A database management system (DBMS) describes a collection of multiple software services that work together to store, compute, maintain, structure, and deliver the data as part of a product. This platform also provides metadata, a system of data labeling, so that engineers and users can understand and map what entities and properties are available and their […]
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 […]
RWDG Webinar: Metadata Management’s Impact on Data Governance
Download the slides here>> About the Webinar Explore the powerful synergy between metadata management and Data Governance to elevate your governance efforts to new heights. Learn how to leverage metadata management to strengthen your Data Governance framework and ensure data-driven success. Join Bob Seiner for an engaging webinar where he will explore the pivotal role […]
Data Detection and Response (DDR): The Future of Data Security
There’s a unanimous consensus that data is the lifeblood of organizations. From customer records to intellectual property, the explosion of information creates tremendous value – and equally tremendous risk. The pace of cyberattacks accelerates relentlessly, with disastrous data breaches becoming a mainstay in news headlines and the associated costs skyrocketing. Current approaches to data security are […]
Ask a Data Ethicist: How Can We Address the Ethics of Reusing Data?
Reusing data is a fundamental part of artificial intelligence and machine learning. Yet, when we collect data for one purpose, and use it for other purposes, we could be crossing both legal and ethical boundaries. How can we address the ethics of reusing data? Understand Your Data Before we address the issue of reuse, we […]
Case Study: Establishing a Data-Literate Culture
Imagine a rapidly expanding small business with a 20% yearly growth tasked with establishing and maintaining a data-literate culture. Then, add a new Data Architecture upgrade with considerable changes to the business logic to this situation, causing a full-on panic. This journey, marked by confusion over data definitions and anxiety over system changes, describes the situation that Brooke Gajownik, director of […]
How to Ensure Data Quality and Consistency in Master Data Management
In the digital age, organizations increasingly rely on data for strategic decision-making, making the management of this data more critical than ever. This reliance has spurred a significant shift across industries, driven by advancements in artificial intelligence (AI) and machine learning (ML), which thrive on comprehensive, high-quality data. This evolution underscores the importance of master […]
Demonstrating the Value of Data Governance
As organizations strive to become more data-driven, they increasingly recognize the importance of Data Governance (DG), a business program supporting harmonized data activities. However, business leaders, colleagues, and workers often express confusion about DG policies and need clarity around its value. This article tackles this issue by exploring the top 10 ways for effectively articulating the value […]
What Is a Data Dictionary? Definition and Benefits
A data dictionary describes data in business terms, including information about the data. It includes elements like data types, structure details, and security restrictions. Unlike business glossaries, which focus on data across the organization, data dictionaries support data architectures – the technical infrastructures that connect a Business Strategy and Data Strategy with technical execution. This support references high-quality metadata that describes data platform attributes […]
Data Integration Tools
Data integration tools are used to collect data from external (and internal) sources, and to reformat, cleanse, and organize the collected data. The ultimate goal of data integration tools is to combine data from a variety of different sources, and provide their users with a single, standardized flow of data. Use of these tools helps […]