Master Business Analysis for Success: Up Skill Training

Mode:	Online Based
Duration:	12 - 20 Weeks
Sessions:	50
Language:	English
Certificate:	Yes

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Information Technology

Business Analysis Course

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.

Modules

Module 1 Business Fundamentals

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

Module 2 Excel (Basic, Intermediate, Advanced)

The basic IT functions
Creating and using a range of name
Locate formulas
IFERROR
VLOOKUP & HLOOKUP
INDEX & MATCH
Analyzing 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
- Organize 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

Module 3 Mathematics & Statistics

Mathematics
- Linear Functions
- Linear Algebra
- Vectors
- Matrices
- Tensors
Statistics
- Descriptive
- Variability
- Distribution
- Probability

Module 4 SQL (Database)

DDL and DML in MySQL and setup
ERD Diagrams and Relational Mapping
Data normalization
Basic Queries
Database Manipulation
Table Manipulation
Relational Algebra
Advanced SQL - Joining, Subquery, Views
Database Security
Multiple Activities to Perform

Module 5 Python

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 (DateTime)
File Management
Multiple Activities to Perform
Multiple Projects to Build

Module 6 R Language

Basics: Installation, data types, and simple operations
Data Structures: Vectors, data frames, and lists
Data Import/Export: Loading and saving data
Manipulation: Subsetting, filtering, and transformations
Visualization: Basic plotting and ggplot2
Statistics: Summary stats and basic analysis
Control Structures: If-else and loops
Functions: Creating and using functions
Packages: Extending R's capabilities
R Markdown: Creating documents
Help/Documentation: Accessing assistance
Data Analysis: Exploring datasets
Error Handling: Troubleshooting errors

Module 7 Machine Learning

Data Preprocessing
Supervised Learning
Unsupervised 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
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

Module 8 Power BI

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 modeling
- Creating relationships between data tables
Visualization
- Basic visualization types
- Customizing visualizations
- Working with visuals and filters
DAX Functions
- Introduction to DAX functions
- DAX formulas and expressions
- Aggregating and summarizing data with DAX
Sharing and Collaboration
- Sharing and publishing reports
- Managing access to reports
- Collaboration with Power BI
Advanced Topics
- Advanced data modeling
- Custom visuals and extensions
- Power BI embedded
Case Studies and Hands-On Projects
- Real-world case studies
- Hands-on projects with Power BI

Module 9 Tableau

Tableau Installation
Installing Tableau on your computer will allow you to undertake data analysis.
Tableau UI
You will learn how to utilise the Tableau user interface to do research and create data visualisations.
Tableau UI Components
Utilising elements for building visualisations, including as sheets and legends, using Tableau UI components.
Tableau Marks Card
Manages how data points look in a display.
Tableau Functions
Understanding built-in data manipulation algorithms using Tableau Functions.
Filters in Tableau
Using tools for data focus and visualisation refinement, such as filters in Tableau.
Forecasting with Tableau
Utilise automated predictions to forecast future data patterns when forecasting using Tableau.
Parameters
Customising an interactive visualisation by working with dynamic values.
Measures
The process for using quantitative data in calculations.
Dimensions
Data categorization and grouping using categorical variables.

Jobs you can Apply after Business Analysis Course

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

Certification

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