Planning For SAP Migration? Start with SAP Data Cleansing & Cleaning
SAP migration is a tedious job and is essential to remain time relevant. One of the most exhaustive tasks, when SAP migration is going on, is to ensure the proper data management. Data is the gold in today’s digital world and one can’t simply afford to lose a single bit of it.
But, is it wise to carry forward all the data during SAP migration?
Absolutely not as with time, some data lose its significance and investing time & efforts on such data is the sheer wastage of resources. Which legacy data migration should be carried forward, what would be the outcomes if legacy data is not carried forward, are some of the questions that should be sorted out before one embarks on the SAP migration journey. By the time you reach the end of this post, all of this and many more other things will be clear.
Understanding the concept of data quality
The utility of data is determined by its quality. Hence, before we began anything, we must understand what does data quality means. Data quality has referred to the viability of data and its significance.
For instance, data that holds clear insights about the related concepts are of good quality while the one that displays vague information and can’t be used to reach any conclusion is of poor quality.
Contact us for: Cloud Migration Services
Access to poor-quality data destroys the value and market worth of a business. A recent Gartner 2020 survey revealed that the global industry has lost nearly $12.8 million per year.
The negative impact of data growth on SAP
Data growth is not always a good thing, especially when the majority of data is of poor quality. Here are some of the potential hassles that one might face with extra data baggage:
· Excess of data will slow the performance of the SAP system.
· With hefty data load, it consumes more time for system backup
· SAP migration becomes too time consuming and becomes a tedious job to handle
· Such overloaded SAP systems demand continual scaling
· One has to do space allocation for new databases
· The excess of data increases the infrastructure expense of the organization
· It is a potential hindrance in the future modernization readiness for SAP applications
Now, that you’re aware of the adverse impact of unwanted and unregulated data growth, it’s time to know about the incidents that lead to this issue:
· Duplication of records
· No regular data housekeeping
· Lacking at the front of implementation of SAP standard procedures
· Excessive work order processing
· Not having an appropriate archiving strategy
· A huge number of orphaned entries and files
All these incidents are responsible for uncontrolled data growth and one must have a tab on all these incidents and ensure that they don’t take place at all or in the least possible manner.
Also Read: SAP Hybris Migration to Commerce Cloud Version 2 — The Process, Advantages, Cons and more…
Data Cleaning or Cleansing — A Need of the Hour during SAP Migration
Do call it data cleaning, data cleansing, or data scrubbing, all these terms are used for the process of figuring out the corrupt, unwanted, and not-necessary data present in a dataset and deleting or removing it. It is performed by using the data wrangling tools or using batch processing via scripting.
Success Case: SAP S/4 HANA Migration : Utilities Gain Flexibility And Optimization With Operational Excellence
It involves the removal of typographical errors and validating the value against the given list of entities.
This process is required to turn a specific data set relevant with the other similar data set and get rid of useless data. For SAP migration, data cleansing is crucial as:
· It prevents user entry errors and corruptions that faulty data can cause during the migration process.
· Data cleaning helps a business to get rid of data that is no longer useful SAP migration becomes quick and less tedious.
Useful Data Management Guidelines and Priorities to Adopt
Data cleaning should be the first step to be taken if you wish to enjoy the hassle-free SAP migration. However, this alone is not going to suffice the purpose. One has to take the help of some other viable data management guideless as well. Here are the key ones:
· Data prevention or data avoidance
By data prevention or avoidance, we mean to prevent the creation of unwanted data in the first place. By taking this step, one can trim down the amount of hard work that the storage layer demands. This process leads to valuable front-end IO availability to service the virtual machines.
Practically speaking, data prevention makes deactivation of the update of certain data types which are no longer holds any worth for the business.
One real-world example of data prevention is switching off updating for ACCT tables.
· Data aggregation or data summarization
One another famous SAP data management policy is data aggregation or data summarization, which refers to the process of gathering and expressing the raw data in a summary form. This process is required when one is needed to have streamlined data for statistical analysis.
In certain cases of data aggregation, raw data can be aggregated in a given period for displaying key statistics like average, minimum sum, and count.
The real-world example of this data management policy can be seen in a retail environment when customers don’t find line items crucial as their data volume is too high for reporting.
Also Read: SAP Migration: ECC to SAP S/4 HANA
· Data deletion
As the title refers clearly, data deletion is the process of deleting the data which is no longer needed to archive and has been already become a part of your system.
Some of the most prominent examples of unwanted data are Logs, Change docs, history, and processed records present in the technical Tables. Multiple SAP Standard reports are available to automatically perform the data deletion job. It is done using the pre-defined selection criteria.
While you’re taking the help of this policy, make sure that the data records that you’re going to delete are no longer a part of any data set which needs to be in the system. Deleting such data can lead to chaos.
· Data archiving
Data archiving is the process of handling or saving data that can’ be prevented or easily deleted. One can figure out the data archiving possibility in the early stage. Also, figure out for how long you need that data to be in your system.
The Final Say
SAP migration could be a breeze provided you have handled the data well. A huge pile of useless data is going to give you jitters for SAP migration. So, better get rid of it in the early stage. Try data cleaning, data deletion, and other useful data management policies. If this seems a tough task, hire an experienced SAP migration service provider like Stridely.
