An Expert Guide to Using Digital Platforms
How to do Data Cleansing In Existing Legacy Systems for your New Digital Platform
What is Data Cleaning, its Importance and Benefits?
Now, we should consider the data cleansing process within the legacy systems.
Typically the data in legacy systems can be of poor quality and be inconsistent between systems. For example, a customer’s name may be Smith in one system and Jones in another. It is also possible that one system uses a number to uniquely identify each customer and another customer uses a completely different alphanumeric code.
The process of normalising and correcting data across your systems is known as cleansing.
Scoping And Cleansing
Earlier, we discussed the need to scope each iteration of your Digital Platform. This scoping will allow us to limit the amount of time-consuming and expensive data cleansing that we will need to undertake at any one time.
Although you should automate your data cleansing as much as possible, cleansing is frequently a semi-accurate manual task requiring time and money. You may choose not to cleanse some data and trust that your new Digital Platform (specifically the Data Broker component described in our earlier section) will work out the “most correct” data when the client Apps requests it for your Digital Platform.
Ideally, you’d undergo the data cleansing process before incorporating it into a Digital Platform, but sometimes it is just too uneconomic to do so!
Other Benefits of the Data Cleansing Process
There are other benefits to cleansing your data. Especially in global organisations, cleansing for a Digital Platform is a great opportunity for agreeing on common coding and identification practices for key information in your organisation. This could be agreeing a global system for labelling products, identifying customers or coding projects. In itself, this will improve cross-border understanding and co-operation within your organisation.
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