10 Business Intelligence (BI) Terms Everyone Should Know

We all know that before taking a business decision, we need to analyze the situation. The better we do so, the more efficient our decisions are. 

Business intelligence provides useful insight into a broader perspective for making the decision that would be fast, relevant and efficient. Here is a basic vocabulary for those who want to improve their decision-making using business intelligence

What is Business Intelligence?

Business intelligence (BI) is the process of turning data into insights that can help inform and improve business decisions. BI can be used to identify trends, spot opportunities and potential risks, and make better-informed decisions about where to allocate resources.

BI tools and techniques include data mining, statistical analysis, predictive modeling, and machine learning. 

In recent years, BI has become increasingly important as businesses have come to realize the vast potential of data-driven decision making. When used effectively, BI can help businesses gain a competitive advantage by providing them with a deeper understanding of their data and their customers.

If you want to read more about business intelligence (BI), we recommend our post Introduction to business intelligence (BI), or check out all of our posts related to business intelligence

Let’s have a look at a basic vocabulary for Business Intelligence

1. Database

A database is a collection of data that can be accessed by computers. The data is usually organized into fields, records, and tables in a way that makes the data easy to find and use. 

For example, a database might store a list of customers and their contact information. This would allow a company to quickly look up a customer’s information when they need to. 

DBMS (Database Management System)

DBMS stands for Database Management System and is a piece of software that manages a database. It stores data in a database, organizes it, and provides access to the data. A DBMS is built on top of a database and provides a way to interact with the data in the database.

RDBMS (Relational Database Management System)

A relational database management system (RDBMS) is a database management system (DBMS) that uses relational techniques to store and retrieve data.

The term “relational” refers to the fact that the data in a RDBMS is stored in tables and that these tables are related to one another by means of foreign keys (more on that later on)

RDBMSs are the most common type of DBMSs, and they are used to store data for a wide variety of applications. Some of the most popular RDBMSs include Microsoft SQL Server, Oracle Database, IBM DB2, and MySQL.

2. SQL

SQL (Structured Query Language) is a database programming language used for managing data in relational database management systems (RDBMS). SQL allows you to query data, update data, and delete data in your database. It is a standard language for accessing and manipulating databases.

SQL is easy to learn and use, and it is a powerful tool for managing data. If you are working with a database, it is likely that you will need to know some SQL.

SQL in Business Intelligence

SQL is important for Business Intelligence for a number of reasons. 

• SQL allows you to access data stored in databases and make sense of it through query language. This means that you can use SQL to answer questions about your data, such as trends over time or relationships between different data points. 
• SQL is also important for Business Intelligence because it allows you to manipulate data in order to gain insights that would not be possible with data in its raw form. 
• Finally, SQL is a standard language that is widely used in the business world, which makes it easier to share data and insights with others.

3. Data Warehouse

A data warehouse is a central repository for all the data in an organization. It is used to store data from multiple sources in a format that can be accessed and analyzed by decision makers.

A data warehouse can be used to track trends, measure performance, and make predictions. It is an important tool for businesses to make data-driven decisions.

Data Warehouse in Business Intelligence

Data warehouses are an essential tool for business intelligence and data science. 

• Central location for all data: Data warehouses provide a single point of access to all of the data that is necessary for decision-making. Without a data warehouse, businesses would have to rely on multiple siloed databases, which would make it difficult to gain a holistic view of the business.
• Change over time: A data warehouse can also help you keep track of changes over time. This is important because it can help you identify trends and patterns that you might not be able to see if you only had data from a single point in time.

4. Key Performance Indicator (KPI)

Key performance indicators (KPIs) are a type of performance measurement that helps businesses track and assess their progress towards meeting their goals. 

KPIs can be used to measure any aspect of business performance, from sales and marketing to financial and operational factors. Organizations use KPIs to track progress, identify areas of improvement, and compare performance across time periods or against other organizations.

KPI:s in Business Intelligence

The use of key performance indicators (KPIs) is essential for any business intelligence (BI) strategy. KPIs provide a way to measure progress and success against specific objectives. 

There are many different KPIs that can be used, and the best ones for your business will depend on your specific objectives. However, some common KPIs used in BI include measures of customer satisfaction, financial performance, operational efficiency, and employee engagement.

By using the right KPIs, businesses can make informed decisions about where to allocate resources and how to improve their overall performance.

5. Dashboard

A dashboard is a graphical user interface (GUI) that provides consolidated information and tools in a single place. A dashboard is typically used to monitor and manage key performance indicators (KPIs), metric data, and other critical information.

It is a valuable tool for businesses as it provides visibility into vital data and insights that can help with decision making.

Dashboards can be static or interactive.

• Static dashboards display information in a static way, typically in the form of charts, graphs, and tables
• Interactive dashboards, on the other hand, allow users to interact with the data and tools on the dashboard

Dashboards can be customized to fit the specific needs of a business or individual.

Dashboard in Business Intelligence

Dashboards are one of the key tools in business intelligence because they provide a quick and easy way to visualize data. By displaying data in a graphical format, dashboards make it easy to see relationships and patterns that would otherwise be hidden in a large data set. 

Dashboards also make it easy to track progress over time and to see how different data sets interact with each other.

BI dashboards are used to make better decisions, improve operational efficiency, and drive growth. By bringing together data from multiple sources, dashboards give users a comprehensive view of their business.

There are many different types of dashboards, from simple to complex, and they can be used for a variety of purposes. For example, a sales dashboard might track revenue, conversion rates and average order value. A marketing dashboard might track website traffic, social media engagement and leads generated.

6. ETL

ETL stands for Extract, Transform and Load. It is a process used to collect data from various sources, clean and transform it, and then load it into a destination database. ETL is commonly used in data warehousing and business intelligence projects.

• Extract: The extract phase of ETL involves collecting data from various sources. This data can come from relational databases, flat files, web APIs, and more. 
• Transform: The transform phase of ETL involves cleaning and transforming the data. This data may need to be converted from one format to another, for example. 
• Load: The load phase of ETL involves loading the data into a destination database. This database can be a relational database, a NoSQL database, or even a data warehouse.

ETL in Business Intelligence

ETL mainly solves two of the key issues surrounding the data part of the Business Intelligence process.

1. Extract data: ETL allows you to collect and join all of these different data sources together into one place, like a data warehouse.
2. Transform: The transform functionalities of an ETL allow you to convert it into a usable format and standardize all of these different data formats. In addition, ETL allows you to clean and remove any errors from your dataset 

7. Primary and Foreign Keys

Primary and Foreign keys are key concepts (no pun intended) in relational databases, and therefore, commonly used in business intelligence

Primary Key in relational database

A primary key is a special type of key in a relational database. It is used to uniquely identify each row in a table. A primary key can be either a single column or a combination of columns. It must be unique, meaning that no two rows can have the same primary key value. A primary key can also be null, but only one row in the table can have a null primary key.

A primary key is used to index a table and to create relationships between tables. The most common type of relationship is a one-to-many relationship, which is when one primary key value is associated with multiple values in another table.

For example, a customer table might have a primary key of customer ID, and an order table might have a primary key of order ID.

Foreign Key in Relational Database

In relational databases, a foreign key is a column (or columns) that contains values that refer to the primary key of another table. The foreign key is used to link two tables together. By linking the two tables, the foreign key allows the data in the two tables to be related.

The foreign key is an important concept in relational databases, as it is used to implement relationships between tables. Foreign keys can be used to enforce referential integrity in a database. Referential integrity means that data in one table must be consistent with data in another table.

8. Data Pipeline

A data pipeline is a system for processing data. It is a set of data processing steps that are executed in a predefined order. A data pipeline can be used to automate the data processing steps that are required to extract, transform, and load data from one system to another.

A data pipeline can be used to process data in batch mode or in real-time. In batch mode, the data processing steps are executed on a schedule, such as once a day or once a week. In real-time, the data processing steps are executed as soon as new data is available.

In addition, data pipelines can be used to process data from a variety of sources, including databases, files, and streaming data. The data can be processed in a variety of ways, including filtering, sorting, and aggregation. 

Data Pipeline in Business Intelligence

Data pipelines are often used in business intelligence to extract, transform and load data from one or more data sources into a data warehouse or data mart.

Data pipelines are a key component of business intelligence (BI) systems as they allow businesses to collect and analyze data from a variety of sources to gain insights into their operations.

9. Cloud

Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, etc. 

Cloud in Business Intelligence

Cloud business intelligence, also called Cloud BI, is a term used to describe the use of cloud-based data and analytics solutions to help organizations make better business decisions. With cloud BI, businesses can access data and analytics tools from anywhere, at any time. 

Cloud BI is a flexible and cost-effective way to deploy BI tools and solutions. With cloud BI, businesses can avoid the high upfront costs of traditional on-premise BI deployments. Instead, they can pay for only the resources they need on a pay-as-you-go basis.

Cloud BI can be delivered in a number of ways, including software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS)

10. Data Mining

Data Mining is a process of discovering and extraction of new unknown information and patterns from the data. Basically, it involves analyzing data to find trends and patterns that can be used to make decisions. 

Data mining can be used to find hidden relationships between different items, to predict future events, or to, for example, make decisions about marketing, product development, or other business strategies.

There are many different data mining techniques, but some of the most common methods include clustering, decision trees, and neural networks.

Data Mining in Business Intelligence

Data mining is a central part of business intelligence as it involves sorting through large data sets to identify trends, patterns, and relationships. This information can then be used to make better decisions about a company’s operations, products, and services.

I like to view it as the insights part of business intelligence, where we have our data collected and perhaps visualized. We then apply various data mining techniques to uncover insights and new information from our data.

There are a variety of different techniques that can be used for data mining, and the most effective method will vary depending on the type of data being analyzed. 

Summary: Business Intelligence Vocabulary

To conclude, the 10 most common terms in BI that anyone interested in business intelligence (BI) should be familiar with: 

1. Database
2. SQL
3. Data Warehouse
4. Key Performance Indicators (KPI)
5. Dashboard
6. ETL
7. Primary and Foreign Keys
8. Data Pipeline
9. Cloud BI
10. Data Mining

If you want to learn more about a future career in business intelligence we highly recommend our comprehensive guide on different roles in BI

FAQ: Business Intelligence Terms