Create a New Model

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Creating a Blank Model

You can create and design a new model with no data, and then import data later.

1. From the Modeler start page, select Model.
2. Select whether you want to create a classic account model or a new model type. For more information on the differences between the two models, check out Get Started with the New Model Type.
3. Enter a name and description (optional) for the model.
4. Select to set up some of the model's preferences.
   1. Planning features are enabled by default, but if you want to create an analytics model, select Planning, and then switch Planning Capabilities off.

      For information about planning and analytics models, see Learn About Models.

   2. For a planning model, the From and To dates to define the timeline for the data can be changed in the side panel when selecting the date dimension.
   3. If your business fiscal year isn't the same as the calendar year, select the Date Settings tab, switch Fiscal Year on, and then select the other parameters as follows:
      • Choose the starting month of your fiscal year.
      • Choose whether you denote your fiscal year by the calendar year when it starts, or the calendar year when it ends.
      • Choose whether to display fiscal periods or calendar months in stories. For example, quarterly reports cover a fiscal period of three months, while annual reports cover a fiscal period of one year.

      Model data in stories, including tables, charts, value driver trees, input controls, and filters, will display fiscal years instead of calendar years.

   4. Enable any other features you need, such as data auditing or locking, data access control, or currency conversion.

      Note that some settings cannot be changed after you've saved the model. For more information, see Set Up Model Preferences.

   5. Select OK to save the model's settings.
   6. For a planning model, in the Model Structure view, select the date dimension to acess the side panel and specify the From and To dates to define the timeline for the data.
5. For an analytical model, the Date dimension is optional. You can remove the Date dimension by selecting it, and then clicking the Delete icon: .
6. If you want to change the default settings for the Date dimension, you can do that now.

   Select the Date dimension, and then in the Dimension Settings panel, review these settings:

   1. Set the granularity of the model's timeline – that is, the time period that your data will be based on: year, quarter, month, week, or day.
      Note

      The week granularity is only available for the new model type, and must be enabled first under Date Settings in the the model preferences.
   2. Choose the default date hierarchy.

      New story tiles will display this hierarchy by default.

7. If you're creating a classic account model, add the mandatory account dimension. Add one to your model by selecting , and then either Add New Dimension to create a new one from scratch, or Add Existing Dimensions to add an account from a list of existing dimensions. If you're creating a new model type, the account dimension is optional. For more information on the configuration possibilities for the new model type, check out the Choosing a Model Configuration section in Get Started with the New Model Type.

   If you create a new account dimension, you can define it as a public dimension, if you want it to be reusable in other models.

8. Optionally, you can add an organization dimension and also other generic dimensions to your model.

   See Learn About Dimensions and Measures for details of all dimension types.

9. If you're creating a new model type, add one or multiple measures to your model. Click  on the left in the Measures section to open the Measure Details panel, and fill in the different fields within the General, Data Type, Aggregations, Units & Currencies and Formatting sections to add a measure.

   Parameter	Description
   Name	Type a unique ID for the measure using letters and numbers only.
   Description	Type a description for the measure to help your users identify it.
   Data Type	Choose the data type for your measure. The data type restricts the values that the measure can hold: Decimal: Up to seven decimal places and up to 15 digits total. Integer: Between -2^31 to 2^31, without decimal places.
   Decimal Place	If you selected Decimal, choose the number of decimal places supported, from one to seven. Keep in mind that a decimal value can only have a maximum of 15 digits including decimal places.
   Aggregation Type	Select Sum. The aggregation type determines how the measure values are aggregated in hierarchical dimensions. For measures, only Sum is supported as the default, but you can specify other aggregation types for specific dimensions.
   Required Dimensions	Select  and choose the dimensions that you want to be required for the measure. If not all required dimensions are in the displayed with the measure, for example in a chart, table, or in the Explorer, users are notified that the measure values could be incorrect.
   Exception Aggregation Type	Use exception aggregation when you want to aggregate non-cumulative quantities. For example, if you have the quantity Inventory Count, you might want to aggregate the inventory count across all products, but not across time periods, because it doesn't make sense to add up inventory counts from multiple time periods. In this case, you would choose the aggregation type SUM for Inventory Count, because you want to add up the inventory counts for all products. But if you don't specify an exception aggregation type, the inventory counts will also be summed across time. To prevent summing inventory counts across time periods, specify an exception aggregation type for the time periods. For example, you might want to choose just the most recent set of Inventory Count values. In this case, you would choose the exception aggregation type LAST, and the exception aggregation dimension Date. Exception aggregations relate to one or more dimensions. For example, for the AVG and LAST exception aggregations, a Date dimension is appropriate. If you select an exception aggregation type, you must also select an exception aggregation dimension.
   Exception Aggregation Dimension	Select  and choose the dimensions that will use the selected exception aggregation type.
   Units & Currencies	Use these options to set the currencies for a monetary measure, or the unit displayed for a non-monetary measure. Unit Type: Select one of the following options: Unit: Use this option for a non-monetary value where you want to display a fixed unit. Type the unit in Fixed Unit. None: Select this option if you don’t need to include any units. Currency: Use this option for all monetary values, then specify the currencies settings for the measure. For example, for a measure that shows only US dollars, set the Currency to Fixed and type USD. These settings don’t just change the units displayed; they also can change how the values are aggregated and which conversion rates apply to the measure.
   Scale	To improve the presentation of numbers, and hide numbers that are not significant, you can set this attribute to show just integers plus the specified number of decimal places. The unit value is then shown by the appropriate word or by an abbreviation. You can select one of the following options: Thousand (3 numerical places – abbreviation k) Million (6 numerical places – abbreviation M) Billion (9 numerical places – abbreviation G. Note that G is the international standard abbreviation for billion) Percent (% 2) This feature is related to the setting of the Unit attribute that determines if the Scale word or just the abbreviated Scale letter is used (see also the example following this table): If Unit is set to Currency, the word selected as the Scale value is used in the output. If Unit is undefined (blank), the abbreviated Scale letter is used.
   Decimal Places	This setting defines the number of digits displayed after the decimal point; select a value from 0–7. Values that have fewer decimal places will match this setting by adding zeros to the end of the value, for example 1.100.

10. If you're creating a new model type, click in the toolbar to open the model preferences, and under Structure Priority, use the Prioritize properties and calculations from drop down to indicate whether account settings or measure settings should get the priority.

    If you decide to prioritize the account account dimension, then all the aggregation definitions, formatting and unit handling are taken from the account dimension. But if you decide to prioritize the measures, everything is taken from the measures. For more information, check out Set Structure Priority and Create Custom Solve Order.

11. Save your model.

    Choose which folder you want to save the model to.

Related Information

Creating a Model from a File

Context

First, the source data is analyzed, and then the data is shown with proposed dimensions for the new model. You then refine the proposal by specifying dimension types and fixing any data-quality problems.

The workflow to create a new model from a file is:

1. Import a source file.
2. Choose dimension types for the dimensions in your new model.
3. Specify attributes for the dimensions.
4. Cleanse your data and fix any mapping or data quality problems.

Data files can be in your local file system or in your network. The source data can be an Excel spreadsheet (.xlsx) or a delimited text file (.csv or .txt). If you import data from Microsoft Excel, and if the data is saved in separate sheets in the Excel workbook, either you can choose which sheet to import (if from a local file system) or the first sheet is automatically imported (from a network file).

The source data must include columns that can be used to create dimensions in a new model, and it must also include transactional data (measures). (The transactional data is visible in the Data Foundation view, which shows you the fact table containing the raw, unaggregated transactional data loaded into your model. For details, see Learn About the Modeler.

The data will typically include details for the main account. You can identify which dimension is the main account during the import process, but if no account data is found, an account dimension will be generated automatically.

In addition to the main dimensions and transactional data, the source can also include attributes for dimensions; that is, text information such as hierarchy information or other properties.

1. From the Modeler start page, select From a CSV or Excel File.
2. In the Import Data From File dialog, choose whether you want to import data from a file on your local system, or from a file server.

   If you don't see the options to choose a local system or file server, see Allow Data Import and Model Export with a File Server.

   Tip

   If you import a file from a file server, you can also schedule imports from that file. For more information, see Update and Schedule Models.
3. If you're importing from a file server, choose a file server connection, or select Create New Connection.

   If you create a new file server connection, specify the path to the folder where the data files are located. For example: C:\folder1\folder2 or \\servername\volume\path or /mnt/abc.

4. Choose the file you want to import.
5. If you are importing from a local Excel workbook containing multiple sheets, select the Sheet you want to import.
   Note

   If you are importing from an Excel file on a file server, the first sheet is automatically imported.
6. If you're importing a .csv file, select which delimiter is used in the file, or select Auto-detect.
7. Select Import.

   For small data files, the data is imported and displayed in the data integration view, which shows the imported data columns that you'll define as dimensions, measures, and attributes.

   Larger data files may take some time to upload. You can work on other tasks while the data is being uploaded in the background.

8. When the data is finished uploading, select it from the Draft Data list to open it in the data integration view.

   

Next Steps

After the initial import of raw data, continue with the data preparation task before completing your model. See Import and Prepare Fact Data for a Classic Account Model, and Import and Prepare Fact Data for a Model with Measures.

Related Information

Creating a Model from a Dataset

1. From the Modeler start page, select From a Data Source.
2. From the proposed list, select Dataset and browse up to your dataset.

Related Information

Creating a Model from a Live Data Connection

Prerequisites

A live data connection to another system is required. The system administrator will create live data connections using the Connections page in SAP Analytics Cloud.

If you want to perform geospatial analysis in your model, then you must manually prepare your data for geospatial analysis in the connected system using SAP HANA Studio.

Access to other systems is usually secured by user ID and password.

1. From the Modeler start page, select Live Data Model.
2. Choose a System Type.
   Note

   If you're creating a model from an SAP S/4HANA live data connection, choose the SAP BW system type.
3. Then select a specific live data Connection.

   You will be prompted to enter the user ID and password to access the selected system. This makes a connection to the target system and reads the list of views that are available.

4. Select the Data Source.
   If you know the name of the data source, you can type or paste it in. Or, you can select the icon to search for a data source or choose one from a list. The first 100 views are preloaded in the list.

   Note

   The model must be created based on a query or view that contains a measure.
5. Enter the Name and Description for the new model that will be created, and click OK.
6. If you need to build a query, do so by dragging data from the Available Data list to the Selected Data and Filters areas.

   Select OK when you've finished building the query.

7. If the data from your data source comes in different versions (Actuals, Budget, Planning, Forecast, Rolling Forecast), select the (Version Information) icon on the toolbar to specify the version information.

   Then, select the column from your data source that contains the version information, and then specify the relevant category for each version of your data, such as Actuals, Budget, Planning, Forecast, or Rolling Forecast.

   If you're using this model in a story, the data will be automatically filtered on Actuals and you can create variance charts with the different categories.

8. Save your model.

Results

Related Information

Live Data Connection Overview Diagram

Models Based on Live Data Connection to HANA Views

Creating a Model from Salesforce Data

Context

1. From the Modeler start page, select From a Data Source.
2. Select Salesforce.
3. Type a name for your model.
4. Select your Salesforce connection or select Create New Connection to create a new connection.

   For more information, see Import Data Connection to Salesforce.

5. In the Select Data area, select User Predefined Model or Define Query.
   • User Predefined Model: A predefined selection of queries that are useful to most Salesforce users.
   • Define Query: Select a number of OData entities that are linked by ID, and select specific properties from them. Select Set to proceed.
6. Select a Source.

   This is the list of user reports on Salesforce.com (SFDC).

7. Define the Metadata Mapping.

   This shows how each dimension is mapped. Once you select a source in the previous step, the metadata mapping is automatically defined. However, if you prefer to use dimension names different from the ones used in the SFDC report, you can edit the predefined names.

8. Select Import.
9. Save your model.

Creating Geo Spatial Models from HANA Calculation Views

You can import a location-enabled model from a live HANA calculation view and use this data source to add multiple location dimensions to a new model.

Prerequisites

To create a Geo model in SAP Analytics Cloud from calculation views on a live HANA system:

• The HANA system should be at least on SPS11 on 112.07 or higher or SPS12 on 122.03 or higher.
• You need to perform data preparation on your source data before undertaking the steps below. For more information see SAP Note 2395407.

1. From the Modeler start page, select Live Data Model.
   Note

   From the acquire data panel, select the filter icon to narrow down the number of data sources in the list. You can filter by data source type or by category.

   The Create Model From Live Data Connection dialog is displayed.

   1. In the System Type field, select SAP HANA.
   2. Then in the Connection field, select the name of the live HANA system containing the calculation views you want to import.

      Provide your access credentials to the system in the displayed Set Credentials dialog.

   3. Select the name of the calculation view you want to import from the Data Source list.
   4. Provide a name for the new model and select OK.

      The calculation view is imported and saved with the new model.

2. Select the (Create a Location Dimension) icon.

   The Create Location Dimension dialog is displayed.

3. In Create Location Dimension, map the location identifier for your calculation view with the corresponding location data and mapping identifiers.

   Field	Required information
   Location Identifier	Select the key column which contains the identifier for the locations
   View Name	Select the location data view.
   Location Dimension Name	This name is automatically generated from the Location Data name.
   Identifier for Mapping	Select the name of the key column of the location data view.

   Note

   the column names in the calculation view model and the location data view have to be unique.
4. Save your model.

Results

You can now visualize the location data on a geo map.

Related Information

Creating a Geo Map

Creating a Model with Coordinate or Area Data for Geospatial Analysis

Before you perform geospatial analysis in stories, you must first import coordinate data or area data, and enrich it in the Modeler. This process creates a new column in the data view with an enriched format of latitude and longitude coordinates or by area using country, region, and subregion data.

Prerequisites

You must use acquired data from supported sources such as SAP BW or a file (.xlsx or CSV). The data must contain a location ID column with unique data, as well as either latitude and longitude columns, or country (required if your regions and subregions are in different countries), region, and subregion columns.

Context

These steps describe how to enrich coordinate or area data while creating a model from a file. You can also enrich coordinate or area data while uploading data to an existing model. For more information, see Combine Data with Your Acquired Data.

1. From the Modeler start page, select From CSV or Exccel File.
2. In the Import Model From File dialog, choose whether you want to import data from a file on your local system, or from a file server.

   If you don't see the option to import data from a file server, see Allow Data Import and Model Export with a File Server.

   Tip

   If you import a file from a file server, you can also schedule imports from that file. For more information, see Update and Schedule Models.
3. If you're importing from a file server, choose a file server connection, or select Create New Connection.

   If you create a new file server connection, specify the path to the folder where the data files are located. For example: C:\folder1\folder2 or \\servername\volume\path or /mnt/abc.

4. Choose the file you want to import.
5. If you are importing from a local Excel workbook containing multiple sheets, select the Sheet you want to import.

   If you are importing from an Excel file on a file server, the first sheet is automatically imported.

6. If you're importing a .csv file, select which delimiter is used in the file.
7. Select Import.

   For small data files, the data is imported and displayed in the Data Integration view, which shows the imported data columns that you'll define as dimensions, measures, and attributes.

8. Larger data files may take some time to upload. You can work on other tasks while the dataset is being uploaded in the background. When the data is finished uploading, select it from the Draft Data list to open it in the Data Integration view.

   

9. Ensure that at least one numeric column has Measure as its dimension type.
10. Select (Geo Enrichment) in the toolbar, and then choose either of the following options:
    • By Coordinates if you want to use latitude and longitude data to create the location dimension.
    • By Area Name if you want to create the location dimension based on country, region, and subregion data. The country data can be imported as ISO3 and ISO2 codes, or the country names in English.
      Note

      To download a list of supported area names, use the link provided in the Geo Enrichment By Area Name dialog.
11. Specify the following information:
    • By Coordinates:
      • Dimension Name: Type a name for the dimension that you will create using the geo enrich process.
      • Location Description: Select the column that will provide the tooltip text for dimension members displayed in a geo map.

      • Location ID: Select the dimension you want to associate with the new location dimension. Select a dimension with a unique location ID.

        Note

        You can create a location for the Dimension ID column of an organization or generic dimension. You cannot create a location dimension associated with Account, Version or Date dimensions.
      • Latitude: Select the column that contains the latitude coordinate.
      • Longitude: Select the column that contains the longitude coordinate.
        Note

        When specifying coordinates, SAP Analytics Cloud only supports the decimal degrees format (with the degree symbol omitted). For example: A latitude of 38.8897 and a longitude of -77.0089.
    • By Area Name

      Choose how you want to specify the country data:

      • Select Column: if you want to select the column containing the country data.
      • Select Country: if you want to select a specific country from a dropdown list.
        Note

        If you select a country from the list, after the data is geo-enriched, it will be limited to areas within the selected country.
12. Select Create.

    A new column is created for the location dimension. Any data quality issues are displayed in the Details panel.

Results

Next Steps

Continue with the data preparation task before completing your model. See Import and Prepare Fact Data for a Classic Account Model, and Import and Prepare Fact Data for a Model with Measures.

Analyzing Geographical Data

Creating a Geo Map

Adding the Bubble Layer

Adding the Heat Map Layer

Adding the Choropleth Layer