News

News

• November 23, 2016 23 Nov'16

  Business should work with IT to get self-service BI governance right

  Self-service analytics is all about getting IT roadblocks out of the way of the business, but traditional tech teams can still play a useful role in defining and implementing BI data governance best practices.

• November 18, 2016 18 Nov'16

  Data visualization plays an important role in a big data environment

  Enterprises are increasingly putting data visualization tools, like Tableau, at the top of their big data platforms to start making sense out of complex data.

• November 17, 2016 17 Nov'16

  How predictive modeling and forecasting failed to pick election winner

  Nearly all predictive modeling algorithms were way off in picking the winner of the presidential election. What went wrong can strike any predictive analytics project if data scientists and other analysts aren't careful.

• November 16, 2016 16 Nov'16

  Don't let bad data dashboard design crash your reports

  Data dashboard design best practices aren't just about making sure reports look good. They're also closely tied to ensuring dashboards function properly.

• November 14, 2016 14 Nov'16

  Tableau data visualization software to embrace machine learning

  Tableau's BI and data visualization tools have primarily been synonymous with basic analytics, but the company is moving to incorporate more advanced analytics capabilities with deeper functionality.

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• November 01, 2016 01 Nov'16

  Cognitive computing applications present new business challenges

  When implementing cognitive software, enterprises need to worry just as much -- if not more -- about the business implications, rather than the technical challenges.

• October 27, 2016 27 Oct'16

  Users still kicking the tires on IBM's cognitive applications

  There's a huge amount of excitement around IBM's cognitive computing tools, but users are still looking for ways to implement them in their businesses.

• October 25, 2016 25 Oct'16

  Pentaho 7.0 update combines data preparation tool with analytics

  Users increasingly want data preparation to be tightly integrated into the analytics process to shorten time to insight, and Pentaho's new 7.0 software release aims to satisfy that need.

• October 13, 2016 13 Oct'16

  IoT data analytics streams into uncharted waters

  In the world of the internet of things, it's one thing to gather mountains of data from an ever-increasing multitude of sensors, appliances, vehicles, smart personal devices and industrial equipment. It's quite another thing to liberate congested ...

• October 06, 2016 06 Oct'16

  Sports data analytics isn't always a slam dunk

  The growing trend of analytics in sports has caused much debate, and even though data-driven decisions can provide some benefits, they're not right for all occasions.

• October 06, 2016 06 Oct'16

  Visualized data aids in building, updating predictive models

  Data scientists at Capital One and BuildingIQ use data visualizations to help guide their efforts in developing, training and modifying predictive models for use in advanced analytics applications.

• September 30, 2016 30 Sep'16

  Users look to real-time streaming to speed up big data analytics

  Real-time data processing and analytics technologies are helping companies find useful information in streams of big data so they can quickly take actions to boost their business operations.

• September 30, 2016 30 Sep'16

  Tableau brings big updates to its popular data visualization tool

  As part of its Tableau 10 release, Tableau has added several new features to the self-service BI and data visualization software in an effort to improve data preparation and deepen analysis.

• September 28, 2016 28 Sep'16

  Advanced analytics tools must align with business needs

  Advanced analytics teams may sometimes be inclined to more academic projects, but the path to true value is ensuring that their work closely aligns with core business needs.

• September 23, 2016 23 Sep'16

  Get your analytics architecture right to support scalable tools

  Analytics teams might prefer to spend their time developing algorithms, but overlooking the importance of analytics infrastructure could cause problems down the road.