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Full Price Tuition Includes Post Lab Environment

Course Description


Self-Service Analytics with InfoAssist (Advanced Techniques)

Course 391  |  CEUs:  1.2  |  2 days
US $1600  Canada $1600

Class Schedule
Start Date End Date Start Time Time Zone Location
December 18th, 2018December 19th, 201809:30 AMESTOnlineClosed
January 24th, 2019January 25th, 201909:30 AMESTOnlineClosed
February 13th, 2019February 14th, 201909:30 AMESTOnlineEnroll
February 14th, 2019February 15th, 201909:30 AMMSTOnlineEnroll
March 21st, 2019March 22nd, 201909:30 AMESTOnlineEnroll
April 30th, 2019May 1st, 201909:30 AMESTOnlineEnroll
May 21st, 2019May 22nd, 201909:30 AMESTOnlineEnroll
May 22nd, 2019May 23rd, 201909:30 AMMSTOnlineEnroll
June 5th, 2019June 6th, 201909:30 AMESTCincinnatiEnroll
June 25th, 2019June 26th, 201909:30 AMESTOnlineEnroll

    Release 8.2.03

    This course goes beyond the basics to show you how to use Information Builders’ InfoAssist for governed self-service reporting, analysis, and data discovery. Besides point-and-click methodologies, it also covers techniques and best practices to gain more insights about your data.

    You will learn how to:

    • Use Boolean logic and filter for aggregated data values
    • Specify parameters for dynamic filters, measures, and dimensions
    • Automatically link procedures to display additional related information
    • Set up customized links to procedures that dig deeper into your data
    • Build free-form reports
    • Retrieve unmatched data
    • Cache data for multiple processing in your session
    • Rank values with an “all others” category
    • Customize charts and animate them over a given time span
    • Populate chart field containers in real-time to aid quick decisions with Insight
    • Create an active display where multiple charts are interconnected
    • Generate reporting and charting templates

    Who should take this class:

    This course is for users who are somewhat familiar with InfoAssist wanting to learn more about the many robust features available for analysis and data discovery purposes.

    

    Also available as eGuide

     

    Prerequisites: