Data Management

Rubbish in, means rubbish out. Data quality is critical to ensure that your business intelligence solution is presenting accurate information. To do this, you need a data management plan that dictates who and how people access the data, covering the following:

Data Quality is about helping organisations better manage and improve the quality of the raw information within their systems, to improve their ability to make business decisions based on the information.

Data Governance is firstly about people and processes, then technology. It’s critical to have the right incentives and processes in place so you can improve data confidence and data quality.

Master Data Management (MDM) relates to creating enterprise data dictionaries for organisations, so that when one division talks about revenue, other divisions are using the same definition. It’s amazing how many different definitions there can be throughout one organisation.

We have developed a suite of tools to help you improve your data management initiatives. The following graphic demonstrates our iterative approach used in our data migration framework.

Example of data management engagements include:

• Data Quality Strategy

• Data Profiling Audit

• Data Governance Project

• Master Data Management Project

• Data Migration