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A visual representation of the most important information needed to achieve one or more objectives; consolidated on a single screen so information can be monitored at a glance.

Business intelligence systems that enable business users to access and work with corporate data even though they do not have a background in statistical analysis, business intelligence, or data mining.

The process of using data to understand past and current business performance and make informed decisions. It is the foundation of business intelligence and data-driven strategy.

The process of discovering patterns and knowledge from large amounts of data. It's often used for market research and customer segmentation.

Techniques that use statistical models and forecasting methods to understand the future and make data-driven decisions.

A data structure technique optimized for data warehousing tools. It is a logical design that outlines how data is stored in a database to answer business questions quickly and accurately.

The process of detecting and correcting (or removing) corrupt or inaccurate records from a record set or database. It includes identifying incomplete, incorrect, inaccurate or irrelevant data and then replacing, modifying or deleting this data.

The administration of data that describes other data, with the goal to provide context and meaning. It helps users understand the data source, its structure, uses, and origin.

The act of reviewing source data, understanding its structure, content, and interrelationships, and identifying potential for data projects. This is particularly important for ensuring data quality.

The process of combining data from multiple sources to create a cohesive, comprehensive view for analysis and reporting.

A process in database usage and especially in data warehousing that involves extracting data from outside sources, transforming it to fit operational needs, and loading it into the end target.

The process of collecting data from various sources and consolidating it into a single dataset that presents significant information in a visual context, which can help in analytical processing.

A subset of a data warehouse that is usually oriented to a specific business line or team. It can increase the end-user response time due to the reduction in volume of data.

A system used for reporting and data analysis, often considered a core component of business intelligence. It is a central repository of integrated data from one or more disparate sources.

Creating reports that provide information to help organizations with decision-making. These reports pull from data analysis, visualizations, and KPIs.

The graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends and patterns.

A method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

The practice of comparing business processes and performance metrics to industry bests and best practices from other companies.

A computing method that allows users to easily and selectively extract and query data to analyze it from different points of view.

A measurable value that demonstrates how effectively a company is achieving key business objectives. Organizations use KPIs to evaluate their success at reaching targets.

A business intelligence process designed to answer a single, specific business question. Users can create reports and data visualizations that are only meant for a one-time use.

Large sets of data that are analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

The combination of skills, technologies, applications and processes used by organizations to gain data-driven insights. These insights can be used to make strategic business decisions.

The overall management of the availability, usability, integrity, and security of the data employed in an organization. It establishes policies and procedures and plans for managing data assets.