Business Intelligence and Intelligent Business Decisions

Background and History of Business Intelligence:

According to Wikipedia, the term ‘business intelligence’ was first used by IBM researcher Hans Luhn in 1958. He defined it as ‘the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.’

Since that time, business intelligence (also known as ‘BI’) has developed and grown, and nowadays when the term ‘BI’ is used it generally refers to the gathering, storing and analyzing of data for the purpose of making intelligent business decisions.

Purpose of BI Technology:

Most (if not all) businesses deal with huge amounts of data. Analyzing this raw data in a quick and accurate manner is extremely difficult due to key trends that are masked by the sheer amount of information to digest.

This is where business intelligence software and technologies can help. BI provides a proven, well-defined methodology to process and analyze business-related information quickly and accurately. This is accomplished via the BI ‘stack.’

Business Intelligence Stack:

The BI stack has been traditionally defined as follows:

1. Data Layer:

a. Consists of the raw data that needs to be analyzed.
b. Data can originate from multiple sources, such as: MySQL, MS SQL, Oracle and Access databases; OLAP (online analytical processing) sources; various spreadsheets like MS Excel; CSV files; and even data sources that are not structured.

2. Analytics Layer:

a. This layer is responsible for transforming the raw data into meaningful information.
b. Components that constitute this analytics layer can be:

i. Data mining: refers to the process of extracting patterns out of raw data.
ii. Predictive analysis: involves the analyzing of data and then predicting future events or patterns.

iii. KPI formulation: the formulation of key performance indicators (KPIs) which are meaningful to a business.

iv. And any other business-specific methods of transforming and massaging data.

3. Presentation Layer:

a. The presentation layer is responsible for visually representing the data provided by the analytics layer.
b. Data visualization can be accomplished via digital dashboards, performance scorecards, graphs, reports, gauges, indicators and any other visualization components.

To summarize how the BI stack functions:

1. Data is collected from a variety of sources.
2. The data is then transformed into meaningful information.
3. The massaged information is displayed to end users using data visualization methods.

The Future of Business Intelligence:

BI technology is constantly evolving and this is reflected by changes to the BI stack.

It is important to note that the stack is not ‘set in stone.’ The nature of business varies to a great extent and how a company chooses to implement business intelligence in their decision-making processes will affect their implementation of the BI stack.

Recent modifications to the stack include things such as:

• The mass adoption of mobile BI, which is reflected in the presentation layer.
• Major advancements in predictive analytics, a component of the analytics layer.
• Environmentally friendly data storage.