Integration & IT Modernization

Three Words for Data Quality Initiatives

Today every business is taking more and more data from various and untrusted sources system and using it in more ways than ever before. Whether it may be a small organization or an enterprise environment, data quality management is both challenging and significantly important to every business. Despite the importance, Data Quality initiatives sometimes remain stuck on the back burner due to resource and time constraints.

The best way to improve quality of data is by using the data collected and providing the feedback. The way to overcome these constraints and improve data quality is by building tools to access the data. These tools must help in examining data in different perspectives. With these different perspectives, data sources can be diagnosed and the quality of the data can be improved. Also note that the tools to be used must provide ease in changing different perspectives.

There are lots of Data Quality tools available in the market. Most companies makes Data Quality tools that enable organizations to jump-start their Data Quality initiatives while also providing a smooth path to Data Quality program growth and maturation.

Informatica has pioneered the categories of data integration and data quality since 1993 and offer a full suite of data quality and data enrichment—or Data as a Service (DaaS)—products that ensures consistent quality throughout data’s lifecycle—as it enters your systems, is analyzed mid-stream, and when it’s stored or archived—on premise, in the cloud, or on Hadoop.

Using Informatica data quality, challenges can be overcome and companies can create a single true and accurate view of customer.

Resist putting your Data Quality initiative on the back burner. Start small but start. if you find yourself asking, “How do you start?”

I will tell you in 3 words.

Engagement, Communication, Accountability

1.) Engage with your source system team early in the process.

Data is coming from all directions and it’s important to open the bridge between all of the sources (the claims department, medical records, insurance forms, etc.)

You cannot forget; however, that this is a two-way street.

2.) The IT team needs to provide clear communication on what data is expected and how it comes across.

  • Standardize and stress the importance of what is required and the format in which it needs to be delivered.
  • Use phrases like, “This is how we want the data, this is how we expect the data.”

3.) After the team communicates the way in which data needs to come over, it is critical to hold the source system team accountable. They are the people who are feeding data into your system. Make sure there is integrity in the data they send over.

It is a team effort.


Imagine a football coach and his team.

The coach gathers the team, communicates to the team on strategy, and then the team goes out into the field and executes on the strategy. That’s the way games are won and that’s how we get Data Quality. With Engagement, Communication, and Accountability.


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  1. Great post, thanks for sharing. Because of the rising importance of data-driven decision making, having a strong data governance team is an important part of the equation, and will be one of the key factors in changing the future of business. There is so much great work being done with data in various industries such as financial services and health care. It will be interesting to see the impact of these changes down the road.

    Linda Boudreau 

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