Models Based on Live Data Connection to HANA Views

In HANA models, only a single Measures dimension is initially visible in the model, but all other dimensions are available on the All Dimensions tab. Because the number of dimensions may be large, and many of these dimensions won't be relevant in SAP Analytics Cloud, you can use the Hide check boxes to make dimensions unavailable in stories based on this model.

For models based on HANA views, version management functionality is also available. You can use this feature to map any of the imported dimensions to selected SAP Analytics Cloud planning categories such as Budgets, Actuals, or Forecasts.

You can define variables for all types of models, but if variables have been defined in HANA you will also be prompted to enter the required values in SAP Analytics Cloud when you open the data output.

When using calculated columns in SAP HANA live data connection models, you'll need to keep in mind the output type of any formulas and operations in use. For data correctness, it is important to ensure the following:

• Any intermediate results are correctly cast to the appropriate type.
• The final result has the appropriate type and scale set.

For example, if you use a function that returns an integer, and divide the result by another integer, the produced output will be an integer, resulting in the loss of any digits to the right of the decimal point. This loss could cause critical data correctness issues.

• Example 1: Calculated Column (Data Type: INTEGER)

  "Age (in Years)"=DaysBetween("Birth_Date", now())/365

  • The formula will return only whole integers for age, which corresponds to the Data Type specified for the calculated column, and is the expected result.
• Example 2: Calculated Column (Data Type: DECIMAL, Length=34, Scale=2)

  "Tenure (in Years)"=DaysBetween("Hire_Date", now())/365

  • The formula will return only whole integers for tenure, but the calculated column settings indicate that a floating point number is expected as the result, meaning that a significant amount of information will be lost for each tenure calculation.
  • In cases like this, there are two recommendations:
    • Use a conversion function on one or both integer values being divided, to convert to the floating number type with the desired precision (for example, DECFLOAT).
    • Increase the Scale setting to minimize the loss of precision as values for the calculated column are aggregated.
  • A corrected Calculated Column definition could be (Data Type: DECIMAL, Length=34, Scale=7)

    "Tenure (in Years)"=DECFLOAT(DaysBetween("Hire_Date", now()))/DECFLOAT(365)

Analytics models that are based on underlying HANA database views will inherit the security restrictions applied in HANA. These restrictions can be modified in SAP Analytics Cloud by assigning specific user role security to them.

The Data Access option that is available for other model types to restrict input to specific named cells is not available for this type of model.

Note that access to models may be secured, and you may be prompted for credentials before opening the model.

When you create a model based on a live data connection HANA view, if your HANA view contains string-based time dimensions or date dimensions that you want to enrich with time-hierarchy information, complete the following steps.

If you enrich the string-based time dimensions or date dimensions in your HANA view, you can use time-related features such as Difference From story calculations, trend series charts, and time range sliders for filtering.

Note

As a best practice, we don't recommend creating string-based dimensions derived from another string-based time dimension that only exists in SAP Analytics Cloud and not in the HANA Calculation View. For more information, see SAP Note 3256812 .

Before you can follow these steps, you'll need these prerequisite configurations:

• Your remote HANA system needs to be on baseline level 2.
• The HANA MODEL DATE ENRICHMENT Delivery unit needs to be imported to the remote system. You'll need to grant SELECT access to the views in the delivery unit to end users.

1. After you select a view, select (Create Time Dimension).
2. In the Dimension field, select the HANA string-based time dimension or date dimension that you want to enrich (for example, 0CALMONTH, which needs to have the format YYYYMM – Calendar Year/Month). Make sure to follow the guidelines listed below:
   • Year must be of type String, with the format YYYY.
   • Quarter must be of type String, with the format YYYYQ.
   • Month must be of type String, with the format YYYYMM.
   • Day must be of type String, with the format YYYYMMDD, or a DATE type column.
   • Other types (for example, Timestamp and SECONDDATE) and formats (for example, MM for month) are not supported.
3. In the Time View field, select the Calculation View that you want to use to enrich the dimension with.
   Note

   Choose the granularity that matches the granularity of the dimension you're creating.
4. In the Field in Time View field, select the column in the Calculation View that will be used as the join dimension for enriching the dimension. Its format should exactly match the format of the dimension being enriched.
5. Choose the Default Hierarchy for the new dimension.
   Note

   You'll be able to work with these enriched dimensions the same way you work with date dimensions in import data models.

Some SAP Analytics Cloud features are enabled for models based on HANA views only if the SAP HANA system meets certain criteria: