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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.


Ten Mistakes to Avoid In Preparing for IoT Analytics

March 7, 2016

 

By Fern Halper and Asim Razvi

The Internet of Things (IoT)—a network of connected devices that can send and receive data over the Internet—is a hot market topic. Although many companies are excited about the possibility of improving operational efficiencies and driving new business models with IoT, this Ten Mistakes to Avoid identifies important factors to consider when getting ready for IoT analytics projects.


Ten Mistakes to Avoid When Deploying Visual BI and Analytics for Business Decisions

November 9, 2015

 

By David Stodder

Data visualization, data discovery, and analytics technologies are rapidly maturing and are becoming easier to use. However, success with these technologies is not as simple as just turning them on. This Ten Mistakes to Avoid identifies important factors in the success or failure of visual BI and analytics deployment and recommends practices for addressing them.


Ten Mistakes to Avoid In Predictive Analytics Efforts

August 5, 2015

 

By Fern Halper

TDWI research indicates that predictive analytics is one of the most popular kinds of advanced analytics. Although many companies are excited about the possibility of utilizing predictive analytics, there are a number of interrelated themes about what not to do when it comes to predictive analytics projects.


Ten Mistakes to Avoid When Growing Your MDM Program

May 11, 2015

 

By Philip Russom

You need a long-term strategy, documented in a governable plan, if MDM is to mature into rich functionality applied over much of your enterprise. This TDWI Ten Mistakes to Avoid booklet drills into the details of such plans.


Ten Mistakes to Avoid in Hadoop Implementations

February 18, 2015

 

By Krish Krishnan

In this Ten Mistakes to Avoid we identify the mistakes with the most negative impact on Hadoop implementations and recommend solutions you can apply to your own environment.


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