Today the term BI, Business Intelligence, is one of the most commonly used at business level when talking about data management and the search for systems which allow us to make sense of them.
What is Business Intelligence?
If we do a quick search, we will find different definitions for this concept but, in one way or another, they all mean the same thing: the set of processes transforming the data of a company into information and knowledge to support the decision making process.
All companies store large volumes of data obtained from their daily operations, such as orders, delivery notes, invoices, accounting movements, payrolls, operations, etc. But these data are just the alphanumeric representation of an attribute or fact, they do not contain any meaning by themselves.
Information has to be more precise. Information is making sense of the data in a specific context. Therefore, while data can be just a figure like i.e. “100“, the information on that data could be “TV sales in August was 100 units”. The next step of Business Intelligence is to transform data and information into reliable knowledge so you can make decisions. What differentiates knowledge from information is that it implies an intellectual process. Following with our example we could say “August was the lowest month in sales”, so we could determine our business strategies.
Why should you use Business Intelligence?
The ability to make timely decisions, quickly and accurately, alongside with a strategic plan based on knowledge about our environment are key to make a difference and achieve success, providing companies with a much-desired competitive advantage.
However, traditional information systems have serious weak points within their structures and very little flexibility to achieve such goals. This is because its design is not aimed at obtaining knowledge from the data stored daily by companies.
What are the limitations of Business Intelligence?
The most prominent limitations of these systems are:
|The need for technical knowledge by users|
|Long response times when there is a need for quick responses|
|Lack of data integration, which causes erroneous and incomplete information|
|Absence of historical information and, therefore, of the evolution of the business|
|Low performance when generating reports under the same database that supports operational systems|
Business Intelligence was born due to these limitations. BI includes the set of tools aimed at extracting and transforming the data stored in companies, promoting their analysis and conversion into information and knowledge, providing companies with the support they need to quickly solve business questions.
In short, a BI solution allows us to observe and understand our environment, what is happening and why, to predict what will happen and decide which path to follow. It gives us complete visibility of our business and the guidelines that we must follow in the future.
What are the benefits of Business Intelligence?
There are many benefits, but we can highlight:
|Trend analysis and future prediction|
|Detection of right and wrong behaviours|
|Learning from previous mistakes|
|End user orientation without the need for technical knowledge|
Focusing on a more technical vision and attending to the general architecture of a BI application, the basic scheme in a Business Intelligence project is as follows:
In future blog posts we will go into the details of the components and processes involved in this type of architecture, but as a first approach I will make a brief description of its phases.
Phases of a BI project
Every company stores data from their operations, but these can be in more than one system.
The first phase of a BI project is to extract the data from the different sources that are in the company, unifying them and transforming them based on future questions you need answers for and loading them into a single centralized container. These processes of extraction, transformation and loading are known by the acronym ETL (Extract – Transform – Load). The container in which the data will be loaded is called DataWarehouse which, under consolidation requirements, will contain all the debugged data of the company. They could also be loaded into small DataMarts that, sharing technical aspects and general characteristics with the DataWarehouse, are designed for departmental purposes, optimized for specific areas.
Next, exploitation tools come into play, specializing in the visualization of information, promoting their analysis through reports, dashboards, alerts, etc. to answer the business questions.
In summary, a Business Intelligence solution manages to unify the data and make sense of them, making them the most valuable component of the company to understand its past, its present and decide on its future, thus providing a clear competitive advantage over companies that don’t possess such solutions.