The term Business Intelligence (BI) has gained relevance among companies that want to remain competitive and up-to-date with the latest digital transformations and has replaced designations such as Decision Support Systems. BI systems combine data collection, storage, and knowledge management with various analytical tools.
BI systems have been part of the evolution of IT in organizations and combine the collection, storage, and processing of data through analytical tools to present complex and competitive information to managers and decision makers. Therefore, BI systems use the data within organizations to provide relevant information for different purposes.
Business Intelligence: what is it?
BI is a process of gathering, organizing, sharing, monitoring and analyzing large amounts of information. Organizational processes generate a significant amount of data and BI systems promise to take advantage of this data by transforming existing raw data into useful information to support decision-making and promote increased knowledge within the organization based on data analysis, which allows the improvement of the organizational strategy.
BI systems have a presence in a number of business sectors, for example, retail, financial, telecommunications, transportation, education, healthcare, e-commerce, and insurance.
From this interpretation of trends and through the analysis of data or the use of forecasting techniques (eg, data mining), BI systems can develop strategies and business opportunities, aiming (in the short term) the competitive advantage in the market and stability (in the long-term). Thus, through the use of BI, organizations guarantee quality and promote the creation and dissemination of knowledge.
Business Intelligence: how does it work?
BI is a meeting point between business, management and information technology. It is through the integration of these sectors into a modus operandi that the BI can be found. BI technologies provide a history, as well as predictable and prescriptive analysis of different business operations.
For example, a company that wants to improve its supply chain needs BI to find out where the delays are occurring (in which products and on what means of transport), and where there are variations in the shipping processes.
If the first sources of information are collected within the companies themselves, the second sources of information may already include consumer needs, their decision-making process, competitive strategies, industrial, economic and technological conditions.
Associated with BI systems are the following concepts: data warehouse – integrated repository that stores data relevant to decision making, extraction, transformation and loading processes that are responsible for automating the complex integration of operational data that regularly feed the data warehousing; online analytical process – encompasses a set of analytical operations on typically multidimensional data; data mining – is used as a technique to extract knowledge from data and can be seen as the process of discovering patterns and knowledge of a vast amount of data; and Data visualization in this component typically uses reports, dashboards (interactive visualizations), and scorecards.
BI tools and functions
There are different BI tools, among the best known are the tools from Microsoft, Qlik, Tableau or Zoomdata. BI can relate to integrated systems such as Enterprise Resource Planning (ERP).
Companies and institutions choose tools based on factors such as the size and complexity of their operations, as well as the type of technology they already have. The most common BI functions include reporting, analysis, complex event processing, business performance management, benchmarking, or data mining.
BI working in companies
With BI it is possible, among others, to analyze trends and discover patterns, eliminating duplication of tasks and achieving cost reduction and optimization of work.
The application of BI allows companies a proactive and non-reactive approach, acting with less uncertainty towards the future since you can understand with more precision what is happening and why.
The aim of the Business Intelligence Platform for Data Integration project was to develop an integrated data system that allowed the development of the Organizational Data Warehouse through an iterative process, contributing to increase the quality of the operations of the plant, in terms of access efficiency and the quality of critical information required for decision-making and stakeholder involvement, upstream and downstream of the value chain.
Business Intelligence (BI) and Business Analytics (BA)
The Business Analytics (BA) area is strongly related to the Business Intelligence area, presenting several similarities and can be seen as a more comprehensive area, even if it encompasses BI technologies.
BA can be defined as an area that deals with operations performed on data whose purpose is to support business activities, such as the decision-making process, hence the great relationship between Business Analytics and Decision Support Systems.
The BA area contains three broad guidelines:
- descriptive analysis, which uses the data to perceive what happens in the past, highlighting BI techniques and technologies (reports, dashboards, OLAP cubes);
- predictive analysis uses the data and techniques to discover patterns and aims to answer questions related to possible future occurrences, such as Data Mining, Web / Media Mining, Time Series Forecasting techniques, among others;
- prescriptive analysis, that typically encompasses optimization algorithms, simulation tools, and Group Support Systems, for example.
In recent times, the concept of Business Analytics has come to be used to encompass several emerging concepts, such as:
- Big Data Analytics;
- (Cloud-Based) Predictive Analytics;
- Text and Social Media Analytics;
- Self-service Analytics;
- Pervasive Analytics;
- Data Stream Management and Real-time Analytics;
- Mobile and Sensor-based Analytics;
- Web-based Analytics.
Revalidation of BI: what the future will bring…
In the near future, we may come to have a sort of “augmented analysis”, where machine learning is embedded in the software and will guide users in their data searches. It will be a mix of BI and BA, and it will certainly be smart.
This way you will be able to look at last year’s numbers (BI) and at the same time get next year’s sales forecasts (BA), with the ability to evaluate how you would act in the form of A, B or C.
It will be a clearly attractive future.