1. Home
  2. Other Releases
  3. On-premises 5.2
  4. Guides
  5. Tours
  6. Concepts
    1. Aggregate filter
    2. Alias
    3. Apache Avro™
    4. Apache Kafka™
    5. Applied filter
    6. Base table
    7. Bookmark
    8. Business schema
    9. Business schema view
    10. Business schema view column
    11. Business schema view formula column
    12. Column
    13. Connector
    14. Dashboard filter
    15. Dashboard folder
    16. Dashboard runtime filter
    17. Data agent
    18. Data alert
    19. Data destination
    20. Date system variable
    21. Distinct filter
    22. Expression
    23. External data source
    24. External session variable
    25. Filter expression
    26. Filter expression session variable
    27. Filter option
    28. Formula column
    29. Formula expression
    30. Full load
    31. Global Variable
    32. Incorta Analyzer Table
    33. Incorta Analyzer Table column
    34. Incorta Analyzer Table formula column
    35. Incorta Analyzer View
    36. Incorta Analyzer View formula column
    37. Incorta SQL Table
    38. Incorta SQL View
    39. Individual filter
    40. Insight filter
    41. Internal query expression
    42. Internal session variable
    43. Join
    44. Join condition
    45. Join condition column
    46. Join filter
    47. Join filter column
    48. Level based measure
    49. Load filter
    50. Local data file
    51. Local data folder
    52. Materialized View
    53. Materialized View Column
    54. Materialized View Formula Column
    55. Measure filter
    56. Miscellaneous system variable
    57. Multi-Source table
    58. Physical schema
    59. Physical schema table
    60. Physical schema table column
    61. Physical schema table formula column
    62. Physical schema table runtime security filter
    63. Presentation variable
    64. Prompt
    65. Query system variable
    66. Runtime business view
    67. Runtime business view formula column
    68. Runtime security filter
    69. Session variable
    70. Shared Storage
    71. SQL Interface
    72. Upgrade Readiness
    73. Variable
    74. Visualization
  7. Tools
  8. References
  9. Integrations
  10. Data applications
  11. Releases

Concepts → Level Based Measure

About a Level Based Measure

A level based measure is a measure that performs a calculation at a predefined level of aggregation and can be evaluated based on one or more levels of aggregation (i.e. grouping dimension). On a Dashboard tab, a defined level based measure displays as a Column in a table insight.

A level based measure enables you to:

  • Evaluate measures grouped by different levels of aggregation in the same tabular insight.
  • Analyze the contribution percentage of one aggregation level with respect to another (e.g. a country’s contribution percentage to the regional revenue).
Important

In the Formula Builder, when using a groupBy parameter for a level based measure, you must include all the leading grouping dimensions in the insight from the top down to the level based measure to be evaluated.

Example

Consider a scenario where you want to analyze the sales revenue by the following aggregation levels:

  • Region
  • Subregion
  • Country

In this case, you must use a level based measure to calculate the following:

  • Revenue based on the Region level
  • A country’s contribution percentage with respect to the Regional revenue
  • Revenue based on the Subregion level
  • A country’s contribution percentage with respect to the Subregion revenue

Use the following steps for detailed instructions on how to use a Level Based Measure:

Note

In the Cluster Management Console (CMC), you can create a tenant that includes Sample Data. The Sample Data includes the SALES schema.

  • In the Navigation bar, select the Content tab, and then select + New → Add Dashboard.

  • In the Add Dashboard dialog, for Name, enter Revenue Dashboard, and then select Add.

  • In the Action bar, select + (add icon), or select + Add Insight.

  • In the Insight panel, select Listing Table or V.

  • In Tables, select Aggregated Table.

  • In the Data panel, select Manage Dataset (+).

  • In the Manage Data Sets panel, in Tables, select SALES.

  • From the Data panel, drag and drop the following fields from the COUNTRIES table to the Grouping Dimension tray:

    • Region
    • Subregion
    • Country

  • Drag and drop the Revenue column from the SALES table to the Measure tray.

    • If the Properties panel is not already open, select > to the right of the Revenue pill to open the panel.
    • In Format, select Dollar Rounded.

  • From the Data panel, drag and drop Add Formula to the Measure tray.

  • The Formula Builder automatically opens:

    • In Search Functions, select the down arrow, and then select Aggregation Functions.

    • Double-click the first sum function, sum(double[] exp, groupBy), to add the formula to the editor.

    • In the Formula Editor, replace double[] exp with Revenue and dimension, ... with Region from the Data panel.

      sum(SALES.SALES.AMOUNT_SOLD,groupBy(SALES.COUNTRIES.COUNTRY_REGION))

    • Select Validate & Save.

  • In the Measure tray, double-click the New Formula pill and rename it to Regional Revenue.

    • Select > to the right of the Regional Revenue pill to open the Properties panel.
    • In Format, select Dollar Rounded.

  • From the Data panel, drag and drop Add Formula to the Measure tray.

    • In Search Functions, select the down arrow, and then select Aggregation Functions.

    • Double-click the second sum function, sum(double[] exp), to add the formula to the editor, and then divide it by the first sum function, sum(double[] exp, groupBy).

    • Replace both occurrences of double[] exp with Revenue and dimension, ... with Region from the Data panel.

      sum(SALES.SALES.AMOUNT_SOLD)/sum(SALES.SALES.AMOUNT_SOLD,groupBy(SALES.COUNTRIES.COUNTRY_REGION))

    • Select Validate & Save.

  • In the Measure tray, double-click the New Formula pill and rename it to Contribution % to Regional Revenue.

    • Select > to the right of the Contribution % to Regional Revenue pill.
    • In Format, select Percent.

  • Redo the same analysis for Subregion Revenue; repeat the last 4 steps above and replace Regional Revenue with Subregion Revenue.

    • Subregion Revenue
      sum(SALES.SALES.AMOUNT_SOLD,groupBy(SALES.COUNTRIES.COUNTRY_REGION,SALES.COUNTRIES.COUNTRY_SUBREGION))
    • Contribution % to Subregion Revenue
      sum(SALES.SALES.AMOUNT_SOLD)/sum(SALES.SALES.AMOUNT_SOLD,groupBy(SALES.COUNTRIES.COUNTRY_REGION,SALES.COUNTRIES.COUNTRY_SUBREGION))
Note

The subregion is of lower hierarchical level than the region. When using a groupBy parameter, you must include all levels of the higher hierarchy leading to the subregion level (i.e. region in this case).

  • Name the insight Sales Revenue Analysis.
  • In the Action bar, select Save.