Data has become one of the most valuable assets of modern businesses. The data a company collects, analyzes, and monetizes now serves as a distinct “asset class” rather than merely a byproduct of its IT operations. However, the value of data to an organization diminishes rapidly as the information becomes less accurate. Companies are responding to […]
Data Quality Metrics Best Practices
The amount of data we deal with has increased rapidly (close to 50TB, even for a small company), whereas 75% of leaders don’t trust their data for business decision-making. Though these are two different stats, the common denominator playing a role could be data quality. With new data flowing from almost every direction, there must be a yardstick or […]
Common Data Integrity Issues (and How to Overcome Them)
To say data has “integrity” means that it can be trusted and relied upon and is ultimately useful. Data integrity also conveys a sense of unity and completeness. The greatest challenges to ensuring that data has integrity are any characteristics or events that detract from the data’s usefulness, trustworthiness, and reliability, as well as anything […]
Embracing Data and Emerging Technologies for Quality Management Excellence
In today’s rapidly evolving business landscape, the role of quality management (QM) is undergoing a significant transformation. No longer just a compliance checkbox, QM is emerging as a strategic asset that can drive continuous improvement and operational excellence. This shift is largely propelled by the adoption of intelligent technologies and the strategic use of data, […]
What Is Data Reliability and Why Do You Need It?
“Can I trust this data?” In the dawning age of artificial intelligence (AI), this question becomes increasingly critical for individuals and organizations. Data reliability is the cornerstone of an organization’s data-driven decision-making. A recent survey from Precisely identified data-driven decision-making as the primary goal of 77% of data initiatives, yet only 46% of organizations have high or very […]
Building Trust in the Digital Age: The Role of Data Verification
Data has famously been referred to as the “new oil,” powering the fifth industrial revolution. As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount. Trust is a multifaceted issue when dealing with data and events, and one core component is data verification. […]
Data Quality Management 101
Data Quality Management is necessary for dealing with the real challenge of low-quality data. Data Quality Management can stop the waste of time and energy required to deal with inaccurate data by manually reprocessing it. Low-quality data can hide problems in operations and make regulatory compliance a challenge. Good Data Quality Management is essential for […]
Data Quality Metrics: How to Measure Success
Data Quality metrics are a measuring system that allows the “quality of data” to be evaluated. Data Quality metrics can be used to determine how useful and relevant data is, and it helps to separate high-quality data from low-quality data. It is much easier—and safer—to make business decisions based on reliable information. Poor information (based […]
Three Reasons to Take a More Holistic Approach to Data Management
Click to learn more about author Olivia Hinkle. Taking a holistic approach to data requires considering the entire data lifecycle – from gathering, integrating, and organizing data to analyzing and maintaining it. Companies must create a standard for their data that fits their business needs and processes. To determine what those are, start by asking […]
Case Study: Department of the Interior Lays Out Steps for Metadata Implementation
After the U.S. Office of Management and Governance issued the Open Data Policy, federal agencies set to the task of developing Enterprise Data Inventories to support a mandate of government transparency. The Department of the Interior (DOI) took this opportunity to create and implement a Metadata Management framework using an enterprise approach, properly documenting data […]