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Glossary

Data Analyst

A data analyst collects, processes and analyzes an organization's data, ensuring data is used as a decision-making tool.

Data architect

The data architect designs and manages an organization's data architecture, which collects, stores, processes, analyzes and shares all data.

Data Architecture

A data architecture provides a framework for collecting, storing, sharing, processing, analyzing and reusing data, thus turning it into value.

Data catalog

A data catalog is an inventory of all data within an organization. This enables internal and external users to easily find and access information.

Data cleansing

Data cleansing (or data cleaning) is the process of identifying and fixing incorrect, incomplete, duplicate, unneeded, or invalid data in a data set.

Data culture

A data culture is where everyone in an organization relies on, and uses, data within their working lives for decision making, planning and operations.

Data dashboards

Data dashboards are management tools that collect and display metrics, such as key performance indicators, to monitor and improve business activities.

Data ethics

Data ethics covers the ethical and moral obligations of collecting, sharing, and using data, focused on ensuring that data is used fairly, for good.

Data governance

Data governance covers how you identify, organize, handle, manage, and use data collected in your organization, reducing risk and enabling agility.

Data innovation

Data innovation is the use of data and analytics to create new added-value products, solutions, processes, organizational methods and markets.

Data integration

Data integration covers bringing together data from multiple different sources, making it more actionable and useful to those who access it.

Data join

Data join involves combining multiple datasets into one, increasing the relevance of data and enabling deeper analysis.

Data lineage

Data lineage (or data traceability) provides full visibility of the data lifecycle inside and outside the organization, including any changes made.

Data literacy

Data literacy is the ability to read, understand, work with, analyze and communicate with data, turning it into meaningful, relevant information.

Data Mesh

Data mesh is a decentralized, federated approach to data management that enables data sharing and data democratization across the organization.

Data mining

Data mining is the analysis of huge volumes of data to find hidden patterns, anomalies, or correlations, predicting future trends and opportunities.

Data quality

Data quality is a measure of the condition of data, based on areas including accuracy, completeness, timeliness, consistency and reliability.

Data Reuse

Data reuse is when information is reused for purposes other than the one it was initially collected for. This creates new value from the data.

Data science

Data science is the practice of extracting and applying valuable information and insights from large volumes of structured and unstructured data.

Data steward

A data steward helps implement a good data governance strategy across their organization to guarantee the quality, usability, and security of data.

Data-as-a-Service / Data Service

Data-as-a-Service (or DaaS) is a business model where organizations offer customers and partners access to their data, normally through subscription.

Database management systems (DBMS)

A database management system (DBMS) is software that allows data to be stored, retrieved, sorted, deleted, modified or used.

Dataset

A dataset is a collection of related data points, providing data in an understandable form to be shared and reused internally and externally.