Understanding business intelligence (BI) allows us to demystify and differentiate from data science. In my experience, business intelligence allows for better information access for management and improved reporting. We know from the previous article that BI is well-suited for descriptive and diagnostic analysis. Descriptive analysis helps us understand “who”, “where”, “when”, “how many”, or “what” happened in the past as shown by the data. Diagnostic analysis tells us why something is happening (the leading cause). When I started my career in a finance department in 2008, we relied much on management information systems (MIS). This finance MIS introduced me to analysis and I later fell in love with data-driven insights (DDI). DDI better serves the organisation and teams when we improve MIS departments to focus on BI. But before we start to think that MIS is outdated and obsolete, we must understand what BI is and why is it important in the organisation.
What is Business Intelligence (BI)
BI could be defined as the practice of turning data into actionable insights. This definition allows us to distinguish BI from others by processes, tools, skills, and roles. The main of business intelligence is to provide actionable insights that enable senior management and business leaders to change or maintain a course of action. I am specific to state that BI works best for senior management and business executives as we tend to require operational insights and reports for middle and lower management. It is better to invest in BI if you are battling with readily available insights for decision-making. Otherwise, we could rather invest in report optimisation for operational reports using robotics process automation (RPA) instead of BI.
Key Skills Required for BI
The key skills needed to be in BI include statistics and analysis. It could be further broken down into the ability to do (1) basic statistics (descriptive statistics), (2) data transformation, (3) data visualisation, and (4) business knowledge. BI analysts are not required to have domain knowledge (e.g. Insurance industry) as business knowledge (i.e. Company knowledge) would suffice. Their daily tasks require BI analysts to focus on what has happened and what trends are currently developing. Typical questions that I used to get when I was a financial business analyst included what is the growth of IT headcount by transformation goals? What are the year-to-date financial actuals compared to the forecast and show how each contributes to the variance? To do and provide insights into the above questions, different team members would be involved.
BI Roles and Responsibilities
There are different roles that could be included are part of the BI analysis. This includes data engineers, data business & process analysts, data analysts, data visualisation specialists, and team leaders or senior managers who would assist with decision-making. Data visualisation specialists are team members who help with visuals, reporting and dashboards. They will be using data models that were developed by data analysts. Data analysts best make data models and analyses that are optimised for visualisation. Data engineers prepare data for data analysts as they specialise in data storage and ETL (Extract, Transform, and Load) procedures.
Conclusions
We can see from above that understanding BI allows us to differentiate it from data science. The processes followed are different to the ones followed by data scientists. This explains how a hiring manager would be able to pick up if the candidate is a data scientist or BI analyst. BI is best suited for descriptive analysis which helps business leaders understand “who”, “where”, “when”, “how many”, or “what” happened for better decision-making. In so doing, data is being transformed into actionable insights thus making BI a key partner for decision making. An ideal BI analyst must have the ability to do (1) basic statistics (descriptive statistics), (2) data transformation, (3) data visualisation, and (4) business knowledge. This includes data engineers, data business & process analysts, data analysts, data visualisation specialists, and team leaders or senior managers who would assist with decision-making. I know that the above helps anyone fall in love with analysis, especially business intelligence analysis.
