What is Business Intelligence?

In the current digital era, every company must master the use of data analysis tools in order to differentiate itself and be able to compete in the market. All this in order to extract, understand the information and make the right decisions for the business.

If you want to find out more about this area, in this post we will discuss the concept of Business Intelligence and the elements that make it up.

Business Intelligence, what?

Business Intelligence refers to the set of tools and strategies oriented to the analysis of a company’s data with the main objective of improving strategies and favouring the company’s decision making.

This concept has become popular in recent years due to the boom in technology. And that is why the vast majority of companies have established the profile of a Data Scientist as essential in their staff.

Business Intelligence tools

These tools streamline the process for users to search, classify, analyse data to obtain the desired information and establish models that facilitate business decision making. They can be classified into three categories:

  • For data management: from extraction, transformation, debugging and standardisation, regardless of the origin of the data.
  • Applications for discovering new data: enables the collection and evaluation of new information (data mining) and the application of predictive analysis techniques to this information in order to develop future projections.
  • Reporting: When the information obtained is already processed, analyses are carried out that help organisations to visualise it graphically in order to produce reports.

In each of these categories, the 10 most commonly used tools on the market in business intelligence are: Microsoft Dynamics, IBM Cognos Analytics, SAP business intelligence, Oracle Business Intelligence, Tableau, Sisense, Clear Analytics, QlikView, Gooddata and Style Intelligence.

Advantages of BI

The major advantages you get from using certain tools to deal with Business Intelligence are:

  • Support decision making by selecting and manipulating the data that matters to you.
  • Obtaining an extended reporting capacity and a greater depth of analysis.
  • Acquisition of historical bases that allow the possibility of going back in time analysis.
  • Allows for future forecasts and projections.
  • The ability to carry out analyses combining external and internal information from different sources.
Felipe Calderero, Co-director of the Data Science Master, presents the programme.
If you are interested in this article, with the Master in Data Science you will acquire the necessary knowledge and tools to boost your professional profile.

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