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The password should be copied and backed up, because it will be needed later.įigure 6 – Password when creating a Database Analysis User You still have the option to indicate a time period in which the access should occur.įigure 5 – Possible options in creating a Database Analysis User First, assign the technical user name and select the option “Enable Space Schema Access”.

Under Database Analysis the DB Analysis User can be created.

In Datasphere click on System – Configuration.įigure 4 – Creating a Database Analysis User.

The user is created with the following steps: The code is displayed and can be used in the next step for generating the PlanViz file.įigure 3 – The generated SQL code Generating the Plan Viz output fileįor this step, a Database Analysis User is required for the Datasphere.

Log into the Datasphere and open the data model you would like to analyze.įigure 2 – Steps in generating the SQL Code.

Generate a SQL code for the Datasphere data model

The following section describes the step-by-step process of the HANA PlanViz analysis. Query runs, in which the Datasphere understands all database queries, can also be monitored in the Data Integration Monitor.įor detailed analyses, Plan Viz can be used as in SAP HANA On Prem systems. Data can also be replicated here, persistent views can be created, remote connections can be analyzed and details on these actions can be queried. It is easy to see how many tables there are, how much memory they require and what actions have recently been performed. The Data Integration Monitor offers support in monitoring and managing table replication from sources outside the SAP Datasphere and indicates the frequency of data updates.

Therefore, tools for the HANA performance analysis can also be used for the performance analysis in the Datasphere. In this blog we will be taking a closer look at this capability SAP Datasphere therefore offers us the ability to analyze performance and to locate problems. Processing data poses great challenges for system performance, especially with rising data volumes.