Data stewardship (DS) is the practice of overseeing an organization’s data assets to ensure they are accessible, reliable, and secure throughout their lifecycles. It is a framework of roles, responsibilities, and processes designed to support the organizational strategy through a data governance (DG) program. At its core, data stewardship comprises data stewards – formalized roles that take responsibility for their […]
What Is a Data Fabric?
Data fabric is an innovative approach to data architecture, and simplifies data management. At its core, data fabric is built on the principle of unification. This standardization serves two purposes: It creates a single-entry point for data consumers, and it enables seamless access to information, regardless of where that data is stored, computed, or administered. These outcomes happen through data […]
Improving Data Quality with Data Stewardship
To get value from data, data stewards must understand and apply business requirements. When business ambiguity arises about how to best serve data stakeholders, data stewards need to know how to find out this information and with whom to speak. By doing so, stewards can align fit-for-purpose data with business needs and improve data quality. Data stewards understand […]
What Is Master Data Management (MDM)? Definition, Components, Benefits, Uses
Master data management (MDM) is a set of practices and tools that help organizations define, unify, and manage their most important shared data assets. MDM provides a single, trusted view of key business entities like customers, products, and suppliers, ensuring data consistency and accuracy across all systems and departments. By ensuring master or “golden” records […]
What Is Data Literacy? Definition, Components, Uses
Data literacy (DL) describes how well an individual or organization understands, works with, analyzes, visualizes, and applies data to reach their goals. The specific context and use case determine what applying data literacy looks like in practice. For example, while reading visualizations on product deliveries provides value, true data literacy involves going further. It involves actively […]
What Is a Graph Database? Definition, Types, Uses
A graph database (GDB) models data as a combination of nodes (vertices) and edges (relationships) with equal importance. Businesspeople query these structures to reveal patterns and insights within the data and their associations. These would be difficult to discern from other data visualizations, such as tables, charts, and documents. Since humans naturally think by associating one concept with another, people […]
Automated Data Management Tools
“Why?” a chief technology officer (CTO) may ask when the subject of automated Data Management tools arises. After all, their organization has probably already been storing, archiving, and backing up enterprise data day after day with success. For example, setting up a Database-as-a-Service (DBaaS) from a reputable cloud computing provider, with appropriate access to data, […]
What Is Data Privacy? Definition, Benefits, Use Cases
Data privacy describes a set of principles and guidelines to ensure the respectful processing, protection, and handling of sensitive data linked to a person. This concept ties to who can define, observe, use, and control a person’s information and how. Typically, privacy spans two types of levels: implicit rules and written legislation. Implicit rules cover norms, behaviors, and values […]
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 Architecture Trends in 2024
Data Architecture, the corporate infrastructure connecting business and data strategies, will face competing priorities in 2024. On the one hand, nearly half of organizations will gravitate toward modernizing their data architectures to increase operational real-time analytics and enable AI and ML (machine learning) capabilities. Simultaneously, with concerns about AI impacts, about 80% will prioritize security and Data Governance in […]