Course Overview

Our comprehensive Business Analyst course combines a diverse range of essential skills, with Data Science as an integral component, to prepare students for thriving careers in this dynamic field. This program offers a deep exploration of Business Analysis, from understanding the pivotal role of a Business Analyst to mastering advanced techniques like Business Process Modeling, CATWOE, MoSCoW, MOST Analysis, PESTLE Analysis, SWOT Analysis, and the "6 Thinking Hats" approach for creative problem-solving. Additionally, students will gain a solid foundation in Data Science, covering key areas such as Mathematics, SQL, Python, and Machine Learning, enabling them to apply data-driven insights effectively within the realm of Business Analysis. This holistic approach ensures that our graduates are well-equipped to excel in the multifaceted world of Business Analysis, where data analytics plays a vital role in informed decision-making and strategic planning within organizations.

Suitable for

This course is suitable for

  • Individuals who want to pursue a career as a business analyst can benefit from a business analysis course.
  • Even experienced business analysts can benefit from advanced or specialized courses to enhance their skills and stay up-to-date with industry best practices.
  • Project managers who want to improve their ability to analyze and document business requirements and collaborate effectively with business analysts can also benefit from these courses.
  • Individuals who have an interest in process improvement, problem-solving, and making data-driven decisions can find value in business analysis courses.
  • Entrepreneurs and small business owners can benefit from business analysis training to improve their ability to understand and optimize their business processes.

Course Modules

Core Modules

  • Introduction to Business Analyst
  • BA understanding Through Story ( Example )
  • Business Process Modeling (BPM)
  • CATWOE (Customers, Actors, Transformation Process, Worldview, Owner, Environmental Constraints)
  • MoSCoW (Must or Should, Could or Would)
  • MOST (Mission, Objectives, Strategies, and Tactics) Analysis
  • PESTLE Analysis
  • SWOT Analysis
  • 6 Thinking Hats
  • Advanced Excel in data analysis enables users to manage, manipulate, and analyse large datasets. It includes features such as PivotTables, PivotCharts, and advanced functions like VLOOKUP, INDEX, MATCH, and IF statements. It is a widely-used tool in data analysis due to its versatility, flexibility, and user-friendly interface.
  • Enlarge Your Functions Toolbar
    • Set up Pivot tables
    • Grouping your data
    • Amend Pivot Tables with new data
    • Use a slicer to filter your data
    • Combining slicers to more than one Pivot Table
    • Using a timeline
    • Organise a Pivot chart
  • Analysing Your Data
    • Set up Pivot tables
    • Grouping your data
    • Amend Pivot Tables with new data
    • Use a slicer to filter your data
    • Combining slicers to more than one Pivot Table
    • Using a timeline
    • Organise a Pivot chart
  • Reducing Your Audit Risk
    • Data Recognition
    • Use of Trace Precedents
    • Use of Trace Dependents
    • Eliminate Arrows
    • Flaws checking
    • Check out Formula
    • Watch Window
  • Enhance Your Workflow
    • Set up Macro security
    • Recording Macros
    • How to edit Macro
    • Understanding the VBA edit window
    • Allow & run a Macro from the ribbon
    • Saving & using a Macro-enabled Workbook
    • Deleting your Macro
  • Additional Topics
    • Scenarios
    • Goal Seek

  • Mathematics
    • Linear Functions
    • Linear Algebra
    • Vectors
    • Matrices
    • Tensors
  • Statistics
    • Descriptive
    • Variability
    • Distribution
    • Probability
  • DDL and DML in MySQL and Setup
  • ERD Diagrams and Relational Mapping
  • Data Normalisation
  • Basic Queries
  • Database Manipulation
  • Table Manipulation
  • Relational Algebra
  • Advanced SQL - Joining, Subquery, Views
  • Database Security
  • Multiple Activities
  • Python Setup and What is Python?
  • Data Types and Syntax
  • Comparison Operators
  • Python Loop
  • Python Statements
  • Logical Operators
  • Methods and Functions
  • Error and Exception Handling
  • Modules Packages and libraries
  • Debugging
  • Advanced Python Modules (Date Time)
  • File Management
  • Multiple Activities
  • Multiple Projects to build
  • R is a highly regarded programming language in the realm of data analysis for its powerful statistical analysis capabilities, comprehensive library support, and graphics facilities. It is favored by statisticians and data analysts for its proficiency in data manipulation, statistical model building, and advanced data visualization.
  • R Introduction
  • R Installing
  • R Syntax
  • Comments, Variables and Data types in R
  • Numbers, Math, Strings, Booleans and Operators in R
  • IF, IF Else, Else if and Nested IF in R
  • Loops in R
  • Functions in R
  • Data Structures in R
  • Graphics in R
  • R Statistics
  • Final Project of Data Analysis with R
  • Data Preprocessing
  • Supervised Learning
  • Regression Models
    • Simple Linear Regression
    • Multiple Linear Regression
    • Polynomial Regression
    • Random Forest Regression
    • Topics such as
      • Assessing a Regression Model
      • Bias vs Variance
      • Regularisation
      • Gradient Descent
  • Classification Models
    • Decision Tree Classification
    • K-Nearest Neighbor
    • Logistic Regression
    • Na誰ve Bayes
    • Random Forest Classification
    • Support Vector Machines
    • Additional Topics
      • Assessing a Classification Model
      • Adaboost
      • Gradient Boosting
      • XGBoost
      • Grid Search CV
  • Unsupervised Learning
  • Clustering Models
    • Hierarchical
    • K-Means Clustering
  • Association
    • Apriori
    • Eclat
  • Build Dashboards for Data Visualisation
  • Solved Sample Code Files for easy practice
  • Access to Multiple Datasets
  • 7+ Real world data projects
  • Introduction to Power BI
    • Overview of Power BI
    • Advantages of Power BI
    • Power BI components
    • Power BI service vs Power BI desktop
  • Data Sources and Connections
    • Data sources overview
    • Connecting to different data sources
    • Working with data in Power BI
  • Data Transformation and Modeling
    • Data transformation and cleaning
    • Data modelling
    • Creating relationships between data tables
  • Visualisation
    • Basic visualisation types
    • Customising visualisations
    • Working with visuals and filters
  • Additional Topics
    • Introduction to DAX functions
    • DAX formulas and expressions
    • Aggregating and summarising data with DAX
  • Sharing and Collaboration
    • Sharing and publishing reports
    • Managing access to reports
    • Collaboration with Power BI
  • Advanced Topics
    • Advanced data modelling
    • Custom visuals and extensions
    • Power BI embedded
  • Case Studies and Hands-On Projects
    • Real-world case studies
    • Hands-on projects with Power BI
  • Tableau is a user-friendly data visualization and business intelligence tool that transforms data into interactive visuals, aiding data-driven decision-making for organizations.
  • Tableau Installation
    • Set up and customise Tableau on your PC to conduct data analysis.
  • Tableau UI
    • You will understand to use tool for researching and producing data visualisations.
  • Tableau UI Components
    • Using elements for creating visualisations, such as sheets and legends.
  • Tableau Marks Card
    • Controls the appearance of data points in a visualisation.
  • Tableau Functions
    • Understanding data manipulation computations built-in.
  • Filters in Tableau
    • Using tools for data focusing and refinement in visualisations.
  • Forecasting with Tableau
    • Utilise automated projections to predict future data patterns.
  • Parameters
    • Working with Dynamic values for customising an interactive visualisation.
  • Measures
    • How Calculations are made using quantitative data.
  • Dimensions
    • Grouping and categorising of data using categorical variables.
  • Project In Tableau
    • House Data Dashobard - Project I
    • Jobs Data Dashboard - Project II

Jobs you can Apply after Business Analysis Course

  • Business Analyst
  • Operations Analyst
  • Product Manager
  • System Analyst
  • Business Intelligence
  • Business Consultant
  • IT Business Analyst


  • Participants will receive certificates from Future Connect Training to mark their success and the priceless information they have learned after completing the training program.

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