Business Analytics/Business Intelligence Definitions

This glossary explains the meaning of key words and phrases that information technology (IT) and business professionals use when discussing business analytics and related software products. You can find additional definitions by visiting WhatIs.com or using the search box below.

  • C

    citizen data scientist

    A citizen data scientist is any individual who contributes to the research of a complex data initiative but who does not have a formal educational background in data analytics (DA) or business intelligence (BI).

  • cloud analytics

    Cloud analytics is a service model in which one or more key element of data analytics is provided through a public or private cloud.  Cloud analytics applications and services are typically provided through a subscription-based or utility (pay-per-use) model.

  • collaborative BI (collaborative business intelligence)

    Collaborative BI (collaborative business intelligence) is the merging of business intelligence software with collaboration tools, including social and Web 2.0 technologies, to support improved data-driven decision making.

  • customer analytics (customer data analytics)

    Customer analytics, also called customer data analytics, is the systematic examination of a company's customer information and customer behavior to identify, attract and retain the most profitable customers.

  • customer intelligence (CI)

    Customer intelligence (CI) is information derived from customer data that an organization collects from both internal and external sources.

  • D

    d3.js (data-driven documents)

    D3.js (data-driven documents) is a library of JavaScript code that enables users to input their own data into prebuilt visualizations. The code allows users to generate graphics in frequently used web formats like HTML, CSS and SVG.

  • data artist

    A data artist is a business analytics (BA) specialist who creates graphs, charts, infographics and other visual tools that help people understand complex data.

  • data exploration

    Data exploration is the first step in data analysis and typically involves summarizing the main characteristics of a data set, including its size, accuracy, initial patterns in the data and other attributes.

  • data journalism

    Data journalism in an approach to writing for the public in which the journalist analyzes large data sets to identify potential news stories.

  • data preparation

    Data preparation is the process of gathering, combining, structuring and organizing data so it can be analyzed as part of data visualization, analytics and machine learning applications.

  • data sampling

    Data sampling is a statistical analysis technique used to select, manipulate and analyze a representative subset of data points to identify patterns and trends in the larger data set being examined.

  • data science as a service (DSaaS)

    Data science as a service (DSaaS) is a form of outsourcing that involves the delivery of information gleaned from advanced analytics applications run by data scientists at an outside company to corporate clients for their business use.

  • data visualization

    Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software.

  • decision-making process

    The decision-making process, in a business context, is a set of steps taken by managers in an enterprise to determine the planned path for business initiatives and to set specific actions in motion.

  • deep analytics

    Deep analytics is the application of sophisticated data processing techniques to yield information from large and typically multi-source data sets comprised of both unstructured and semi-structured data.

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