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What Is Data Stewardship?

Data stewardship (DS) is the practice of overseeing an organization’s data assets to ensure they are accessible, reliable, and secure throughout their lifecycles. It is a framework of roles, responsibilities, and processes designed to support the organizational strategy through a data governance (DG) program. At its core, data stewardship comprises data stewards – formalized roles that take responsibility for their […]

Webinar: Harnessing the Power of Data Intelligence – Transforming Data into Business Value

Download the slides here>> This webinar is sponsored by About the Webinar In an era where data is the lifeblood of business innovation and growth, managing and understanding this critical asset has become paramount. However, the rapidly changing data landscape created a pressing need to grow and expand beyond traditional data governance to something more […]

Webinar: Launching a Data Quality Program

Download the slides here>> About the Webinar In today’s data-driven world, the quality of data is paramount to the success of any organization. High-quality data empowers accurate decision-making, effective business strategies, and operational efficiency. On the flip side, poor data quality can result in inaccurate reporting, misguided decisions, and increased costs. As organizations increasingly rely […]

Getting Started with Data Quality

Imagine burning three trillion U.S. dollars. Businesses do this virtually every year because of poor data quality (DQ).  In a data-driven age, organizations cannot afford to waste this time and money. Instead, they need to focus on achieving good data quality through a comprehensive program dedicated to business needs. But how does a company implement an effective […]

Best Practices for Getting Company Data Ecosystems AI-Ready

Organizations invest considerable resources into collecting customer data to build digital footprints and profiles for enhancing the customer experience (CX). Previous technologies and toolsets limited businesses to simple, structured data, which included mainly transactional information as well as customer and call center conversations. Then, they would use a solution like sentiment analysis to determine if […]