Business Intelligence Analyst Course

• Professional Background: No prior experience in business intelligence or data analysis is required; however, a basic understanding of business operations and analytical thinking will enhance the learning experience. 

• Language Proficiency: Learners must have a strong command of English, as all course content, discussions, and assessments are delivered in English. 

• Interest in Data Analysis: The course is ideal for individuals aiming to advance their careers by developing the analytical skills necessary to interpret complex data, support business decisions, and drive results. 

• Master Data Analysis Skills: Gain the ability to collect, analyse, and interpret large datasets, providing actionable insights that support business decisions and strategy. 

• Enhance Reporting and Visualisation: Learn how to create compelling reports and data visualisations using advanced business intelligence tools, making complex data easy to understand and communicate to stakeholders. 

• Develop Analytical Thinking: Develop critical thinking skills to assess business challenges, identify patterns, and recommend data-driven solutions for improved business performance. 

• Understand Business Intelligence Tools: Master popular BI tools, such as Microsoft Power BI, Tableau, and Excel, to extract, process, and present data in meaningful ways. 

The Business Intelligence Analyst Course is designed for professionals who want to enhance their analytical abilities and contribute to data-driven decision-making within their organisations. Below are the individuals who will benefit from this course: 

• Data Analysts 

• Business Analysts 

• Marketing Professionals 

• Financial Analysts 

• Operations Managers 

• IT Professionals 

• Sales Analysts 

• Project Managers 

• Decision Makers 

Module 1: Introduction to Business Intelligence 

• Overview of Business Intelligence (BI) 

• Role of Data in Business Decision-Making 

• Introduction to BI Tools and Technologies 

• Understanding Data Sources: Structured Vs Unstructured Data
   

Module 2: Data Warehousing and ETL Processes 

• Introduction to Data Warehousing 

• ETL Fundamentals 

• Data Warehouse Design and Dimensional Modelling 

• Data Mart Vs Data Warehouse
   

Module 3: Data Analytics and Visualisation 

• Fundamentals of Data Analysis and Statistical Techniques 

• Introduction to Data Visualisation Tools 

• Crafting Effective Visualisations 

• Interactive Dashboards and Data Storytelling
   

Module 4: SQL for Business Intelligence 

• Basics of SQL 

• SQL Techniques for Data Analysis 

• SQL Functions and Stored Procedures for BI Tasks 

• Optimising SQL Queries for Performance 

• Data Manipulation and Analysis Using SQL
   

Module 5: Introduction to Business Analytics with Python 

• Python Basics for Data Analysis 

• Data Manipulation with Pandas 

• Introduction to Predictive Analytics with Python
   

Module 6: BI Tools and Technologies 

• Overview of Popular BI and Analytics Tools 

• Data Connection, Visualisation, and Dashboard Creation 

• Exploring Power BI: Data Modelling, Reporting, and Publishing 

• Introduction to Qlik Sense 

• Comparative Analysis of BI Tool
   

Module 7: Project Management and Collaboration in BI 

• Fundamentals of Project Management for BI Projects 

• Collaboration Techniques and Tools for BI Teams 

• Stakeholder Management and Communication Strategies 

• BI Project Lifecycle