Business Intelligence key terms, Explained

The sections below provide the elementary definitions and, in some cases, relevant examples of various key terminologies used in the business intelligence domain. While there are several terminologies that are used in this domain, the terminologies below have been chosen based on the frequency of usage and relative importance.

Business Intelligence Key terms

Business Intelligence Key terms

Ad Hoc Query

Sometimes, users may need to find out certain information ad-hoc. Such requirements are not pre-planned. For example, if the system has been facing some unusual issues, the IT manager may want to see the anti-virus scan logs for the past two weeks. To find out such information, ad hoc queries are sent to the BI or analytics software.


When a file or information is sent over the Internet, it leaves a trail of data using which, information about the file and its sender can be found. Depending on the reason, the trail is picked up; it can be a serious privacy concern. Anonymization helps wipe out such trail. The identity of the person sending such files cannot be tracked.

Academic Analytics

It is the application of BI tools, processes and strategies for the improvement in educational institutions. Academic analytics helps people in charge of strategic planning in an educational institution to identify with the help of analytics the strengths, weaknesses of a student and course of actions and find ways to improve the overall operations, processes and revenue of the educational institutions. For example, the Learning Management Systems (LMS) can provide data about the performance of students.

Multipolar analytics

A big data model in which the big data in an organization are collected, stored and analysed in different locations instead of doing the same activities in a central location.

Behavioral Analytics

Behavior analytics or User Behavioral Analytics is the tracking, collecting and assessing of user activities and data with the help of monitoring systems. The main purpose of these actions is to identify unusual or suspicious behavior and assess their impact on an organization or any other entity. To do that, monitoring systems analyse historical data logs such as network and authentication logs. Typically, monitoring systems establish a baseline of user behavior or what constitutes normal behavior and assesses all activities based on the baseline. Monitoring systems may assess certain behavior as less or more risky depending on variousparameters. The monitoring systems do not take any action based on its assessment; it just sends its assessment to stakeholders.

Business Process Management (BPM)

BPM is a systematic approach to bring improvements in the various business processes an organization follows. A business process is an activity or a set of activities performed in an organization to achieve a specific goal. For example, the goal of the HR department in an organization is to provide ratings to employees based on objective, data-based feedback. To do this, the HR department does multiple activities such as data or feedback collection, feeding the data into systems and coordinating with other departments. The goal of BPM is to reduce human errors and miscommunication and improve productivity and quality.

Business Service Provider (BSP)

A company that provides customized third-party software applications to its customers on a rental basis. BSPs are ideal for sourcing software applications that can execute specific business processes such as payroll and bookkeeping. Organizations that rent such software applications request customizations according to their needs. BSPs are suitable for companies with small budget.  Examples of reputed BSPs are Agillon, eAlity, Employease and EConvergent.

Corporate Performance Management (CPM)

It is the practice of monitoring and managing the performance of an organization based on key performance indicators (KPIs) such as return on investment (ROI), overhead, revenue and operational costs. Till a certain time, CPM was used within the finance department but now it is used to measure the performance of the whole organization. A CPM software is a dashboard that displays various metrics and functions such as individual and project performance relative to corporate strategies and goals and graphical scorecards and dashboards.

Cubes or Data Cubes

A cube or data cube is a method of storing data in multidimensional form which is helpful in analytics. When a cube is stored, the data can be viewed from multiple dimensions and new dimensions of analytics can be unearthed. Cubes are often summarized before queries are run on it which enables faster processing and extraction of results. The name of the query language used on cubes is Multidimensional Expressions (MDX).


It is a data visualization tool that displays the current status of the metrics and KPIs for an enterprise. Basically, a BI dashboard provides information about the performance of an organization based on the KPIs it has set. Data from KPIs are usually presented on a single screen and employees can view the information with multiple dimensions using features such as filtering and other functionalities. The information can be accessed based on roles and privileges. Additionally, the dashboard can display data by pulling data from multiple sources on a real-time basis.

Data Warehouse

It is physical or logical repository for all the data collected by the different business systems in an organization. Data warehouses store huge volumes of diverse data that may be of interest to different groups of employees in the organization. In a sense, a data warehouse can be considered collection of data marts. There are two approaches to create a data warehouse — top down and bottom up. In the top down approach, first the data warehouse is created and then multiple data marts are created according to the requirements of different users whereas in the bottom up approach, the data warehouse is created after the data marts are created.

Data Mart

A data mart is a location where data is stored and such data is meant to serve a particular group of knowledge workers. Though the terms data mart and data warehouse are confusing, they are not the same. While a data warehouse stores data related to an entire organization, a data mart stores data that caters to a specific group of employees such as the Human Resources department. Data in a data mart are usually customized to suit the unique needs of a specific group of people. Today, software systems have been designed to create data marts by pulling data from disparate sources and then customizing them to suit the needs of specific people. Data marts are often built to perform specific analytics tasks.

Embedded Analytics

Business software applications such as the Customer Relationship Management (CRM), marketing automation financial systems and enterprise resource planning (ERP) can have embedded BI functionalities and capabilities. When this happens, users find it easier to access BI tools and functionalities such as dashboards, visual workflows, self-service analytics, data visualization tools, static and interactive reports, benchmarking, and mobile reports.

Google Analytics

It is a free web analytics tool offered by Google that is especially useful for search engine optimization. The tool offers multiple features such as data visualization, segmentation, customized reports and integration with other Google products such as AdWords and Website Optimizer.

Contextual Data

Contextual data helps make information more meaningful and actionable by providing relevant data. Contextual data is used in a variety of businesses or industries. For example, an ice cream parlour wants to find out the reason it is not selling enough ice creams during the summer. So, the location of the parlour is used as contextual data and found that it is located near the schools and universities which are closed during the summer season.

Balanced Scorecard

A performance metric used to assess the performance of the various internal functions of a business and identify steps to improve performance.

Key Performance Indicator (KPI)

A KPI is an important business metric that is used to measure the performance or the health of an organization. KPIs vary by organizations as each organization devises its own set of KPIs. For example, a telecom firm can have customer churn percentage as a KPI while the government can have educated unemployment rate as a KPI. Most of the times, a company’s vision and performance benchmark are driven by relevant KPIs.

Prescriptive Analytics

It is the practice of suggesting solutions to problems based on successful methods in solving problems in the past. Prescriptive analytics systems draw heavily from data derived from successful strategies and apply them in current situations.

Slice and Dice

A technique of breaking down information into smaller chunks so that more information can be gained from the object. The technique also helps in adding more perspectives about the data and find solutions to problems. In IT parlance, this technique is also known as drilling down.

Data point and Data visualization

It is an item on the chart having relevant data. In practical scenario there are multiple data points available on a graph or chart. Data visualization is nothing but the pictorial representation of the data in different visual forms like maps, charts etc.


This is actually the view of data at any particular point of time. So, a snapshot is relevant for the time when it is taken only and it varies in the next moment.

Gap Analysis

It is basically a study to identify the data gaps or missing data which is required for BI and reporting.

Drill Down

It is the process of clicking on an item and navigates through the hierarchy to get more details and explanation of the data.


It is the process of combining business intelligence, predictive models, data input etc to forecast the probable future trends.


It measures the performance based on different parameters. Metrics can be defined for various BI KPIs.

Data Mining

It is a process, based on complex algorithm and logic to search the data and find possible patterns and their relationships.


The above terminologies are frequently used in the BI domain and for a first-timer in this domain; the definitions could be a good place to start with. Ideally, one should delve deeper into the domain after gaining an idea of the various concepts given here. Hope this guide will help to understand the key terms frequently used in BI world.



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