With quickly changing data products and capabilities in today’s marketplace, businesses are at risk of making mistakes when choosing solutions for information systems and data management. Many companies prefer to rely on consultants and trusted partners for total expertise, rather than navigate the narrow, overlapping disciplines of data scientists, data analysts, and data engineers. Because of their poor data quality, 40 percent of all business initiatives fail to achieve their targeted benefits. Ensuring that the data your organization uses to make business-guiding and revenue-driven decisions are accurate will significantly improve your short-term and long-term success.
Our white paper on data quality management will help your company answer the following questions:
- What is Data Quality Management?
- What Roles are Required of a Team for Successful Data Quality Management?
- How Does the Typical Data Quality Cycle Work?
- What are the Impacts of Poor Data?
- What are the Key Characteristics of High-Quality Data?
- What is RESPEC's Three-Step Process for Evaluating Data Quality?