december 13, 2022
How to choose a platform for a BI system?
Business Intelligence Lifecycle
The business intelligence life cycle consists of several phases, from converting raw data to its analysis and decision making.
Interestingly, 5 stages of BI value chain also coincide with a few BI lifecycle steps.
The 7 steps of a typical BI lifecycle
Identification of business processes and problems
BI exists to solve business problems, so the first crucial step in a business intelligence life cycle is to identify them and solve them. This involves understanding the business process, identifying where it is lacking, and the problem being raised from there. For instance, when acquiring a new customer through digital marketing, there may be a budget constraint for businesses. Therefore, the problem in this instance is lack of new customers, and BI needs to solve the question of how to acquire new customers with optimised budgets.
Data collection
As per the example above, a BI analyst has to look for relevant data that explains how much money was spent on various marketing channels, the number of customers acquired from each channel, the efficiency of each channel, customer complaints, and customer behaviour, purchasing history, etc. All this data can be available at various places in different forms.
Data warehousing
Another significant aspect of a business intelligence lifecycle is data warehousing. This step involves saving relevant data in RDBMS and other types of database management systems.
Data preparation and analysis
The fourth step is to prepare the data stored in a warehouse to perform data analysis. This includes monitoring daily activities, coming up with summary stats, and different models such as predictive, prescriptive, forecasting, and other types of analysis.
Reporting
Reporting involves converting the insights gained from analytics into visual and ‘digestible’ forms of reports, dashboards, KPIs, and presentations provided to the decision-makers.
Business decision
Based on the reports, the leadership then takes strategic and operational decisions. As the data justifies this decision-making, BI systems have a high chance of successfully achieving their goals. For example, a report can explain which marketing channels have acquired the most customers in a day, and the prediction on channel performance with a revised marketing budget. Based on the report, managers may decide to cut the spending on Facebook marketing and reallocate the money to Instagram, or even recommend spending marketing budget on other channels.
Evaluation and iteration
The last step is to assess the feasibility of the decision in monetary or even social terms. Once the decision is implemented, it’s essential to check if the decision was successful and to what extent. This feedback is critical as, depending on how many changes have been recommended, it makes decision making more effective, and the process more streamlined
