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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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Ten Mistakes Q117 cover

Ten Mistakes to Avoid in Building Out a Data Science Program

January 31, 2017

 

By Fern Halper and Martin Pacino

Organizations are moving past traditional structured data and are embracing text data from emails, machine-generated data, and streaming data to enhance their analyses. Data science is an outgrowth of this of this evolution, but many companies are still in the early stages of their data science efforts. In this Ten Mistakes to Avoid, TDWI’s Fern Halper and Martin Pacino identify the mistakes most detrimental to building out a successful data science program.


Ten Mistakes to Avoid When Defining an Enterprise BI and Analytics Strategy

November 3, 2016

 

By Nancy Williams and Steve Williams

The benefits of business intelligence—and now big data analytics—may be couched in different business terms, but there has to be a connection to increased profits if there is to be a return on a BI investment. This Ten Mistakes to Avoid examines some of the key, commonly encountered BI strategy challenges faced by major companies across a wide range of industries.


Ten Mistakes to Avoid in Data Storytelling

May 5, 2016

 

By Dave Wells

Data storytelling takes the next step beyond data visualization by connecting multiple visuals with narrative, offering interpretation, and inviting conversation. Crafting a good data story, however, is challenging. This Ten Mistakes to Avoid offers guidance to advance your storytelling skills and increase the impact of your data stories.


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