Page Comparison

Data managment

Data managment contains BW analyses which are described below. Analyses System size and Housekeeping potential are described in the Basis add-on chapter.Image Modified

_{Data managment analyses tiles}

InfoProviders size

The analysis provides an overview of all InfoProviders in the system divided into 3 categories. Each category represents size of InfoProviders that correspond to a particular group. E.g. "10%" group represent first 10% largest InfoProviders and their corresponding size. By clicking on a bar, application will be redirected to "Top InfoProviders" analysis, where "Top %" filter will be applied accordingly.

_{InfoProviders size analysis chart}

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The user can switch to the table view for more detailed information where data can be downloaded into a CSV file for further processing.

InfoProviders by year

This analysis provides user with an overview of InfoProviders in the system. Two charts are displayed here:

• Distribution by InfoProvider type - displays whole system per InfoProvider type
• InfoProviders - objects in the chart are sorted by size by default and can be further filtered

Both charts always display last 4 years + all others merged into other group (e.g. 2013 and lower) based on amount of InfoProvider data that belong to the group. InfoProviders chart can be filtered using:

• Top % - displays InfoProviders that belongs to a particular filter, e.g. "10%" will display first 10% of InfoProviders, 
• # of objects - specifies max. number of objects to be displayed

_{InfoProviders by year analysis chart} 

The user can filter data and also switch to the table view for more detailed information where data can be downloaded into a CSV file for further processing.

It is possible to switch color mode of bottom chart to "Query usage". This colorizing mode groups data in InfoProvider by their respecting reporting usage. All data that were reported on less than 10 times are colorized with blue color and all data reported on more than 1000 times are colorized with red color. Warm data colorized with orange color belong to the category between these two threshold values. 

_{InfoProviders by query usage analysis chart}

User can change these threshold values by clicking on the  button.

NLS potential

Based on the analysis performed in the system, the visualization provides you with an overview on the potentials for archiving of particular object types (such as InfoCubes, DataStore objects, Write-Optimized DSOs) in form of column charts. 

_{NLS potential analysis chart}

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Columns that depend on data distribution settings of particular analysis are data areas usage/size columns. These columns are created based on specification of data groups for particular analysis. See Appendix B: How to define data distribution analysis /wiki/spaces/ITOA/pages/14700282 for details how data distribution and their respective data groups are defined for analysis. Each of these column contains sum (for sizes) and weight avarage (for usage) of corresponding data area values that belong to them.

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_{InfoProvider query access details InfoProvide query}

User behaviour

User behaviour contains BW analyses which are described below.

_{User behaviour analyses tiles}

Data size vs. query usage

The visualization shows the relationship between data access and size of InfoProviders divided by time characteristic (in this case, year) in form of a scatter plot. It can show user how many times were data (of corresponding year) of an InfoProvider accessed in reporting. Visualization summarizes displayed information in tiles on right hand side. 

_{Data size vs. query usage analysis chart} 

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If you want to go back to previous selection (scale) just click on the button or if you want to display all collected objects click on the button. The user can also filter data. Table view is also available in one to one form, that means objects that you can see on chart will be listed in table form and ready to download into a CSV file for further processing.

Front-end usage

The visualization shows usage of different front-ends. It shows user which front-ends are used and how many queries were executed via them per some analyzed time period. 

_{Front-end usage analysis chart}

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It is possible to click on the data in the plot area and user will be redirected to the other analysis called 'Query usage by country' with used filter based on the chosen data. 
To distinguish between front-ends we are using handle type (field HANDLETP) of table RSDDSTAT_OLAP. Here is the list of possible front-ends that we are collecting:

We provide also possibility to define your custom logic for separation of front-ends that is based on handle type and you can define it by implementation of BADI "/DVD/HS_GET_QUERY_FRONTEND_USG".

Query usage by country

The visualization shows usage of different queries from all over the world. It shows user from which countries queries were executed and how many times, per some analysed period. 

_{Query usage by country analysis chart}

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Query usage by user group

The visualization shows the usage of different queries according to user groups per some analysed period. 

_{Query usage by user group analysis chart}

The user can filter data and also switch to the table view for more detailed information where data can be downloaded into a CSV file for further processing.

It is possible to click on the user group in the bar chart and user will be redirected to the other analysis called 'Query usage by query group' with used filter based on the chosen data.
As default implementation for identification of user group, "User group for authorization check" of user is used. We are providing possibility to implement custom logic of assignation user to user group by implementation of BADI "/DVD/HS_CENTRAL_GET_QUERY_GRP". 

Query usage by query group

The visualization shows the usage of different queries according to query groups per some analysed period. 

_{Query usage by query group analysis chart}

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It is possible to click on the user group in the bar chart and user will be redirected to the other analysis called 'Query top usage' with used filter based on the chosen data.
Query group is read from InfoArea which contains InfoProvider where queries were executed. We are providing possibility to implement custom logic for identification of query group by implementation of BADI "/DVD/HS_CENTRAL_GET_QUERY_GRP".

Query top usage

The visualization shows the most used queries. Queries can be filtered using:

• Top % - displays queries that belongs to a particular filter, e.g. "10%" will display first 10% of queries, 
• # of objects - specifies max. number of objects to be displayed

_{Query top usage analysis chart}

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It is possible to click on the query in the bar chart and user will be redirected to the other analysis called 'Query runtime single' with used filter based on the chosen data.

Disused / Unused queries

The visualization shows disused and unused queries per some analysed period. It shows the user queries which are not used anymore "disused" and those which were not used at all "unused". 
Queries can be filtered using:

• Top % - displays queries that belongs to a particular filter, e.g. "10%" will display first 10% of queries, 
• # of objects - specifies max. number of objects to be displayed
  

_{Disused queries analysis chart}

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_{InfoProvider usage analysis chart}

The user can filter data and also switch to the table view for more detailed information where data can be downloaded into a CSV file for further processing.

System health

System health contains analyses which are described below. 

_{System performance analyses tiles}

The worst runtime queries

The visualization shows the worst and also best query executions runtimes per some analysed period per day. For each day maximum of 10 worst query executions are captured. 

_{Query worst runtime analysis chart}

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_{Selection filters of worst query execution}

Query runtime

The visualizations show query average runtimes per some analyzed period. There are two charts visible. Left side chart displays query groups based on average runtime i.e. how many queries in system belong to each performance group during analyzed period. Right side chart displays scatter chart plot for each individual query with average runtime and number of executions. The user can filter data and also switch to the table view for more detailed information where data can be downloaded into a CSV file for further processing.

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_{Query execution details table}

Here it is also possible to filter or download data. User can also click (drill down) on the row in order to get more information about query execution as time when query was executed, min., max. and average query runtime and also selection string.

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_{Query execution details per filtering InfoObjects combinations}

Here it is also possible to filter or download data or switch to table view and download data to CSV file for further processing.

Query runtime by categories

The visualizations show query average runtimes according to query processing categories per some analyzed period. Displayed categories are BI Suite, Data Manager, Olap - Cache, Olap – Olap, Olap – Authorizations and Olap – Input Help (for more info). 
Top part of analysis display average time spent in processing by each category for whole system. While bottom chart displays average processing times in categories for individual queries. 

_{Query runtime by categories analysis chart}

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There is a lot of possible KPI analyzes which can be visualised per some analyzed period (check appendix H: Complete list of KPIs).

_{CPU usage analysis chart}

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