Data Archiving Process
Increasing amounts of data that need to be available for further analyses but that are rarely required place a load on your BI system. The granular storage of data can quickly result in a large volume of data, particularly in the Enterprise Data Warehousing layer.
If you want to keep the amount of data in your BI system constant without deleting data, you can use data archiving. The data is first moved to an archive or near-line storage and then deleted from the BI system. You can either access the data directly or load it back as required, depending on how you archived the data.
You can use ADK-based archiving or near-line storage for InfoCubes and DataStore objects. The central object is the data archiving process. When defining the data archiving process, you can choose between classic ADK archiving, near-line storage, and a mixture of both solutions.
ADK-based archiving uses the Archive Development Kit (ADK). The ADK is a tool from SAP NetWeaver for developing archiving solutions that provides the runtime environment for archiving. Its main function is to read and write data to and from archive files.
More information: Introduction to Data Archiving (CA-ARC)
The option you choose depends on your requirements and use of the data:
● You can archive the data based on ADK: this type of archiving is recommended for data that is no longer relevant to current analysis processes, but must remain archived for the legally-required storage period and must be provided for analysis in an emergency.
● You can store the data in near-line storage: near-line storage is recommended for data that you may still need. Storing historical data in near-line storage reduces the data volume of InfoProviders; however, the data is still available for BEx queries. You can also access the data archived in near-line storage from the query monitor. You do not have to load the data back into the BI system. The database partitions and the near-line storage partitions for an InfoProvider consistently reflect the total dataset.
● You can combine ADK-based archiving with the storage of data in near-line storage: this type of archiving is recommended if you want an extra backup of your data in addition to near-line storage. Some third-party tools for near-line storage must also be connected to the ADK to allow the data to be stored. In this case, you must select both near-line storage and ADK-based archiving when you create a data archiving process.
Using a near-line storage interface, you can enhance your BI system with near-line storage solutions from third-party providers. In this way, selected SAP partners can integrate their near-line storage solutions into the BI system on the basis of BAPIs.
Use this new archiving concept for objects that you create. You can still use the archiving objects from SAP BW3.5 in the processing transaction used up until now. There is no tool for migrating existing archiving objects to the new archiving process concept. If you want to change to the new concept, however, you have to reload the data that has already been archived and then delete the archiving object. You then have to create an archiving process and archive the data again.
Using the data archiving process, you can archive and store transaction data from InfoCubes and DataStore objects.
The data archiving process consists of three main steps:
1. Creating the archive file/near-line object
2. Storing the archive file in an archiving object (ADK-based) or near-line storage
3. Deleting the archived data from the database
A data archiving process is always assigned to one specific InfoProvider and has the same name as this InfoProvider. It can be created retrospectively for an existing InfoProvider that is already filled with data.
In ADK archiving, an archiving object is created for each InfoProvider.
As with the role of the archiving object during ADK archiving, the near-line object addresses the connected near-line storage solution during near-line storage. It is also generated from the data archiving process for an InfoProvider. Near-line objects consist of various near-line segments that reflect different views of the respective InfoProviders and can also reflect the different versions of an InfoProvider.
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