We are happy to announce the enhancement of the “Initial Data Migration Profile” in SAP Readiness Check for SAP ERP Usage and Data Profiling.
Figure 1: The old and new view of the Initial Data Migration Profile
The Initial Data Migration Profile of the SAP Readiness Check for SAP ERP Usage and Data Profiling analyzes important SAP ERP 6.0 data objects and their data volumes. The profile data delivers valuable input for the often tedious and costly exercise of manually scoping and assessing data objects. With this newest release, we have enhanced the data collector and revamped the user experience when reviewing the results, displaying more information, and offering additional capabilities for slicing and dicing the information.
The following list highlights the new and enhanced features that are described in more detail further below:
- Where possible, a deeper level of data analysis providing more insight into the business objects
- Filtering and grouping functions to enhance the user experience
- Introduction of new interactive UI elements to assist in the visualization of the findings
- The ability to run “what-if” scenarios supporting a selective data transition approach
- Where applicable, insight into the history of the data volume
- Identification of unused data objects and deprecated organizational units
The New Data Collector
We completely redesigned the Initial Data Profile data collector from scratch, replacing the existing collector as it only provided limited information regarding the analyzed data objects.
The scoping and development of the new data collector was done in cooperation and collaboration with the SAP Business Data Transformation Solutions team. SAP Readiness Check for SAP ERP Usage and Data Profiling and SAP Business Transformation Center now use the same data collector. This alignment helps expedite the move from evaluating and scoping to planning and conducting a selective data transition project.
Business objects are now used as data object identifiers, more commonly used to represent real-world artifacts than database table names. In total, 215 business objects are now analyzed by the data collector.
We have extended the analysis beyond the high-level data volume figures for many business objects and now provide insights into additional valuable data. For instance, you can now group results by organizational elements (e.g., company codes, plants, or sales organizations) depending on the attributes of the business object.
The data volumes can also be categorized in a historical context for business objects containing the necessary date attributes by defining year range filters.
Additionally, the new data collector now determines the first and last recorded activity dates for applicable business objects, helping to identify business objects no longer in use and resulting in a leaner data scope for the data migration.
These added values help project teams decide on the best transition approach. For instance, the Initial Data Migration Profile result can be used to evaluate the feasibility of a selective data transition approach by gaining initial insight into expected data volumes and facilitating the definition of the data scope. If the selective data transition approach is an option for your transition project, you can continue to investigate the data in detail and create a digital blueprint with the tool.
The New Initial Data Migration Profile User Experience
Figure 2: The new Initial Data Migration Profile dashboard card
The Initial Data Migration Profile dashboard card now presents a pie chart instead of a bar chart indicating the top 6 business objects by volume (see Fig. 2). To open the detail view, select any item from the pie chart or the dashboard card header.
The detailed view of the Initial Data Migration Profile was newly created from scratch and follows a flexible column layout model, which is available in many other SAP Fiori apps. The view lets users quickly expand the column they want to focus on and switch between different layouts.
Figure 3: The new Initial Data Migration Profile view in 1-column mode
By default, the view displays a table of all analyzed business objects (fig. 3) including the following columns:
- business object name
- application component
- related table name of the business object
- data type (master or transactional data)
- latest activity
- total number of items
Initially, the table is sorted by the number of items in descending order, which can be changed using the corresponding button on the top right of the table control. The content of the table can also be exported to a spreadsheet.
To quickly search for a specific business object, start typing the object’s name into the search field on top of the table, and the table will filter accordingly.
Business objects with in-depth data analysis available have a detail indicator to the right of the last column in the row. Selecting a business object switches the view to the 2-column (detail) mode. The business object list is now shown in a compressed format on the left, while the detailed data of the selected business object is presented on the right side (see Fig. 4).
To increase the space of the detail column to full screen or to close the detail column, use the corresponding buttons in the top right corner.
Figure 4: 2-column mode of the view showing the details of the selected business object
The right column within the view is divided into two parts. The filter criteria and KPIs of the selected business object are shown at the top. The lower section presents charts and tables to visualize and support analyzing the data based on the selected filter criteria.
The capabilities that can be used to group and filter the business object data depend on the attributes of the selected business object. For example, the “FI Documents” business object has the filter criteria year and company code available. Other business objects, like “Equipment,” do not contain any aspect of time but can be grouped by plant. Some objects do not have any grouping capability, such as the business object “Status Management.” For these business objects, no detailed data is available.
When the business object data contains date attributes, use the range slider control to set different intervals by year. The data is immediately filtered according to the selected range. Use the corresponding multi-select combo boxes to select filter criteria for organizational key elements, like company code or plant. All selected filter criteria are applied to the data immediately using “AND” logic.
The Selected Data Ratio KPI visualizes the ratio between the total data volume of the selected business object and the data volume based on the applied filter conditions. Additionally, the business object’s oldest and latest activity dates are shown in the KPI section. The values for the total and filtered data volumes are displayed to help identify unused or no longer used business objects.
Depending on the capabilities of the business object’s grouping criteria, you can select different options to present and examine the business object volume data using the toolbar at the top of the data section. For example, the data within the “FI Document” business object can be analyzed using the following charts and tables:
Figure 5: Different options to present and examine the business object data
When using the table option to view the business object detail, the table content can be exported to a spreadsheet for further processing by selecting the export button on top of the table.
Filter Criteria Views
To increase usability, the new Initial Data Migration Profile allows users not only to define and activate filter criteria for organizational and date-related key figures (e.g., company code, plants, year of creation, etc.) but to store them persistently in filter criteria views, which – once activated – are applied to all business object data, provided the criteria fields exist in the business object (otherwise the filter criteria is ignored).
This feature supports ongoing discussions about the data migration scope: You can define filter criteria views for different data migration scenarios and use them for what-if analysis. For example, you can save filter criteria evaluating the impact of migrating 3 or 4 years of historical data to the new system or analyze the effects of carving out one or more company codes.
Figure 6: Expand and hide the filter section
To set up a filter criteria view, expand the filter section above the business object table by selecting the related button (see Fig. 6). The filter section includes a set of multi-select combo boxes for all the available filter criteria. Choosing the values in these combo boxes defines the criteria for your filtered view. To apply your view’s filter criteria, select the Go button at the bottom of the filter section (see Fig. 7).
Figure 7: Setting up filter criteria views which are applied to all business objects
If you want to save your filtered view persistently for the analysis, select the drop-down button on top of the filter section (next to the caption “Standard”; see Fig. 7 and 8). This opens the “My Views” pop-up window, which lists any existing filter criteria views of the analysis and offers buttons to either save the currently selected filter criteria into a new view or to manage existing views (see Fig. 8).
Figure 8: Create and manage filter criteria views
To run an SAP Readiness Check for SAP ERP Usage and Data Profiling analysis, follow the instructions described in SAP Note 3112362.
You can also update an existing analysis by implementing the latest version of SAP Note 3112362 and running the analysis in your SAP ERP system again. Then, use the Update Analysis option within the header of the dashboard view within the SAP Readiness Check cloud app to update the analysis data.
As always, we are interested in your feedback!
Your SAP Readiness Check Team
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