Data hygiene
All data ages and its accuracy can change from excellent at the point of creation to no longer fit for purpose. Couple that with the fact that even new data can have flaws, and it’s clear that we need the capability to cleanse our data constantly or periodically, and sort out the ‘good’ from the ‘could be improved’ to the ‘bad’.
DBMS does not necessarily come with all cp number philippines of the tools to make sure that data is of the highest quality when it’s entered, nor how good it is over time. Therefore one of the considerationsshould be: “how will data hygiene be maintained at the highest quality?”
Data governance
The introduction of GDPR has made all organisations reflect on the policies around their data and systems and how robust and fit for purpose they are. Couple this with the legal requirements that GDPR brings and the opportunities for large fines for data breaches, and the way we manage/govern our data has never been more important. Therefore, a good DBMS must be able to respect an organisation’s data governance policy and provide tools to simplify, control, and audit the process.
Data integration
The traditional view of DBMS has been one of a ‘presentation layer’ to provide access to data, often via a UI or through controlled data transfers (possibly via scheduled extracts). Today we expect data to be democratised, securely controlled, but available where it’s needed, when it’s needed. This means that the way in which data can be accessed within DBMS has never been more important.