(DI-1705) BW add-on Fiori frontend

Data management

Data management contains analyses BW analyses which are described below. 

_{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}

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. 2012 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}

Users have the possibility to change archiving settings and the analysis will recalculate the archiving potential accordingly by the button . 

_{NLS potential analysis settings} 

Table view provides user with detailed archiving potential on object level. The user can download data into a CSV file for further processing. 

_{NLS potential analysis table view} 

Data Distribution

These analyses provide information how data are distributed in the system InfoProviders based on specified characteristic and how many times these data areas were accessed by reporting (queries). Number of Data Distribution analyses tiles is not set and is bound to settings on central system. By default BW module is shipped with only one predefined data distribution analysis. Analysis tile contains overview information of how many of analyzed InfoProviders do contain specified characteristic.

Data distribution tile

By clicking on tile you are presented with detail results of the specified data distribution analysis. 

Result table contains multiple columns. There are columns that are present in all data distribution analyses results:

• InfoProvider - contains technical name of InfoProvider
• InfoProvider Type - contains type of InfoProvider (INFOCUBE,DSO,ADSO)
• Description - Long text of InfoProvider
• InfoProvider Size [ MB ] - InfoProvider total size in MB
• InfoProvider Usage - Total number of queries that read data in InfoProvider
• DTP source count - Number of times InfoProvider was used as source in DTP load requests
• Lookups count - Number of lookups that do exist in system for this InfoProvider
• Trend Size - chart for vizualization of data areas sizes
• Trend Usage - chart for vizualization of data areas usages

Data distribution analysis view

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 /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.

You can filter on top of the any table column by clicking on the toolabar  button. It is also possible to download table content (without chart columns) into CSV file by clicking on  toolabr button. You can also hide/show all data areas columns by clicking on  toolbar button.

You can click on any InfoProvider line to display queries that were executed on top of the InfoProvider. Each line in this detail view contains query that was executed with also filter selection that was used during its execution (only filters for same characteristic as was used for data distribution are displayed). 

InfoProvider query access details

User behaviour

User behaviour contains BW module 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} 

It is possible to select multiple objects and display only them in the chart.

_{Analysis area sub-selection}

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 times queries were executed via them per some analyzed time period. 

_{Front-end 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.

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}

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 country in the map or in the bar chart and user will be redirected to the other analysis called 'Query usage by user group' with used filter based on the chosen data.
Identification of country is done by company address assigned to user that executed query.

We are providing possibility to implement custom logic of assignation user to country by implementation of BADI "/DVD/HS_CENTRAL_GET_QUERY_GRP". 

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}

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 top usage' with used filter based on the chosen data.
Default implementation is using InfoArea where besides InfoProvider where query was executed as default query group. 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}

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 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}

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.

The user can switch between disused and unused analyses using appropriate radio buttons. Unused queries are displayed as a list. 

_{Unused queries analysis list}

Data can be downloaded into a CSV file for further processing.

InfoProvider usage

The visualization shows reporting usage (query executions) of InfoProviders in analysed time period. 

_{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}

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 data in the plot area or in the table and the user will be redirected to the exact selection of query for corresponding worst execution, where data can be filtered and downloaded into the CSV.

_{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. 

_{Query runtime analysis charts}

User can click (drill down) in the left column chart in order to get more information about query execution. 

_{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.

To this analysis it is also possible to go directly from the scatter plot in the Query runtime analysis (by drilling down on the data in the scatter plot).

_{Query execution details per filtering InfoObjects combinations}

Here it is also possible to filter or download data or switch to table view.

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}