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    Tableau Applies Machine Learning Algorithms to Analytics

    The amount of time that passes between when data is collected and actionable intelligence is created keeps getting narrower with each passing day. Tableau Software this week released a version 10.3 update to its data visualization and analytics software that leverages machine learning algorithms to recommend and identify different sets of data that should be joined to generate additional insights.

    Dustin Smith, competitive intelligence manager for Tableau, says that as analytics tools make greater use of these types of algorithms, end users will be less dependent on reports generated by IT departments using traditional data warehouse platforms. Instead, users can now interrogate data at their leisure without an intervention on the part of the IT organization required.

    “IT departments will be getting out of the reports business,” says Smith.

    Other additional capabilities included in version 10.3 include support for six new data sources, including the ability to import tables stored with PDF files. The other five new data sources are Amazon Athena, ServiceNow, MongoDB, Dropbox and Microsoft OneDrive.

    Finally, Tableau has added an alert capability that allows users to monitor changes to key performance metrics.

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    Overall, Smith says end users have already made it clear they want to be able to make informed decisions using the latest data available as quickly as possible. The issue that many IT organizations now need to come to terms with is the degree to which they are standing in the way of enabling those decisions to be made.

    Mike Vizard
    Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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