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Data Quality

Successful organizations realize the significance and value of high-quality data. However, our experience tells us that Data Quality initiatives must be driven by the need to solve a business problem, and there must be a close collaboration between the business and IT.

The Datasource Data Quality methodology first evaluates your data in operational and decision-making contexts to identify the value of the data and focus on what matters most. Our approach then sets the stage for IT and the business to continuously partner on data improvement. The steps include:

Contextualize

We not only analyze the systems, but how the data is being used in business operations and decision-making. This is where data value and the impact of data quality issues are realized.

Profile

With the proper context, we conduct focused, advanced analysis of known and unknown data issues. Working with the business, we discover and prioritize issues based on both data metrics and business impact.

Design

We work with business and IT to design solutions and define business rules for data cleansing and monitoring. We establish clear, ongoing responsibilities for business and IT stakeholders.

Monitor

To accommodate a dynamic business environment, we implement monitoring to ensure that appropriate data quality is maintained for business operations and decision-making.

Contact us now to learn about how a Datasource assessment can provide you with an understanding of how data quality impacts business in your organization. In addition to the initial assessment, we will provide you with the tools needed to ensure that your organization can create a collaborative, scalable, and successful Data Quality program.

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