Analytics covers the analysis of data in its broadest sense, including its collection, measurement, analysis, visualization and interpretation.
API (Application Programming Interface)
An API is an interface that allows computer programs to automatically interact under specified, documented conditions, without human intervention.
Big data covers the technologies, methods and processes used to collect and analyze the enormous volumes of data now produced by organizations.
Chief Data Officer
The Chief Data Officer (CDO) is the senior executive responsible for how an organization utilizes and governs data to drive maximum business value.
A data analyst collects, processes and analyzes an organization's data, ensuring data is used as a decision-making tool.
The data architect designs and manages an organization's data architecture, which collects, stores, processes, analyzes and shares all data.
A data architecture provides a framework for collecting, storing, sharing, processing, analyzing and reusing data, thus turning it into value.
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 (or data cleaning) is the process of identifying and fixing incorrect, incomplete, duplicate, unneeded, or invalid data in a data set.
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 are management tools that collect and display metrics, such as key performance indicators, to monitor and improve business activities.
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 gathering is the systematic, methodological process of collecting raw data from inside and outside an organization.
Data governance covers how you identify, organize, handle, manage, and use data collected in your organization, reducing risk and enabling agility.
Data innovation is the use of data and analytics to create new added-value products, solutions, processes, organizational methods and markets.
Data integration covers bringing together data from multiple different sources, making it more actionable and useful to those who access it.
Data join involves combining multiple datasets into one, increasing the relevance of data and enabling deeper analysis.
Data lineage (or data traceability) provides full visibility of the data lifecycle inside and outside the organization, including any changes made.
Data literacy is the ability to read, understand, work with, analyze and communicate with data, turning it into meaningful, relevant information.
Data mesh is a decentralized, federated approach to data management that enables data sharing and data democratization across the organization.
Data mining is the analysis of huge volumes of data to find hidden patterns, anomalies, or correlations, predicting future trends and opportunities.
A data producer is the root source of data. It can be a person manually entering data, an automated service, or a device/machine that gathers data.
A data product is a product built around data, containing everything required to complete a specific task or objective using that underlying data.
Data quality is a measure of the condition of data, based on areas including accuracy, completeness, timeliness, consistency and reliability.
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 is the practice of extracting and applying valuable information and insights from large volumes of structured and unstructured data.
A data steward helps implement a good data governance strategy across their organization to guarantee the quality, usability, and security of data.
Data storage is the retention of digital information on recording media, so that it can be accessed by computers or other devices for future use.
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.
In a data-driven organization employees across all departments rely on insights from data to support strategic and operational decision making.
Database management systems (DBMS)
A database management system (DBMS) is software that allows data to be stored, retrieved, sorted, deleted, modified or used.
GDPR – General Data Protection Regul...
The General Data Protection Regulation (GDPR) is legislation designed to protect and control the use of personal data in the EU and other countries.
Geographic Information System (GIS)
A Geographic Information System (GIS) is an information system that gathers, manages and analyzes spatial and geographic data.
Metadata is data that gives a description of other data. This provides context to make it more easily understandable and usable.
No-code solutions enable non-specialists without programming skills to quickly and easily develop and publish full software applications.
Open data is data which is shared, openly accessible and exploitable for any purpose by everyone (including companies, citizens, media, or consumers)....
Open data portal
An open data portal is an online portal used by both public and private organizations to share data externally with their audiences.
Self-service data enables everyone within an organization or ecosystem to independently access, query and gain insights from data.
A smart city is an area that uses technology and data to improve the citizen experience, increase efficiency, innovate, and meet its wider objectives.
Smart grids aim to optimize the production, distribution and consumption of electricity through connected technology, including networks and sensors.
Smart parking uses digital technologies to optimize vehicle parking, saving time, reducing pollution and improving the driving experience.
A sovereign cloud is a cloud environment that is physically located within one country, facilitating compliance with local laws.
Standardized data is data from different sources that has been transformed into a consistent, standards-based format, allowing meaningful comparisons.