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.
A/B testing (split testing)
A/B testing, sometimes called split testing, is an assessment tool for identifying which version of something helps an individual or organization meet a business goal more effectively.
ad hoc analysis
Ad hoc analysis is a business intelligence (BI) process designed to answer specific business questions by using company data from various sources. A report helps stakeholders assess an event and formulate actionable next steps.
Advanced analytics is a broad category of inquiry that can be used to help drive changes and improvements in business practices.
An analytic database, also called an analytical database, is a read-only system that stores historical data on business metrics such as sales performance and inventory levels.
asset turnover ratio
The asset turnover ratio is a measurement that shows how efficiently a company is using its owned resources to generate revenue or sales.
Association rules are 'if-then' statements, that help to show the probability of relationships between data items, within large data sets in various types of databases.
BABOK Guide (Guide to the Business Analysis Body of Knowledge)
The guide to the Business Analysis Body of Knowledge, or the BABOK Guide, is a book from the International Institute of Business Analysis (IIBA) that provides essential support and direction to business analysts (BAs) by presenting a collection of the activities that comprise business analysis.
big data analytics
Big data analytics is the often complex process of examining big data to uncover information -- such as hidden patterns, correlations, market trends and customer preferences -- that can help organizations make informed business decisions.
BIRT (Business Intelligence and Reporting Tools)
BIRT (Business Intelligence and Reporting Tools) is an open source technology platform sponsored by the Eclipse Foundation that consists of a visual report designer and a runtime component for Java and Java EE environments.
Business analytics (BA) is the iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis.
business intelligence (BI)
Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.
business intelligence architecture
A business intelligence architecture is the framework for the various technologies an organization deploys to run business intelligence and analytics applications.
business intelligence competency center (BICC)
A business intelligence competency center (BICC) is a team of people that, in its most fully realized form, is responsible for managing all aspects of an organization's BI strategy, projects and systems.
business intelligence dashboard
A business intelligence dashboard, or BI dashboard, is a data visualization and analysis tool that displays on one screen the status of key performance indicators (KPIs) and other important business metrics and data points for an organization, department, team or process.
citizen data scientist
A citizen data scientist is an individual who does some data science work for an organization but doesn't hold the title of data scientist or have a formal background in advanced analytics, statistics or related disciplines.
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 behavior to identify, attract and retain the most profitable customers.
d3.js (data-driven documents)
Data curation is the process of creating, organizing and maintaining data sets so they can be accessed and used by people looking for information.
Data exploration is the first step in data analysis involving the use of data visualization tools and statistical techniques to uncover data set characteristics and initial patterns.
Data journalism in an approach to writing for the public in which the journalist analyzes large data sets to identify potential news stories.
Data mining is the process of sorting through large data sets to identify patterns and relationships that can help solve business problems through data analysis.
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 is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from.
days sales outstanding (DSO)
Days sales outstanding (DSO) is the measurement of the average number of days it takes a business to collect payments after a sale has been made.
A decision-making process is a series of steps taken by an individual to determine the best option or course of action to meet their needs.
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.
What is data preparation? An in-depth guide to data prep
Data preparation is the process of gathering, combining, structuring and organizing data so it can be used in business intelligence (BI), analytics and data visualization applications.
Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch or other device instead of waiting for the data to be sent back to a centralized data store.
embedded BI (embedded business intelligence)
Embedded BI (business intelligence) is the integration of self-service BI tools into commonly used business applications.
Ensemble modeling is the process of running two or more related but different analytical models and then synthesizing the results into a single score or spread in order to improve the accuracy of predictive analytics and data mining applications.
enterprise mashup (or data mashup)
An enterprise mashup is the integration of heterogeneous digital data and applications from multiple sources for business purposes. An enterprise mashup is also sometimes known as a business mashup or, less precisely, as a data mashup.
Funnel analysis is a way to measure and improve the performance of customer interactions in a step-wise progression from the initial customer contact to a predetermined conversion metric.
Google Advertising ID
Google Advertising ID is a piece of universally unique identifier code that allows mobile applications running on Android devices to identify users and gather data for the purposes of building profiles.
Google Analytics is a free web analytics service that provides statistics and analytical tools for search engine optimization (SEO) and marketing purposes.
heat map (heatmap)
A heat map is a two-dimensional representation of data in which values are represented by colors. Heat maps allow users to understand and analyze complex data sets.
In-database analytics is a scheme for processing data within the database, avoiding the data movement that slows response time.
In-memory analytics queries data residing in a computer’s random access memory (RAM) rather than data stored on physical disks. This results in vastly shortened query response times.
key performance indicators (KPIs)
Key performance indicators (KPIs) are quantifiable business metrics that corporate executives and other managers use to track and analyze factors deemed crucial to the success of an organization.
key results indicator (KRI)
A key result indicator (KRI) is a metric that measures the quantitative results of business actions to help companies track progress and reach organizational goals.
Lambda architecture is an approach to big data management that provides access to batch processing and near real-time processing with a hybrid approach.
location intelligence (LI)
Location intelligence (LI) is a business analysis tool capability that enables companies to gather geographic- and location-related data to better understand global, regional and local business trends.
Logistic regression is a statistical analysis method to predict a binary outcome, such as yes or no, based on prior observations of a data set.
MicroStrategy is an enterprise business intelligence (BI) application and software vendor.
In data mining, a named entity is a phrase that clearly identifies one item from a set of other items that have similar attributes.
Noisy data is meaningless data. The term was often used as a synonym for corrupt data, but its meaning has expanded to include data from unstructured text that cannot be understood by machines.
Noisy text is an electronically-stored communication that cannot be categorized properly by a text mining software program. Noisy text is often caused by an end user's excessive use of idiomatic expressions, abbreviations, chat and text acronyms or business-specific lingo.
Operational efficiency is the ability of an organization to reduce waste in time, effort and materials as much as possible, while still producing a high-quality service or product.
operational intelligence (OI)
Operational intelligence (OI) is an approach to data analysis that enables decisions and actions in business operations to be based on real-time data as it's generated or collected by companies.
process intelligence (business process intelligence)
Process intelligence is data that has been systematically collected to analyze the individual steps within a business process or operational workflow.
processing in memory (PIM)
Processing in memory, or PIM (sometimes called processor in memory), refers to the integration of a processor with Random Access Memory (RAM) on a single chip.
What is predictive analytics? An enterprise guide
Predictive analytics is a form of advanced analytics that uses current and historical data to forecast activity, behavior and trends.
Qlik is a software vendor specializing in data visualization, executive dashboards and self-service business intelligence products.
R programming language
The R programming language is an open source scripting language for predictive analytics and data visualization.
real-time business intelligence (RTBI)
Real-time business intelligence (RTBI) combines data analytics and various data processing tools to enable access to the most recent, up-to-the-minute relevant data and visualizations.
Revenue attribution is the process of matching customer sales to specific advertisements in order to understand where revenue is coming from and optimize how advertising budgets are spent in the future.
SAS Institute Inc.
SAS Institute Inc. is a software vendor that specializes in advanced and predictive analytics software applications, as well as business intelligence and data visualization offerings.
Scala (Scalable Language)
Scala is a software programming language that mixes object-oriented methods with functional programming capabilities. It was used to create the scalable Spark analytics engine.
Self-service analytics is an approach to advanced analytics that gives the ability to conduct analyses to business users, rather than data scientists.
self-service business intelligence (self-service BI)
Self-service business intelligence (BI) is an approach to data analytics that enables business users to access and explore data sets even if they don't have a background in BI or related functions like data mining and statistical analysis.
sentiment analysis (opinion mining)
Sentiment analysis systems help organizations gather insights into real-time customer sentiment, customer experience and brand reputation.
Social analysis is the practice of analyzing a situation or social problem through objective, systematic exploration.
social media analytics
Social media analytics is the process of collecting and analyzing audience data shared on social networks to improve an organization's strategic business decisions.
standard operating procedure (SOP)
A standard operating procedure (SOP) is a set of written instructions that describes the step-by-step process that must be taken to properly perform a routine activity.
text mining (text analytics)
Text mining is the process of exploring and analyzing large amounts of unstructured text data aided by software that can identify concepts, patterns, topics, keywords and other attributes in the data.
Text tagging is the process of manually or automatically adding tags or annotation to various components of unstructured data as one step in the process of preparing such data for analysis.
Unstructured data is information, in many different forms, that doesn't follow conventional data models, making it difficult to store and manage in a mainstream relational database.
The unstructured text collected from social media activities plays a key role in predictive analytics for the enterprise because it is a prime source for sentiment analysis to determine the general attitude of consumers toward a brand or idea.
Web analytics is the process of analyzing the behavior of visitors to a website.