Garbage In…. Garbage Out….

BI System Chart

No BI technology, no matter how advanced, can provide useful analytics if it is based on poor quality data sources. Poor data quality is the silent enemy of BI systems. Many organizations often try and ‘fix’ poor data quality by making changes in the reporting toolset and manual workarounds. However, such ‘fixes’ only address the symptoms and not the cause. The best way to tackle poor data quality is to go to the source of the problem, and the source often involves more than meets the eye…

At Engage, we recognize that data quality is much more than a just a technology issue, it is also a change management issue. Data entry activities have a big impact on the timing, quantity, and quality of data that is created in source systems. Yet, many organizations have lax controls and protocols over the creation, ownership, and processing of their own data. Such weaknesses inevitably lead to BI problems downstream.

Our Change Management for BI will help you develop and execute a data quality strategy that meets the following goals:

  1. Establish and enforce compliance for accurate and timely data entry into source systems.
  2. Establish clear best practice standards for maintenance and governance of data quality.
  3. Develop Master Data Model (MDM) for optimized data consumption.
  4. Develop standardized reconciliation protocols for data management and data cleansing before it arrives in the data warehouse (e.g. via source systems or interfaces)