In the big data era, businesses are generating and collecting more data than ever before. This data can be a valuable resource for making better business decisions, but it can also be overwhelming and difficult to manage. A data glossary can help to make sense of this data by providing a central repository for definitions of key terms and concepts. This can help to improve communication and collaboration between different departments within an organisation, as well as with external partners. A data glossary can also help to improve data quality by ensuring that data is consistently defined and used. This can lead to more accurate and reliable insights, which can help businesses to make better decisions.
As the industry is evolving fast, so will our Data Glossary, thus you can expect an updated version with the latest terms.
The development of intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
Large and complex data sets that cannot be processed using traditional data processing techniques.
The use of data and analytical tools to provide insights into business operations and decision-making.
The delivery of computing services such as servers, storage, databases, and software over the internet, rather than on local servers or personal computers.
Data refers to information, facts, or statistics that are collected, analysed, and interpreted to understand a particular phenomenon, process or behaviour.
The process of examining and interpreting data to discover useful insights and draw conclusions.
The design and organization of data structures, systems, and processes that enable efficient and effective data management and usage.
The process of managing the availability, usability, integrity, and security of data used in an organization.
The process of combining data from different sources and formats into a single, unified view for analysis and decision-making.
The process of acquiring, storing, protecting, and processing data to ensure its accuracy, completeness, and reliability throughout its lifecycle.
The process of transferring data from one system or format to another, often as part of a system upgrade or replacement.
The process of discovering patterns, correlations, and anomalies in large data sets using statistical and computational methods.
The process of creating a conceptual or logical representation of data structures and relationships.
The protection of personal and sensitive information from unauthorised access, use, and disclosure.
The degree to which data is accurate, complete, consistent, and relevant for its intended use.
The interdisciplinary field that involves extracting insights and knowledge from data using scientific and statistical methods.
The protection of digital data from unauthorized access, use, disclosure, disruption, modification, or destruction.
The physical or digital location where data is stored, such as a hard drive, server, or cloud storage system.
The plan and process for managing an organization’s data assets to achieve its business goals and objectives.
The graphical representation of data and information to communicate complex data in a clear and concise manner.
A central repository for storing and managing large volumes of data from various sources.
The network of physical objects embedded with sensors, software, and connectivity that enables them to collect and exchange data with other devices and systems.
A type of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed.
The use of statistical algorithms and machine learning techniques to analyze historical data and make predictions about future events.