Business Analysis and Data Analysis


What is Business Analysis?

Business analysis is the knowledge, techniques and tasks we use to understand the structure, strategy, and operation of an organisation. It is also the process of describing how organisations function. Organisations need to have systems and processes in place to achieve their purpose, vision, mission, goals, and objectives. These systems and processes deliver value to stakeholders. We use business analysis to help identify business needs and determine solutions to business problems. Solutions often include developing or implementing an information system, improving a business process, or changing the way the organisation does something.

Business analysis and projects

We perform business analysis at all levels of the organisation: strategic, tactical, operation and project. We apply business analysis techniques throughout the project life cycle including the pre-project and post-project phases. In the pre-project phase, we use the techniques to perform feasibility studies and develop business cases. Post-project we analyse project outcome to assess project value delivery. And in the implementation phase, business analysis techniques help the project manager improve project performance.

Graphic showing Business Analysis responsibility in pre-project, project and post-project phases
Business Analysis in Project Phases

Business Analysis Body of Knowledge

The Business Analysis Body of Knowledge (BABOK) describes the knowledge, activities, tasks, and skills necessary to perform a business analysis study. The BABOK guide describes the generally accepted practices in the field of business analysis and provides a framework for performing a business analysis study that delivers value for the organisation. The latest version, BABOK version 3, lists fifty techniques every business analyst should know.

For more information on the International Institute for Business Analysis (IIBA), and the BABOK guide, click HERE.

What is a Business Analyst

A business analyst is any person who performs business analysis activities, no matter what their job title or organisational role might be. Business analysts may be full-time employees, or the function may be outsourced. Management consultants, for example, perform many business analysis functions during the diagnosis, action-planning, and implementation phases of their consulting assignments. Business analysts who specialize in information systems and computer technology projects are commonly known as systems analysts.

What Can Business Analysts Do For Organisations?

All organisations regardless of size can benefit from business analysis. Organisations typically use business analysts to:

  • Understand how the organisation functions to accomplish its purpose, vision, and mission.
  • Help management define and develop strategy, set goals and objectives.
  • Determine the course of action the organisation must take to achieve their goals and objectives.
  • Define the capabilities the organisation needs to provide products and services.
  • Analyse and synthesize data and information from multiple sources.
  • Determine how the various organisational units and stakeholders interact, both within and outside the organisation.
  • Align needs of organisational units with the capabilities delivered by information and communications technology systems.
  • Understand the current state of the organisation.
  • Elicit actual stakeholder needs and requirements, not simply their expressed desires.
  • Define and validate solutions to business problems.
  • Facilitate communication between business units and systems development specialists.
  • Facilitate change within the organisation to accommodate proposed solutions.
  • Perform feasibility studies in the pre-project phase.
  • Develop project business cases that justify investment and determine value.
  • Evaluate solution value delivery in post-project phase.

For more information on the role of the Business Analyst in the pre-project phase check out my blog: Feasibility Study – A Step-by-Step Guide


One of the key functions of a business analyst, or management consultant, is to analyse and synthesize data and information from multiple sources.

What is Data Analysis?

Data analysis is the process of collecting, cleaning, analyzing and interpreting data to gain insights, to draw conclusions, make predictions, and drive informed decision-making.

What is the Difference Between Data and Information?

Although the words data and information are often used interchangeably, there is a distinct difference between the two terms. Data are a simple statement of fact. Data is plural, datum is singular, and a datum is an uninterpreted raw statement of fact.

We convert data into information by recording, classifying, organizing or relating the data in some way within context to convey meaning and insight. This insight is used to shape business processes to improve operational efficiency, reduce costs, or increase productivity. In addition, we use data analysis to improve our decision-making. We analyse data to identify trends and patterns, and then base our decisions on the insights we derive.

Five Types of Data Analysis

There are five types of data analysis: 1) Descriptive analysis, 2) Diagnostic analysis, 3) Predictive analysis, 4) Prescriptive Analysis, and 5) Cognitive analysis.

The five type of analysis are used sequentially. This means that you start off with descriptive analysis and then work through each type in turn. The type of analysis you chose depends on your specific needs and goals, the type of data your organisation generates, and the resources you have available.

Descriptive analysis

This is the most basic type of data analysis. It describes what has happened in the past. It does not try to predict the future, or explain why things have happened. Descriptive analysis simply summarizes data and identifies trends and patterns.

You use descriptive data analysis to answer questions like:

  • What did we sell last month?
  • What are our most popular products?
  • How many people use our service?
  • What are our customers demographics?
  • Who are our top customers?
  • How much downtime did we have last month?

Descriptive analysis helps you identify opportunities and areas for improvement.

Diagnostic analysis

Diagnostic analysis helps you understand why things happened. After you have identified what happened, you now want to know why? You want to identify problems and get to the root cause.

Diagnostic analysis gives you answers to questions like:

  • Why did sales decline in the last quarter?
  • Why are there so many defects in our products?
  • Why is our customer turnover so high?
  • Why are we not meeting our goals?
  • Why are we having so much downtime in production?

You use diagnostic data analysis to identify the correlation and relationship between variables. Once you have identified the root cause you can take the appropriate corrective action.

Predictive analysis

Predictive analysis follows diagnostic analysis. You don’t just want to know what happened and why it happened, you want to know what is likely to happen in the future. You use predictive analysis to forecast what is likely to happen in the future. This type of analysis uses algorithms and historical data to forecast future patterns or events and evaluate the probability (likelihood) of future scenarios.

Predictive analysis gives you answers to the following types of questions:

  • What is the likelihood of a customer going to a competitor?
  • When will a customer make a purchase?
  • Which products are going to be popular next year?
  • What is the likelihood we will meet our production target?
  • When is this machine likely to fail?

Prescriptive analysis

Prescriptive analysis techniques give you an ideas of what actions you should take. This is the second-most sophisticated type of analysis. You typically use prescriptive analysis techniques after you know what has happened in the past, why it has happened, and what is likely to happen in the future. Prescriptive analysis helps you optimize your business decisions and processes.

Prescriptive analysis helps you answer the following questions:

  • What can we do to increase sales.
  • How can we improve customer satisfaction?
  • What do we need to do to reduce costs/improve productivity?
  • How can we prevent this system from failing?

Cognitive analysis

Cognitive analysis is at the tops of the data analysis pyramid. This is the most sophisticated type of analysis because it uses artificial intelligence (AI) and machine learning to understand and interpret data. With the development of AI models, and their incorporation into web browsers and normal office productivity software, this form of analysis is becoming easier to perform. However, it still takes a human mind to verify and validate the quality of information you get from AI. Consequently, you use AI-based cognitive analysis with caution.

Typical questions cognitive analysis can answer include:

  • What are the most likely causes of machine breakdown in our plant?
  • What are the most important factors influencing consumer buying behaviour?
  • What are the risks involved in this investment?
  • What is the most likely climate change scenario facing our organisation?

The Data Analysis Process

Data analysis is a structured process consisting of five sequential steps:

  • Identify the business question you want to answer, or the problem you want to solve. Decide what you want to measure, and how you will measure it. Identify the type and source of the data.
  • Collect the raw data you need to answer the question or solve the problem.
  • Clean the data. Prepare it for analysis by removing duplicates, blank spaces and outliers. Standardise the data structure and format.
  • Analyse the data using the appropriate tools and techniques. Look for trends, patterns, outliers, variations, correlations and relationships. Visualise the data using graphs and other visualisation tools.
  • Interpret the data. Turn the data into information, interpret the results, draw conclusions, and make recommendations. Define the limitations of your conclusions.