Learn what business intelligence (BI) is and what it is used for here. We also discuss business intelligence tools and business intelligence analytics.
In the age of digitalisation and data analysis, companies are turning to business intelligence as the foundation of the decision-making process. We talk about what business intelligence is, what business intelligence tools exist and how they relate to data analytics.
If you work in or run a company, you have probably heard of business intelligence and use it in your daily basis. Nearly all companies already use business intelligence, especially to make decisions.
Business intelligence or BI has become the cement on which all the pillars of a business are built. In an increasingly competitive market, making informed decisions based on quality data is crucial to ensure business growth and differentiate from the competition.
What is business intelligence (BI)?
Being literal, business intelligence is a type of intelligence that helps companies make better decisions and improve their business.
Business intelligence can also be described as the capacity to transform information into valuable knowledge or, in other words, into productive intelligence that helps an organisation make better decisions, generate business opportunities or optimise operations, tasks or processes.
In practice, business intelligence refers to the use of data analysis tools and techniques to gather, process, and transform raw data into meaningful and actionable insights. These insights are then used by businesses to make informed decisions, identify trends, patterns, and opportunities, and gain a deeper understanding of their operations, customers, and market dynamics. Business intelligence helps organizations to improve their overall efficiency, optimize processes, and achieve their goals by leveraging data-driven insights.
In simple terms, business intelligence is using data analytics to make better decisions and improve a business performance.
What is the main purpose of business intelligence?
The main purpose of business intelligence is to help businesses make better, data-driven decisions. By gathering, analyzing, and presenting relevant data and insights, business intelligence enables organizations to understand their performance, identify trends, uncover opportunities, and optimize their operations. It empowers businesses to act strategically, improve efficiency, and stay competitive in their respective markets.
Ultimately, the goal of business intelligence is to provide actionable information that supports decision-making and drives business success.
History and transformation of business intelligence
Although it seems to be a concept from the 21st century, the term business intelligence appeared for the first time in the Cyclopaedia of Commercial and Business Anecdotes, published in the United States in 1865.
Business intelligence was already being used in the 1960s. At that time, it was used to refer to the system that made it possible to share information between companies. In the 1980s, with the Internet's appearance in 1983, business intelligence started to be linked to technology and computer models.
In the 1960s and 1980s, business intelligence was used to support the business decision-making process, albeit in a much more rudimentary and less efficient way than today. In the 1960s, companies used business intelligence to gather information about competitors and to predict market trends and adapt their offers to those of other companies. In the 1980s BI started to develop in the technological and digital environment, although it was far from reaching the level of correlation with data and IT that prevails today.
The proliferation of BI as we know it today began in the 1990s along with the early commercialisation of business intelligence tools. However, in the 1990s business intelligence was not easily accessible as the tools at the time were very difficult to use and required IT specialists.
With the beginning of the new decade in the 2000s, software vendors realised the potential of BI and analytic tools and the supply of business intelligence software and applications began to expand. With the increase in supply came improvements. Vendors realised the need to create tools that were intuitive, easy to use and allowed business and non-technical users to collect, integrate and analyse information and data without having to rely on the IT department.
In the last decade, the application of business intelligence in business environments has advanced to the point where business intelligence is now almost as necessary as a computer to run a business. In this context, business intelligence tools and systems have not only multiplied, but have also greatly improved their capabilities.
However, challenges remain. Although technology has advanced, today we produce more data than ever before, so the complexity that once revolved around accessing data now lies in the overproduction of data, in determining which data is useful in the massive processing of data, and in knowing how to leverage the value of the data available.
Although organisations collect more data than ever before, transforming data into valuable information is also much more complex than ever before. The more information we have —data assets, data sources, systems, data repositories, etc.— the more difficult it is to understand and to be able to draw conclusions from it. This is why today business intelligence requires data processing techniques and strategies, such as interoperability, data integration, system integration, data governance, etc.
What is the difference between business intelligence and data analytics?
Business intelligence (BI) and data analytics are pretty similar concepts that are, in fact, related to one another. They both involve data processing and data analysis, but they are not exaclty the same.
Business intelligence is the generation of actionable insights that help companies make better decisions while data analytics is one of the techniques used to produce business intelligence. That is to say, business intelligence is a broader concept than data analytics and, while it definitely encompasses data analysis, it also involves other data-related processes.
Some also differentiate between the two in terms of their purpose. According to that perspective, while business intelligence primarily aims to provide valuable insights to support decision-making within an organization, data analytics is centered around exploring and extracting knowledge from data to identify patterns, correlations and trends.
Business intelligence analytics
Obviously, obtaining business intelligence requires complex processes closely linked to technology and data. Nowadays we cannot talk about business intelligence without also talking about data analytics.
Data analytics is the foundation of business intelligence. Data has become the commodity of organisations when it comes to generating knowledge and valuable information. Data analysis is the process by which companies transform data into information and information into insights.
However, technological progress places us in a context in which business intelligence goes far beyond data analysis and already involves more complex processes such as data mining and different types of artificial intelligence such as machine learning or deep learning, etc. The possibilities for companies to generate intelligence are now endless.
In the end, though, they all serve the same purpose: using data to make better data-driven decisions, optimise business strategies, generate opportunities, drive continuous progress, solve productivity issues and adapt as quickly as possible to market and customer changes.
Business intelligence is a long-term project —practically endless and always cyclical— that starts with data collection, goes through data analysis and culminates in data visualisation and the presentation of the information through dashboards, reports or other interactive reporting and visualisation systems.
Business intelligence tools
As we have already noted, there are a large number of business intelligence tools on the market. The proliferation of the tools available makes it harder for companies to choose one.
To choose the right BI tool companies must not only consider the capabilities of each tool, but also the amount of data they have, the complexity of the processes they want to carry out and their business needs.
Las grandes consultoras tecnológicas actúan como agente divulgador y sirven de ayuda a las organizaciones a la hora de elegir una herramienta. Gartner, una de las mayores consultoras del mundo, publica cada año un informe listando las herramientas de análisis y BI líderes del mercado. En el último Cuadrante Mágico de Gartner, Microsoft se posicionó como el líder absoluto del cuadrante gracias a su conjunto de herramientas Power BI.
Large technology consultancies act as a broker and help organisations when it comes to choosing a tool. Gartner, one of the world's largest consulting firms, publishes an annual report listing the leading BI and analytic tools on the market. In the latest Gartner Magic Quadrant, Microsoft was ranked as the absolute leader thanks to Power BI.
As a preferred Microsoft Power BI partner, Bismart relies on Power BI and Microsoft technology to develop its business solutions and to offer the best service and technical capabilities to its customers. However, not all companies are the same and not all need the same tools. There are many possibilities, but choosing well is key.
Not sure which BI tool is right for your company? Our team of experts can help you!
