Data Archiving

Introduction

Information is your business. The more you acquire it, the wealthier you are. The wealthier you become the more data you've got to handle - at a time. Today's businesses cannot afford to throw away a single bit of information. None becomes useless. They only get redundant for the moment And to handle the redundant old with minimum time and resources spent on it is the challenge faced by most of the companies today. The large volumes of data stored in modern databases can often lead to performance bottlenecks, which intern lead to poor application performance and increased demand on resources. Therefore, data that is no longer needed in the database should be removed to maximize space and performance. However, simply deleting the data is often not an option, as read-access to some data may still be required. Hence, though the protocols of data can be rearranged, the total amount of space needed keeps on increasing. Even the high availability concepts offered by hardware vendors, for example using data replication, require increased investment in disk space and CPU performance.
SAP Data Archiving is the only method supported by SAP for consistently removing data from the database (and subsequently maintaining the availability or read-access). Consistency is achieved by the integrity requirements of SAP archiving programs.
We offer unique archiving strategy for freeing up space resulting in speed, efficiency, data clarity and optimised performance.
We offer unique archiving method which allow for the removal of this vast data from the live scenario without restricting easy access or retrieval of the same. This gives the database more free space and hence more speed, efficiency and data clarity.

Why Archiving ?

Here lies the challenge of reducing hardware costs by the effective handling of the old gold-ARCHIVING. Archiving is, in principle, only carried out for data that is no longer required by the day-to-day business because it belongs to closed business processes. For indexed accesses, which are usually the case, this means that the system has to search through larger index trees. The processing time is proportional to the volume of data, which the system has to search through. The end user will also be offered more data because the volume of data selected increases when data volumes are larger. This has a particularly negative effect on the clarity of the available data. To sum up, archiving data that is no longer required by the day-to-day business can significantly reduce end user workloads
In the R/3 System, data from closed business processes is only very rarely processed in change mode. Investigations have shown that in the FI component the system accesses documents belonging to closed posting periods only in exceptional circumstances. So the data not actuaify required by the operational transactions and which can be removed and stored in tertiary storage media (archived) is considerable.

Archiving requirements:

Legal requirements:

Some kinds of data must be archived so that they can be analyzed at any time in the future, for example data required by the tax authorities. These requirements are subject to the laws of the relevant country.

Technical requirements:

From a technical point of view, the question is whether data can still be read long after it has been archived, independent of the hardware used at the time of archiving and the software release status.

Business requirements:

From the business point of view, only those data objects which are no longer required in day-to-day operations may removed from the database. Therefore, a logic check must be performed to ensure that only data objects belonging to completed business processes can be archived.