The dreaded place where useful data gets lost and buried in an unusable format. It’s not standardized across the company, creates a headache when migrating SAP plant maintenance data, and takes too much time to make sense of when maintenance workers are in a hurry. The problem with long text fields is that they’re unstructured, so useful data gets hidden in the mess!

Where to Start Cleansing your SAP Long text Data

1. Reference Standard Text – Commonly used text should be extracted and converted into standard text and referenced within Long Text. That way the text will be consistent wherever it’s referenced.
2. Extract Useful Data from Long Text – Extract useful data from unstructured long text to make it easier to search. It will become more useable, easier to find, and will be grouped with similar data.
3. Improve Your Governance Processes – If your long text data is a disaster, the root cause could be your SAP PM data governance. Long text is unstructured in nature and users can type whatever they want, in any format. To create consistency, try a solution such as NRX MDG where we format the long text in a consistent way to make it easier for users to understand.

What Does High Quality Data Look Like?

Normally, a cleansing project will take an immense amount of time, personnel, and investment, with poor results. The experts at HubHead have gained years of expertise doing cleansing projects and can provide valuable advice on best practices in improving your data quality. Ultimately, you should be able to get your long text fields to the point where you can,

1. Report on the data
2. Search through the data
3. Standardize the data