Now run setup. In the below screenshot, provide the kernel file path. Master Password will be picked Provide the Installation Export path Master Password will be picked automatically, you can still choose your own password. Mandatory to Enable for NW 7. Skip SLD registration or connect it to Solman. Ensure that the queue is calculated as expected Skip the modification Adjustment provide the shadow instance number and keep going further Lock the Development Please take a backup as mentioned in the SUM tool and proceed with the execution phase Again take a backup at the end of Execution phase and proceed with post-processing.
Upgrade finished successfully. Now run SGEN for all the components 7. Choose the SP level as that of source. Alert Moderator. Alerting is not available for unauthorized users. Assigned Tags. Similar Blog Posts. Related Questions. You must be Logged on to comment or reply to a post. Bartosz Jarkowski. Hello, very nice first blog! Best regards Bartosz. Like 1 Share. Right click and copy the link to share this comment. The rows from the second, or right hand side table only show up if they have a match with the rows from the first table.
In the same way, you can use the right outer join where all the rows from the right tables are preserved as common rows. Temporal Joins are used to map a period of time. You can define Temporal join that contains at least one time-dependent characteristic or a pseudo time-dependent InfoProvider.
In the next window, change how the InfoSet screen appears. Click on Select InfoProvider option. This will allow you to select the InfoProvider to which data is joined. Make the changes to the InfoSet. Select Join type, etc. An InfoCube is defined as a multidimensional dataset which is used for analysis in a BEx query. An InfoCube consists of a set of relational tables which are logically joined to implement the star schema.
A fact table in the star schema is joined with multiple dimension tables. They are available as InfoProviders for analysis and reporting purposes. An InfoCube is used to store the data physically.
It consists of a number of InfoObjects that are filled with data from staging. It has the structure of a star schema. The real-time characteristic can be assigned to an InfoCube. InfoCubes consist of different InfoObjects and are structured according to the star schema.
There are large fact tables that contains key figure for InfoCube and multiple smaller dimension tables that surround it.
An InfoCube contains fact tables that further contain key figures and characteristics of an InfoCube that are stored in the dimensions. These dimensions and fact tables are linked to each other using identification numbers dimension IDs.
The key figures in an InfoCube are related to characteristics of its dimension. Granularity degree of detail of key figures in an InfoCube is defined by its characteristics. Characteristics that logically belong together are grouped together in a dimension. The fact table and dimension tables in an InfoCube are both Relational database tables. An InfoCube consists of a fact table which is surrounded by 16 dimension tables and master data that is lying outside the cube.
It is a self-enclosed data set encompassing one or more related business processes. A reporting user can define or execute queries against an info cube. Your own InfoCube should begin with a letter between A to Z and that it should be 3 to 9 characters in length. All InfoObjects to be used in an InfoCube should be available in an active version.
Enter the technical name of the InfoCube. Add InfoObject to dimension. In a similar way you can also create new dimensions and add InfoObjects. In a similar way you can add other key figures as well. Real time InfoCubes are used to support parallel write access.
Real time InfoCubes are used in connection with the entry of planning data. You can also convert a real time InfoCube. This will delete the transaction data and InfoCube will be set to inactive. You can schedule this report as background job for InfoCubes with more than 10, data records because the runtime could potentially be long.
Virtual InfoProvider is known as InfoProviders that contains transactional data which is not stored in the object and can be read directly for analysis and reporting purposes.
In Virtual Provider, it allows read only read access to the data. Virtual InfoProviders are used to provide information without any time lag and without storing the data physically. As mentioned above, there is a need to find out when a Virtual InfoProvider should be used. Virtual Providers based on this method are easiest and the most transparent way to build this type of InfoProvider. In this case, a virtual provider can be based on a DataSource for direct access or on another InfoProvider.
Either the BEx query is executed or you navigate inside the query. But, a request is sent through the virtual provider to its source and the needed data is returned back. A large amount of data is accessed in the first query navigation step, and no appropriate aggregates are available in the source system. In this Virtual Provider, you can use the transactional data for analysis and reporting purpose from external system using BAPI.
A query is executed on VirtualProvider that triggers a data request with characteristic selections. The source structure is dynamic and is determined by the selections. This is the most complex type of a VirtualProvider but at the same time it is also more flexible using which you can add data from the source and also can apply complex calculations or any changes before it is pushed to the OLAP engine. You have a number of options for defining the properties of the data source more precisely.
According to these properties, the data manager provides various function module interfaces for converting the parameters and data.
These interfaces have to be implemented outside the BI system. If you compare this VirtualProvider with other types, this VirtualProvider is more flexible, more generic but you have to put lot of effort for implementation. In this you allow a direct access to the source system for an InfoObject type of a characteristic that you have selected for use as an InfoProvider. So there is no need to load the master data, however direct access can have negative impact on query performance.
Go to InfoObjects Maintenance page. Next is to go the modeling tab, select the InfoProvider tree. Define Transformation rules and activate. A MultiProvider is known as an InfoProvider that allows you to combine data from multiple InfoProviders and makes it available for reporting purposes. To combine the data, a Union operation is used in a MultiProvider. Here, the system constructs the union set of the data sets involved and all the values of these data sets are combined.
In an InfoSet you create the dataset using joins. These joins only combine values that appear in both tables. As compared to a Union, joins form the intersection of the tables. Create an InfoArea to which you want to assign the new MultiProvider. Then the MultiProvider screen appears. Use drag and drop to transfer the required InfoObjects into your MultiProvider.
You can also transfer the entire dimensions. The next step is to save and activate the MultiProvider and only this activated MultiProvider will be available for reporting and analysis. You can load the data from an external system to BI using these flat files. The data from a flat file can be transferred to BI from a workstation or from an application server.
If there are character fields that are not filled in a CSV file, they are filled with a blank space and with a zero 0 if they are numerical fields.
Check the following blog in the SAP Community to get more information about the wizard: Integrating customer transport requests in updates and upgrades. The usage of such an approach can result in certain kinds of impacts for database tables.
To prevent unexpected occurrences of such impacts during the maintenance event on a production system, they have to be identified in advance using the Impact Analysis tool as part of Software Update Manager 2. Software Update Manager. Download SUM 1. Software Maintenance. Database Migration. System Conversion. In all cases, SUM will take care for the software update, apply new software components and update existing ones.
Consider the downtime-optimized conversion approach to reduce the downtime of a system conversion. Customer Transport Integration. Although i doubt that this would be a recommended approach as this would just increase the complexity for administration.
The whole concept of data warehousing was founded on segregating long running intense sequential processing from short random read processing. No Account? Sign up. By signing in, you agree to our Terms of Use and Privacy Policy.
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