Checklist: Make data integrity a priority when planning for 2014

Data integrity is critical to an organization. If you lose focus on its importance, business users will lose faith in its value to the business.


Without a proven track record of trustworthy data, your organization will never be fully confident of its business value.

Your data will never be perfect. But you can get close by making data integrity a priority. As you launch into 2014, concentrate on best practices that instill trust in your data across the organization. Otherwise, without a proven track record of trustworthy data, your organization will never be fully confident of its business value.

Start by answering some basic questions: 

  • When you face data quality issues, can you respond appropriately?
  • Do you have the systems, processes, tools, controls, and monitoring in place to anticipate problems and correct them?
  • Do you have available resources to focus on the problem?
  • Have you communicated these mechanisms to the business?

The following checklist, which is grouped into related tasks, can help your answer be an unqualified “yes” to those questions:


Assign a business owner and IT owner for every system of record (SOR) or system of source (SOS).

  • Empower owners to take action in the event of a problem.
  • Establish service level agreement (SLA) monitoring and alerts for SOR/SOS and middleware systems.



Appoint a data steward to apprise stakeholders of data definitions, standards, and rules.

  • Publish business terms in a searchable glossary, accessible with simple desktop tools.
  • Create a data lineage repository to make data movement across systems transparent.


Create data quality scorecards for individual key elements.

  • Set up data masking, encryption, virus detection, and other security measures.
  • Develop impact analysis so you can forecast problems before they arise and find solutions before it is too late.
  • Have appropriate end-to-end change management procedures in place so you can recover quickly if any changes cause problems.


Set up a regulated system for data archiving, retention, and destruction.

  • Protect even your obsolete data by implementing security measures.
  • Automate processes to eliminate arbitrary decisions about data and the chance of inconsistent and untrustworthy data.

Poor data quality can result in any number of other negative outcomes. Higher costs. Breakdowns in business processes. Poor business decisions. Inferior customer service. If you plan now to make 100 percent data integrity a goal, you can count on 100 percent trust from your organization. Ensure that have a clear definition of data in general and within various business processes at your organization by reading Informatica Vice President of Global Integration Services John Schmidt’s blog post, “How Do You Know If Your Data Has Integrity.”

Related content


Ensure integrity throughout your data's life cycle

Identifying who owns your data at different stages in the life cycle should be a priority if your business wants to be successful.


3 steps to improve communications and operational excellence

Raise your visibility, credibility, and influence by using business terms with stakeholders, then translating them into your own best practices.


Best practices are a better bet than trying to predict the future

Your problems will become only more pronounced the longer you resist a centralized data management solution.