4 Steps to ideal Master Data Management – Your MDM Project
Implementing and developing an optimal Master Data Management (MDM) solution is a project that requires close collaboration between business and IT. Based on our experience, we have identified four project steps to ensure the best data quality and a high level of MDM maturity in your organization.
1. Screening The Data Landscape
Situation
Want to improve data quality in your organization? Are you struggling to find a specific problem/application or measure the value of high quality data?
Procedure
We work with you to analyze your data landscape, identify quality issues, and measure value. This can be achieved through comprehensive master data management.
Result
Get an action plan with guidance on how to approach your master data management project in a condensed report.
2. Database Testing
Situation
You know what data quality issues exist in your organization, but you are not sure how good the data quality is?
Procedure
We measure the quality criteria of a data source with DATAROCKET Core (syntax test + semantic test) in a starter project.
Result
A data profile report of your data landscape (e.g., duplicates, golden records, error and plausibility issues, content, minimum and maximum values, descriptive statistics).
3. Cleansing Projects
Situation
You know the problem and want to take your data quality to the next level?
Procedure
We work with you to create a set of quality criteria and metrics (for measuring value) to be calculated, tailored to your needs. We compile these in the form of a data pipeline in DATAROCKET Core, which can be used for workflow-optimizing cleansing.
Result
You get high quality data, continuous reporting, and a structured and detailed data quality policy.
4. Real-Time Quality Control
Situation
You want to automate quality control and ensure early on that nothing can negatively impact the quality of your data - e.g., errors in data entry/data set changes or during data migration - and to maintain a consistent and continuous level of data quality in your master data so that it can be used by different departments and provide a solid basis for reporting.
Procedure
DATAROCKET Core acts as a central hub to which other relevant systems can be connected. The pre-defined quality policy automatically performs checks, such as checking values for accuracy and duplicates during data entry.
Result
One comprehensive master data management system. You get a single source of verified data (single point of truth) and a 360° view of your data. Most importantly, you will be able to take control of your master data - in short, your business will benefit.
