Data-Driven Biz

  • Data Science for Everyone

    Statistical models and machine learning algorithms are often mysterious and confusing for average business and data professionals. However, even the most math-adverse can reach some understanding. 02/22/2017

  • Data Digest: Civic Technology, AI Aggression, Defining Data Science

    Data initiatives that increase government transparency, Google experiments with competitive AIs, and the difference between a data scientist and a data analyst. 02/21/2017

  • Desire for Mobile BI Continues to Increase

    Almost three-quarters of users count on mobile access to BI insights, according to a new survey. Supported by improved technology and users' desire for more data access, mobile BI is growing in a big way. 02/21/2017

Tech Talk

  • Avoid the Premature Release of Data Warehouse Software

    Although we may be subject to intense pressure to meet implementation targets, we should make every effort to avoid treating our user community as beta testers or supplying users with inaccurate program prompts or user documentation. 02/15/2017

  • The Rise of Predictive Infrastructure

    Infrastructure speed has reached a plateau. Today's enterprises should be seeking out predictive, automated solutions to improve their enterprise infrastructure. 02/09/2017

Intersection Biz-IT

  • TDWI 2016 Salary Survey: Gender Pay Gap Remains

    According to TDWI research, the gender gap in BI-related fields widened in 2016. There are many reasons why women are earning less than men in these jobs. 02/21/2017

  • AI in the Crosshairs

    At the 2017 World Economic Forum meeting, tech industry leaders openly discussed some of the ethical and societal challenges facing the current surge in big data-driven AI. 02/17/2017

  • Successful Data Lakes: A Growing Trend

    Data lakes have been widely misunderstood, but they are now benefiting from new best practices -- helping organizations gain significant value. 02/16/2017

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Q&A with Jill Dyché

Find out what's keeping teams up at night and get great advice on how to face common problems when it comes to analytic and data programs. From head-scratchers about analytics and data management to organizational issues and culture, we are talking about it all with Q&A with Jill Dyche.

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