Explain the architecture of a BI system
1 Answer


→ Business intelligence is a set of mathematical models and analysis methodologies that exploit the available data to generate information and knowledge useful for complex decision-making processes.

→ i.e. it is a broad category of applications and technologies for gathering. storing, analysing and providing access to data to help clients make better decisions.

For Example: Reducing the staff in the company

If I want to reduce the staff in my company. So to reduce the staff it needs the right

Information, how many staff I have, what type of staff I have, what is my business doing with this staff. how much do I cam, what is my growth, what is my operational expenses, do I need to reduce the staff or not?

So if you can provide the right information at the right time in the right format which is matching to the business data so you can take the right decisions on that data



Data is a set of representation of plain facts. Data are the facts of the world. Data represent a structured codification of single primary entities, as well as of transactions involving two or more primary entities.


Information is the outcome of extraction and processing activities carried out on data, and it appears meaningful for those who receive it in a specific domain.


Information is transformed into knowledge when it is used to make decisions and develop the corresponding actions.

The activity of providing support to knowledge workers through the integration of decision-making processes and enabling information technologies is usually referred to as knowledge management.







Data sources:

In a first stage, it is necessary to gather and integrate the data stored in the various primary and secondary sources, which are heterogeneous in origin and type. The sources consist for the most part of data belonging to operational systems, but may also include unstructured documents, such as emails and data received from external providers.

Data warehouses and data marts:

Using extraction and transformation tools known as extract, transform, load (ETL), the data originating from the different sources are stored in databases intended to support business intelligence analyses. These databases are usually referred to as data warehouses and data marts.

Business intelligence methodologies:

Data are finally extracted and used to feed mathematical models and analysis methodologies intended to support decision makers. In a business intelligence system, several decision support applications may be implemented, most of which will be described in the following chapters:

• multidimensional cube analysis:

exploratory data analysis;

• time series analysis:

• optimization models.

Inductive learning models for data mining:


Data Exploration:

It is an informative search which is used by data consumers to form real and true analysis from the information collected. It is about describing the data by means of statistical and visualization techniques. We explore data in order to bring important aspects of that data into focus for further analysis. Often, data is gathered in a non-rigid or controlled manner in large bulks,

Data mining:

Data mining technique has to be chosen based on the type of business and the type of problem your business faces. A generalized approach has to be used to improve the accuracy and cost effectiveness of using data mining techniques.


By moving up one level in the pyramid we find optimization models that allow us to determine the best solution out of a set of alternative actions, which is usually fairly extensive and sometimes even infinite.


The top of the pyramid corresponds to the choice and the actual adoption of a specific decision, and in some way represents the natural conclusion of the decision-making process. Even when business intelligence methodologies are available and successfully adopted, the choice of a decision pertains to the decision makers, who may also take advantage of informal and unstructured information available to adapt and modify the recommendations and the conclusions achieved through the use of mathematical models.

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