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Adaptive Data Governance: What, Why, How

In DATAVERSITY’s 2023 Trends in Data Management survey, about 64% of participants stated that their companies had Data Governance (DG), the formalization and enforcement of data operations across the company, in the initial stages. Yet, 60.9% listed data silos as the greatest Data Management challenge. If DG is supposed to break down data silos for better insights while ensuring compliance […]

Understanding the Modern Data Stack

The modern data stack is a collection of tools used to collect, store, and analyze data. Understanding the components of a modern data stack is crucial in grasping how contemporary data ecosystems function. At its core, data engineering plays a pivotal role by focusing on the practical application of data collection, storage, and retrieval. This discipline ensures […]

A Brief History of Data Quality

The term “Data Quality” focuses primarily on the level of accuracy possessed by the data, but also includes other qualities such as accessibility and usefulness. Some data isn’t accurate at all, which, in turn, promotes bad decision-making. Some organizations promote fact-checking and Data Governance, and, as a consequence, make decisions that give them an advantage. […]

Data Discovery 101

Data discovery deals with extracting useful information from data and presenting it in a visual format that is easily understood. The types of useful information discovered during the process range from finding patterns in human behavior to gaining insights about data glitches to answering highly specific business questions. Using data taken from a variety of […]

Data Governance Metrics: How to Measure Success

The use of Data Governance metrics as a measurement system promotes the efficient use and management of data.  Establishing key performance indicators (KPIs) is normally the first step in monitoring and measuring the effectiveness of a Data Governance program. These indicators allow organizations to assess and adjust their Data Governance strategies. A measurement system allows […]

Master Data vs. Reference Data

The terms “master data” and “reference data” can be confused fairly easily. Both provide data that changes only occasionally over time and provide data that is designed to be accurate and up to date.  Master data provides the accurate information needed for business transactions that are critical to the running of a business – the […]

Types of Data Integrity

Over time, different types of data integrity systems and methods for promoting data integrity have been developed. Data integrity emphasizes confirming the data remains unchanged and consistent over the data’s entire lifecycle. In essence, the data remains pure and uncorrupted. Security plays an important role in ensuring the data is not altered and maintains its […]

Women in Data: Meet Dr. Christina Sandema-Sombe

The latest installment in our Q&A series with women leaders in data features Dr. Christina Sandema-Sombe, chief data steward of Nike, Inc. (Read our previous Q&A here.)  Dr. Christina Sandema-Sombe first learned the joys – and challenges – of working with data as the global impact measurement lead at a humanitarian aid organization. Over a decade […]

Data Stewardship Best Practices

As we continue to do business in a digitally connected world, more data-driven organizations are prioritizing data stewardship and following best practices to improve data quality and management. Data stewards maintain and protect data assets that need special care, not just for cybersecurity but for better business insights and more informed decision-making. In his presentation at a […]