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In a hypercompetitive and globalized world, there is more and more information to capture and learn. Companies are often overwhelmed with data, and until a few years ago it was difficult to manage. But this is no longer the case. Business Intelligence systems are present in the DNA of successful organizations. The now-famous BI allows companies to learn from their customers, their operations, their production, and their marketing processes. In this sense, it’s key that you learn how to structure your business intelligence software development projects.

Gartner defines a BI system as the set of applications, infrastructures, and tools that facilitate the access and analysis of information to improve and optimize decisions and organizational performance. In this sense, TechTarget affirms that it is a technology-driven process for analyzing data and presenting actionable information to help managers and other users make better-informed business decisions.


Business Intelligence Software Development.

With the popularization and evolution of business intelligence systems, more and more companies want to incorporate them into their structures. Although some canned services and programs allow a certain development of competitive intelligence skills in an organization, our experience in Huenei has shown us that these don’t allow us to exploit all the potential available. An ideal approach is the Ad Hoc development of software systems tailored to the specific needs of organizations. This is one of the challenges that we most like to face at Huenei.

But developing a business intelligence system for a company is not an easy task. The development team needs to specifically understand the needs of the organization and thus adapt them to a global structure of business intelligence.

In this article, we will focus on giving you a description of the components you should consider in your business intelligence software development projects. It is then the responsibility of the development team, such as Huenei’s, to adapt these components to the structure required by the organization.


Components of a BI System

  1. Data Sources

Data sources are the points of supply of potentially useful data for the analysis of a business process. These data sources can be internal, that is, found within the company’s system, or external.

Some examples of data sources in a Business Intelligence system are:

  • Databases.
  • Files.
  • Management systems, such as ERP, CRM, SCM, GIS, and so on.
  • Internet: websites, social media, and so on.
  • Information systems of the organization.
  • Information systems external to the organization but to which there is access: suppliers, customers, etc.
  • Data provided by the public administration, such as statistics on population, exchange rates, etc.
  • Data collected from sensors, mobile devices, and IoT, among others.


  1. ETL

The second layer of the architecture of a BI system in an organization is called ETL. In it, the data passes from the data sources of the previous step and reaches the organization’s databases. The acronym ETL refers to the three central activities of this instance: Extract, Transform, Load.

  • Extract refers to obtaining information from internal and external sources. We are talking about capturing data that can come from heterogeneous or homogeneous sources.
  • Transform is the filtering, cleaning, purification, homogenization, and grouping of the collected information. It is a set of unification rules to transform data from source to destination. Some examples are converting to a certain unit of measure, purging and cleaning inconsistent data, encoding, etc.
  • Load refers to the structurization and updating of data and metadata in the database. In other words, the data is entered into the corresponding storage place.
ETL Process

Illustration by BI Smart

  1. Data Store

Once captured, transformed, and loaded, the collected data is stored in data warehouses. There are different types of databases depending on the characteristics of the data they store, as well as their structure. As an example, below we will tell you about the most common structures.

  • Operational Data Store (ODS): this is an intermediate store between the ETL and the Data Warehouses, which allow large amounts of information to be stored in a sequential and orderly manner. You should understand them as intermediate instances, before their final storage.
  • Data Warehouse: it is a data repository that provides a global, common, and integrated vision of the organization’s data.
  • Data Mart: it is a subset of the data warehouses focused and of value for a certain department of the company. They are like small databases of the different areas of your company: Marketing, Operations, Finance, Human Resources, etc.


  1. Metadata.

Metadata refers to data about data. It is information about where the data is used and stored, the data sources, the changes made to the data, and the relationships between data.

The author of a document represents metadata, as well as the duration of an audio file, the font, and color of a text, the date of creation of a file, the moment of data capture, etc. This information is useful for the correct administration of the previously captured and stored data.


  1. End-User Layer.

This layer is what gives meaning to all the previous steps. Here, the end-user has access to the information, can analyze it, and use it for decision-making. It represents a series of tools to analyze and visualize information in different formats and for different users.

  • Analytical apps.
  • Visualization tools.
  • OLAP.
  • Data mining.
  • Reporting and query tools.


Ready, you already know the structure of a Business Intelligence system. Following this structure in the development of BI management software will allow you to arrive at a useful product for your company. But don’t forget: the development and this structure must be adapted to the specific needs of your organization.