Solutions

Empower the Business User

Subject Matter Experts have the desire to own their data domains further while they work with centralized data governance and operations teams who desire to own systems and best practices.

However, the status quo of data quality – a fundamental part of data governance – is inherently broken. Business users struggle to establish fit with having to do constant back and forth with the data governance / data operations team to communicate needs and logic, and are not empowered to own the quality of their data better. This separation between data teams and business teams creates a chasm that we must cross if we are to scale data quality and data governance across our organizations.

Crossing the Chasm with Decentralized Data Quality

The end-to-end augmented data quality platform for enterprises.

Solidify a DQ Framework

Empowering business users with access to automated metadata to review statistical overview of data fields and ability to review automated data controls accelerates the first step in a DQ framework. This process establishes a baseline of data quality across the enterprise, provides gap analysis, defines KPIs for measurement and ultimately establishes DQ goals and standards.

Establish Fit for Success

As a second step, business users should be allowed to author, manage, adjust, test, validate and productionize data controls based on their firsthand knowledge and logic directly into a DQ framework. Establishing fit for data’s expectations is the most crucial step in a DQ program - and empowering the business user to take ownership of this fit is crucial for DQ program success.

Measure for Improvement

A decentralized DQ framework enables different business users to own DQ in their verticals or business units. Measuring improvement in DQ is directly correlated to KPIs defined, factors of DQ that matter to the business unit, and tracking such KPIs automatically over time.

Find Innovative, Hidden Insights

Eliminating the chasm between business users with direct access to data and data controls empowers the business user to unlock previously unknown insights through reviewing metadata, statistical overviews, and ultimately anomalies caught. Bringing in the business user closer to data management ultimately fosters a culture of innovation to explore new ideas and insights that a centralized data team might overlook.

Operationalize for Continuous Improvement

By enabling business users to directly engage with data quality processes, continuous improvement becomes part of everyday operations. This approach allows the SME and the data team to work together to quickly adapt and refine strategies, ensuring that data quality keeps pace with business needs. With this proactive model, improvements are constant rather than periodic, leading to more accurate and timely data that supports better business decisions and enhances operational efficiency.

Supercharge the Engineer

Centralized Management of DQ