Are we hyper focused on the business outcome alone or more focused on the process that leads to a repeatable outcome? When it comes to data governance your business is likely focused on how to use data to create value but someone inside your organization needs to take ownership of the quality of the data. This issue bubbles up to a boil when data is deemed untrustworthy by executive management or when the quality of the data is mandatory for risk management and compliance.
Most companies wait until their name is in the headlines to prepare a process for data quality—but the damage is already done, to both the brand and the customer experience.
This is the spirit of Data Governance – institute an enterprise policy, define owners, and a process to follow to improve the quality of data.
There are many drivers for data governance, risk management and compliance initiatives and accurate and trustworthy data is one that makes the short list. When it comes to data quality the top drivers for sound data governance include:
- Lack of accurate and consistent data to support risk and compliance
- Lack of visibility into your process level information
- Disparate systems and platforms – and the growing amount of 3rd party data
- Product/Customer centric information silos
- Multiple manual steps and semi-automated controls
Governing Data that Moves
Many organizations have semi-automated checks and balances in place between disparate systems along with manual processes to correct issues, but don’t have enterprise end-to-end business rules to monitor the process from source to destination. By providing standardization and automation enabled through analytical business rules, visibility is brought into the business process to access and continuously improve the performance of your data as it moves between many disparate systems, called Data In Motion.
Having an enterprise view of data quality supports the data governance framework and is an asset when it comes to proving to the audit team that end-to-end business rules are monitoring your data to ensure risk and compliance imperatives are sufficiently covered. When this is done on an enterprise wide basis you have clear visibility into your process level information, along with automated end-to-end business rules that remove the cost of semi-automated and manual steps.
This approach to Data Governance casts a safety net around the many disparate systems to address:
- Incomplete and inconsistent data across multiple data systems
- Duplicate or invalid data that dilutes the reliability of information
- Minimal insight into the timeliness of data and little capability to monitor dynamic data
- Lack of visibility into operational data quality
Infogix offers a data governance framework to support risk and compliance that provides valuable insights into the health of your data via reporting solutions tailored to IT and business users. Using our solution, companies can glean insights from data to make better business decisions.