Data strategy projects are not the spectacular projects with cool dashboards and groundbreaking analytical results. These are projects to fix or prevent data quality issues. In spite of that data quality related questions consume most of the time and resources in analytics projects.
Although many think that data quality issues are IT problems in the reality these are manifestation of issues caused by business processes that are not managing data properly.
You should always ask: how reliable my analytics results are if they are based on data of questionable quality? This question is also more-and-more in the focus of regulations like BCBS 239, GDPR, Swiss Data Law.
How we help?
We help our clients with deploying proven process frameworks and software tools to fix data quality problems.
- We define high quality data and set up deterministic/artificial intelligence rules to distinguish it from junk
- Set up a straightforward rule set to maintain high data quality – also proposing business process changes
- We clean the data to ensure high data quality with the help of a data steward of your organisation
- We help you to find a data steward if you do not have one yet
- We help you to continuously monitor and address data quality issues and enhance your data governance framework
Typical topics of a data strategy project are: data modelling, data processing, master data management (MDM), data governance (DG), data quality.