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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. […]

MDM vs. CDP: Which Does Your Organization Need?

Most, if not all, organizations need help utilizing the data collected from various sources efficiently, thanks to the ever-evolving enterprise data management landscape. Often, the reasons include: 1) Data is collected and stored in siloed systems; 2) Different verticals or departments own different types of data; 3) Inconsistent data quality across the organization. Implementing a central […]

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 […]

Mind the Gap: The Data Chasm

Welcome to the inaugural edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). This month, we start not with a gap but with a chasm – one that’s at the core of a bewildering paradox. We continue to see […]