten Mistakes to Avoid, we will look at the most common mistakes that occur when implementing a big data program to help you enhance your analytical insights and the decision support processes in your enterprise.