Datavard Insights BW analysis enables you to analyze data distribution and the usage of InfoProviders in a particular system based on a characteristic (usually on time characteristic). The characteristic you choose splits data into groups, which enables us to analyze the distribution of data. Here is an example.

It is possible to enhance a set of used time characteristics by additional ones. See section (DI-1811) Define the Data Distribution Analysis#Additional Time Characteristics for more information.

Define the Data distribution analysis

You can define a new Data distribution analysis of InfoProviders in your monitored systems following the steps described in this section. This results in the creation of a new tile in Insights Fiori front-end in "Data Management" tab.

Custom Data distribution analysis tile

To define a new Data distribution analysis (technically called as Subgroup)

1. Run the transaction SE38 and execute the program "/DVD/HS_CENTRAL_SUBGROUP" or the transaction /DVD/HS_SUBG. The following screen appears.
2. Define the following Data distribution analysis attributes:
   1. Subgroup ID - unique identifier of Data distribution analysis. 

   2. Split Characteristics - defines which InfoObjects are used for the Data distribution analysis. In the current version only 1 characteristic can be defined as a split characteristic and used for data distribution. During the Data distribution analysis each analyzed InfoProvider is searched for the characteristic. If the characteristic is found, all the InfoProvider data is split to groups, which are based on the distinct values of the split characteristic. 

      We implemented a safety check that allows to split object data only up to 100 distinct values to prevent generation of too much data in the system.

   3. Data groups definition area - in this table you can define data groups. Each data group is identified by its ID (DATA_GROUP), it's description and set of conditions. These conditions define how InfoProvider data created by split characteristic is grouped into results.
      

3. Click Save to save the definition of the Data distribution analysis. To execute ...analysis we should

4. add this new data distribution to our collector. whar are we doing next and what for?

   If you would refresh Fiori after this step, you should see a new tile without data.

5. Execute the /DVD/MON transaction on ...central system.
6. Click Monitoring settings under Settings.
   
7. In the tree on left side of the screen double click on the KPI collectors folder. 
8. In the displayed list of collectors search for "/DVD/MON_HM_CL_COL_DU" collector and select its row.
9. While the collector row is selected double click on Collector's inputs folder in the left tree.

   
   

   

   
   

10. In the displayed list of collector input tables click Display/Change for/by the input table "/DVD/HS_IT_DU1".

    
    

    
11. In table maintenance view switch to the edit mode. tu to ako pokracuje a naco totu robime
    
12. Click Create new record.
13. Fill the following fields:
    1. Subgroup ID - same ID as was/ you defined for Data distribution analysis definition in the first step.

    2. Number - number of days to update size data of data groups. no entiendo
       

       Data distribution analyses collector is executed every day for all defined Data distribution analyses. Doing size update of all InfoProviders data everyday would not be possible due to long runtime of this action. Therefore it is recommened to update sizes of data in InfoProviders only once per some period. Minimal recommended value is two weeks. Update of usage of InfoProvider data is done everyday as it is much faster.

       

14. Click on Save button.
    A new Data distribution analysis is now defined. The analysis is automatically executed on all systems where the Data Distribution Collector is scheduled. See BW add-on setup section on how to schedule a collector.
    You can view the results in Fiori front-end.
    

Example

Here is an example how would be one InfoProvider data processed with data distribution specified as in previous step list. We use in this example the InfoProvider /DVD/IC_CUBE that contains the characteristic 0CURRENCY.

The ....analysis finds this characteristic in structure of the InfoProvider and selects all distinct values while it calculates their respective sizes (to co piseme hore sme vynechali). In our example the InfoProvider has size of 10 GB in total. Results of such(what is such) split would be in our example as follows:

• 0CURRENCY - EUR - 1 GB 
• 0CURRENCY - USD - 3 GB
• 0CURRENCY - NZD - 3 GB
• 0CURRENCY - JPY - 2 GB
• 0CURRENCY - CHF - 1 GB

As we don't want to see results for all available distinct currencies separately, we have defined 3 data groups (See step 1 above). The previous results are assigned to the specified data groups based on the selection defined for them./ definition

• Data group 1 - data with 0CURRENCY EUR belongs here (1 GB).
• Data group 2 - data with 0CURRENCY USD belongs here (3 GB).
• Data group 3 - groups all other data (6GB).

After execution of ... collector, we can view in Fiori front-end three columns for Data Group sizes and Data Group usages and not other columns for all distinct values/ currencies. The grouping makes it possible to focus on the usage/ analysis of data that are important for us. big screen

Restricting... InfoProviders to be analyzed  

It is not always necessary to analyze all InfoProviders based on a characteristic. You can restrict for which InfoProviders the Data distribution analysis should be executed. To restrict a specific analysis change the input table "/DVD/HS_IT_DU2" of ...collector in the following way: 

• Add a new row to the table with the following content (append or where)
  
  • Subgroup ID - ID of Data distribution analysis for which you want to restrict InfoProviders which schould be analyzed,
  • Number - Unique number for each new line in the table
  • Object type - INFOCUBE, DSO or ADSO - for type of InfoProvider which selection should be restricted.
  • Select option - Standard select option format to filter on technical name on InfoProvider
• Bellow is an example of new rows that we would add to restrict our CURRENCY Data distribution analysis to analyze all DSO and ADSO InfoProviders in the system but only one InfoCube with technical name "/DVD/IC_CUBE"

  
  

  

Additional Time Characteristics

"Standard" Data distribution analysis can be enhanced on monitored system v to take into account not just standard time characteristics (already present) but also additional ones. The only requirement for adding a time characteristic is that its values must contain a year value in the standard format YYYY somewhere. Additional time characteristics are specified on monitored/ satellite and not central system.- aktiv

For their specification execute the report "/DVD/HS_SET_ADD_TIME_CHAR" or the transaction /DVD/HS_ADDTCHA. After execution an ALV table is displayed. In this table you can add rows. Each row defines one additional time characteristic, which may used in ..analysis. 

In the first column specify the technical InfoObject name and second column the position of the year value in standard format YYYY in values of characteristic. What is it? After specification of the additional time characteristic click .

Navigational attributes(not too much tech?) can be also defined as an additional time characteristic.

Examples of viable additional time characteristics:

InfoObject: 0BIRTHDAY   Year Value Position: 1   - example of characteristic values: 20160101, 20170101, 20171231

InfoObject: ZDVD_MONTH   Year Value Position: 3   - example of characteristic values: 012016, 022016, 032017

InfoObject: ZDVD_FXYEAR   Year Value Position: 4   - example of characteristic values: BCD2016, BCD2017, DGG2017

Data distribution analysis customization

"STANDARD" Data distribution analysis can be customized according to your requirement. By default, analysis is providing following 6 data groups, in which data sizes and usages are distributed in ascending order:

<={current year - 5}, {current year - 4}, {current year - 3}, {current year - 2}, {current year - 1}, >={current year}

e.g. <=2013, 2014, 2015, 2016, 2017 ,>=2018

You can change this behavior by using the expert settings (transaction /DVD/RL_SETT_EXPERT) with the Tool name 'HM_BW' :

co za tabulka

Data groups are re-created during the next collector execution (e.g. with the HMBW_1DAY monitoring profile).