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What’s New in Cognos Analytics 11.1.4

October 31, 2019

Demos and Q&A with IBM Offering Manager

Cognos Analytics 11.1.4 was released on October 15, 2019, with a bunch of cool new functionality and improvements.

In this webinar recording, the oh-so-personable Rachel Su from the IBM product team demos and discusses

  • Custom visualizations from D3 and other visualization engines
  • Forecasting in visualizations, including confidence intervals (very cool)
  • Improved crosstabs
  • Improved KPI widget
  • Compact legends
  • Starting points in Exploration
  • Jupyter Notebooks in Reporting
  • Improvements in Smarts
▼ TECHNOLOGIES COVERED

Cognos Analytics

▼ PRESENTER

Rachel Su
Cognos Analytics Offering Management Leader
IBM

Rachel has over 10 years of experience in different areas of Cognos. Her current area of focus is Cognos Analytics reporting. She is passionate about analyzing the market landscape, as well as transforming and modernizing business intelligence. She also has proven track record of delivering advanced product features. 

▼ PRESENTATION OUTLINE 1

  • IBM Cognos Analytics 11.1.4 overview
    • New welcome section on the home page
    • Waterfall visualization available
    • Forecasting in line/column visualization
    • KPI widget (compare two measures)
    • Zero suppression for OLAP sources in crosstabs/tables
    • Supporting custom visualizations (D3, Highcharts, iCharts)
    • Updated crosstab (resize column/row, hide, search)
    • Compact legends on visualization
    • Jupyter Notebooks output in reports
    • Weather Company data source
  • Reporting
    • Supporting custom visualizations
      • Custom visualizations can be uploaded directly from Reporting and dashboarding for reuse
      • Developers can preview and test custom visualizations live within Cognos Analytics before uploading
      • Administrators can set permission on custom visualizations for access control
      • Additional properties can be included as part of the custom visualization
    • Compact legends on visualizations
      • Legends are top positioned by default
      • More compact design
      • Users can change legend section height directly on the visualizations by using the gripper
    • Jupyter Notebook integration with Reporting
      • Jupyter Notebook cells can be included as part of the report output
      • For saved report outputs, Notebook cells will always show the latest refresh results
    • Dashboard
      • KPI visualization
        • Three data slots – KPI measure, comparative/target measure and time
        • The time slot is an optional field and can be used to generate the spark line
        • The target measure can be taken from the data, a calculation or a manual value found in the properties
        • Up to three steps to measure performance against a target
        • Built-in indicator shape selection
      • Crosstab enhancement – new design layout RFE: https://www.ibm.com/developerworks/rfe/execute?use_case=viewRfe&CR_ID=128582 and https://www.ibm.com/developerworks/rfe/execute?use_case=viewRfe&CR_ID=127414
      • Waterfall visualization – depict positive and negative values within the same visualization
      • Time series forecasting
        • Option to display forecasted values in line, column or bar visualizations with time data
        • Available in dashboards, stories and explorations
        • Automatic detection of seasonality and exponential smoothing model with best fit
      • Explore
        • Compare card
          • Suggestions for creating a comparison
          • Improved interaction with compare line
          • Comparisons across more aggregation methods – average, counts
        • Relationship diagram
          • Choices up front to help users orient themselves to the information
          • Suggested visualizations presented immediately
          • Edit scope, like edit drivers (edit drivers also has updated UI)
        • Other
          • Clarify ambiguous fields
          • Properties on visualizations
        • Data modules
          • Improved joins: support for between non-equi joins; Operators: [<, >, <=, >= ] now supported
          • Simplified data group creation – change from numeric to text style in cases where groups need to be specific values
          • IBM Weather Company data
            • Live data connectivity to IBM Weather Company’s history on demand and enhanced forecast API packages
            • Blend weather data with your corporate data
          • Smarts & AI
            • AI assistant enhancements
              • Generate a dashboard using a suggested chart as context
              • Improved filter support
              • Smarter related visualization recommendations
            • Home page
              • Generate a dashboard using a suggested chart as context
              • Improved filter support
              • Smarter related visualization recommendations

▼ PRESENTATION OUTLINE 2