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TDWI Upside - Where Data Means Business

Data Digest: Data-Driven Decisions, Data Breaches, Voice Data

Learn a simple strategy for any enterprise to implement data-driven decision making, five steps for preparing for a data breach before it happens, and the implications of recent improvements in voice recognition.

Data Stories: Three Ways to Look at the Data behind Music

Music is math already according to some ways of thinking. It’s only natural that many data visualizations have been created to explore the history or popularity of different genres and artists.

Customer Data Profiling: Persona Disambiguation and Behavioral Analytics (Part 3 of 4)

When multiple customers use one account, it can cause problems for your predictive models. Use behavioral analytics to separate the personas and improve your customer service.

Data Digest: Shadow Data, Data Hoarding, and Different Types of Data Scientists

In today’s articles, read about the dangers of ungoverned access to “shadow data,” the costs of hoarding every bit of data, and tactics for hiring the type of data scientist that matches your needs.

Customer Data Profiling: Problems with Personas (Part 2 of 4)

Even an advanced CRM system can break down when one customer profile is capturing the attributes and behaviors of more than one real individual.

Customer Data Profiling: The Precision Problem (Part 1 of 4)

Over the years, CRM tools have evolved from simple customer databases into increasingly more sophisticated tools for engagement, but the growing amount of customer data brings new challenges.

Improve Your Business by Leading the Transformation to Prescriptive Analytics

Forecasting what's coming is no longer enough. Modern enterprises must use prescriptive analytics to ensure users of all skill sets are able to benefit from a data-driven culture.

Data Digest: Use Cognitive Computing with Big Data, Maintain Your Data Quality, Secure Your Big Data

Learn about trends in cognitive computing that help enterprises manage big data, why you may be struggling with data quality and what to do about it, and 5 best practices in big data security.

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