KHDA

Business Analyst Course in Ethiopia

Business Analyst career acceleration in 85 hours

Hands-on Excel, SQL, Power BI, Tableau & Microsoft Fabric

AI-powered Business Analysis & Reporting via Automation Sandbox

Enterprise Digital Transformation simulation: stakeholder & KPI analysis

Capstone project with real business scenarios & dashboards

Flexible learning modes & easy payment options

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Overview

What you will learn:

  • Learn data manipulation and analysis by mastering the advanced Excel functions
  • Learn about SQL to perform data extraction and data queries
  • Build your expertise in data visualisation using Power BI
  • Learn to create impressive dashboards with Tableau
  • Develop data modelling skills and learn DAX for data analysis
  • Apply your skills through hands-on, industry-relevant projects and case studies

Upcoming sessions

Curriculum

1

Excel Interface Overview (Ribbon, Toolbar, Sheets)

2

Workbook vs. Worksheet

3

Navigation Shortcuts (Ctrl + Arrow Keys, etc.)

4

Basic Data Entry and Cell Formatting

5

Saving, Opening, and Managing Excel Files

6

Printing and Page Layout Settings

7

Basic Formulas (SUM, AVERAGE, MIN, MAX)

8

Relative vs. Absolute Cell References ($A$1 vs. A1)

9

Text Functions (CONCATENATE, LEFT, RIGHT, MID, LEN, TRIM)

10

Logical Functions (IF, AND, OR)

11

Basic Date Functions (TODAY, NOW, DATE, DATEDIF)

12

Introduction to Charts (Bar, Line, Pie, Scatter, etc.)

13

Creating and Formatting Charts

14

Adding Data Labels, Legends, and Titles

15

Sparklines and Conditional Formatting

16

Best Practices for Data Visualization

17

Lookup Functions (VLOOKUP, HLOOKUP, XLOOKUP)

18

INDEX and MATCH Functions

19

Advanced Text Functions (TEXT, FIND, SEARCH, SUBSTITUTE)

20

Data Cleaning Techniques (Remove Duplicates, Text to Columns)

21

Working with Named Ranges

1

Sorting Data (Single & Multi-level)

2

Filtering Data (Basic & Advanced Filters)

3

Subtotals and Grouping Data

4

Data Validation for Error Prevention

5

Using Excel Tables for Data Management

6

Array Formulas and Dynamic Arrays (FILTER, SORT, UNIQUE)

7

Financial Functions (NPV, IRR, PMT)

8

Statistical Functions (MEDIAN, MODE, STDEV)

9

Error Handling Functions (IFERROR, ISERROR)

10

Advanced Date and Time Functions (WORKDAY, NETWORKDAYS, EOMONTH)

11

Creating and Formatting PivotTables

12

Grouping and Summarizing Data

13

Calculated Fields and Items

14

Creating PivotCharts

15

Slicers and Timelines for Interactive Reports

16

Introduction to Macros and VBA

17

Recording and Running Macros

18

Basic VBA Concepts (Variables, Loops, If Statements)

19

Editing and Debugging Macro Code

20

Best Practices for Macro Security

1

What is SQL? Overview and Importance

2

Relational Database Concepts (Tables, Rows, Columns)

3

Common Database Management Systems (MySQL, PostgreSQL, Oracle, SQL Server)

4

SQL Syntax Rules

5

Connecting to a Database (Using tools like MySQL Workbench or pgAdmin)

6

The SELECT Statement

7

Selecting Specific Columns

8

Using DISTINCT to Remove Duplicates

9

Simple WHERE Clauses for Filtering

10

Using ORDER BY for Sorting Data

11

Basic LIMIT clause (for databases like MySQL/PostgreSQL)

12

Using Comparison Operators (=, !=, >, <, >=, <=)

13

Logical Operators (AND, OR, NOT)

14

Filtering with BETWEEN, IN, and LIKE

15

Handling NULL values (IS NULL, IS NOT NULL)

16

Sorting Data with ORDER BY (Ascending & Descending)

17

Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)

18

Grouping Data with GROUP BY

19

Filtering Groups with HAVING

20

Using GROUP BY with Multiple Columns

21

Understanding the Difference between WHERE and HAVING

22

Introduction to Joins and Data Relationships

23

INNER JOIN for Matching Data

24

LEFT JOIN for Including Non-matching Records

25

RIGHT JOIN and FULL OUTER JOIN (if supported by the database)

26

Using Aliases for Table Names

27

Joining Multiple Tables

28

Best Practices for Writing Joins

1

Overview of Power BI components (Desktop, Service, Mobile).

2

Copilot Introduction: How to use AI-powered features for data exploration.

3

Installing Power BI Desktop and setting up the environment.

4

Navigating the Power BI interface: ribbons, panes, and views.

5

Hands-on Lab: Importing sample datasets and exploring Copilot.

6

Connecting to various data sources (Excel, SQL, Web APIs).

7

Data profiling, data types, and handling missing values.

8

Advanced transformations: merging, appending, pivoting, unpivoting data.

9

Using Power Query Editor for complex data shaping.

10

Hands-on Lab: Transforming raw data into a clean dataset.

1

Designing star and snowflake schemas.

2

Creating and managing table relationships.

3

DAX basics: calculated columns, measures, and quick measures.

4

Using DAX for basic calculations like SUM, AVERAGE, COUNT.

5

Hands-on Lab: Building a data model for sales data analysis.

6

Advanced DAX functions: CALCULATE, FILTER, ALL, RELATED.

7

Time intelligence functions for date-based calculations (e.g., YTD, QTD).

8

Performance optimization techniques: DAX query tuning, minimizing model size.

9

Hands-on Lab: Creating advanced DAX measures for business insights.

1

Building advanced visuals: combination charts, gauges, maps, and custom visuals.

2

Creating dynamic reports with slicers, bookmarks, and drill-through.

3

Designing for user experience: layout, color schemes, and storytelling.

4

Best practices for dashboard design and performance.

5

Hands-on Lab: Creating an interactive sales performance dashboard.

6

Publishing reports and dashboards to Power BI Service.

7

Configuring dataset refresh schedules and managing gateways.

8

Setting up Row-Level Security (RLS) for data access control.

9

Hands-on Lab: Publishing and sharing reports with user access control.

1

Using Copilot to generate natural language insights and queries.

2

Automating data exploration and report generation.

3

Implementing Copilot for predictive analytics and recommendations.

4

Hands-on Lab: Using Copilot for advanced data exploration.

5

Utilizing AI visuals like Key Influencers, Decomposition Tree, and Smart Narrative.

6

Conducting clustering, anomaly detection, and forecasting.

7

Interactive Q&A with natural language queries.

8

Hands-on Lab: Applying AI visuals to real-world business data.

9

Overview of Microsoft Fabric: Synapse, Data Factory, Data Lake, and Power BI.

10

Using OneLake for centralized data storage.

11

Building Synapse Dataflows for real-time data ingestion.

12

Creating data pipelines for ETL processes and integrating with Power BI.

13

Hands-on Lab: Setting up a Fabric workspace, creating dataflows, and integrating with Power BI.

1

Overview of Tableau Prep for data cleaning and transformation.

2

Importing, filtering, and shaping data for analysis.

3

Data profiling and preparing datasets for analysis.

4

Connecting to various data sources (spreadsheets, databases, cloud).

5

Understanding live connections vs extracts.

6

Managing data joins, unions, and blends.

7

Building foundational visualizations like bar charts, line charts, and scatter plots.

8

Sorting, filtering, and grouping data.

9

Working with visual marks (size, color, labels) for enhanced data presentation.

10

Creating row-level and aggregate calculations.

11

Using string functions, logical functions, and conditional calculations.

12

Practical applications of calculations for deriving insights.

1

Incorporating reference lines, trend lines, and forecasts.

2

Using parameters to create dynamic visualizations.

3

Highlight actions, sets, and advanced tooltips for interactivity.

4

Understanding Fixed, Include, and Exclude LOD calculations.

5

Practical scenarios for using LOD expressions in reporting.

6

Combining LOD expressions with other calculations.

7

Creating dual-axis charts, waterfall charts, and bullet graphs.

8

Understanding when and how to use advanced charts for storytelling.

9

Hands-on practice with custom chart creation.

10

Building interactive dashboards from multiple sheets.

11

Using dashboard actions to filter and highlight data dynamically.

12

Creating stories to present data insights in a narrative format

Meet your Trainer

Himanshu

Mr Himanshu is a highly experienced professional with over 20 years in leadership and IT. He specializes in academic management, quality assurance, and institutional compliance, managing licensing and approvals from awarding bodies like Pearson, Qualify, and regional authorities. With expertise in IT infrastructure, digital transformation, and training, Himanshu has served as a lecturer, director, and program leader. Certified in Cisco, Microsoft, and CompTIA technologies, he excels in managing IT operations, curriculum development, and delivering technical training in diverse, multicultural environments.

Core Competencies:

  • Leadership and Management
  • IT Infrastructure Expertise
  • Program Development Skills
  • Quality Assurance and Compliance
  • Staff Training and Mentoring
  • Technology Integration Proficiency
  • Networking and IT Solutions

Professional Qualifications:

  • Masters of Business Administration (MBA) Marketing & HRD
  • Master of Science
  • Bachelor of Science in Botany Honors
  • Currently studying for the MCIPS Certification from Chartered Institute, UK
  • CIPS Level 4 & CIPS Level 5 from Chartered Institute of Procurement & Supply, UK
  • CIPS Northern Emirates Committee Member- Education
  • Trainer, Learners Point Academy, Dubai

Learning Outcomes

Successful completion of the training will help you to:

  • 1

    Master advanced Excel features for data analysis

  • 2

    Extract, manipulate and organise data Power BI, Tableau & MySQL

  • 3

    Become an expert in Tableau for advanced visual analytics

  • 4

    Use Copilot features in Power BI for predictive data analysis and automate data exploration

  • 5

    Develop impressive interactive, clean and dynamic reports, dashboards

  • objective-image

    Ready to get started?

  • KHDA Certificate

    Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

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    Learners Point Certificate

    Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

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    Frequently asked questions

    Our Business Analyst Course in Ethiopia builds an individual’s expertise in data analytics and visualisation. Through hands-on projects and real-world scenarios, students gain expertise in Excel, SQL, Tableau, Power BI, Copilot and more.

    To enrol in this course, no background knowledge is necessary. Our Business Analyst course covers everything from basics to advanced. It is perfect for anyone who wants to learn about data analysis.

    The topics that are covered in the Business Analyst course are listed below:

    • Business Analysis with Excel’s advanced features
    • Data Extraction and Manipulation with SQL
    • Data Modelling and DAX with Power BI
    • Introduction to Microsoft Power BI for Business Analytics
    • Visualisation and Power BI Services
    • Advanced Analytics using Copilot and Fabric
    • Tableau for Business Analytics
    • Visual Analytics and Dashboarding with Tableau

    As a fresher and you are starting your career as a Business Analyst, you can apply for the following job roles:

    • Junior Data Analyst
    • Financial Analyst
    • Product Manager
    • Business Analytics Specialist

    Do you want to learn more about Learners Point Academy?

    • Learn more about courses
    • Understand about our methodology
    • Let’s talk about Corporate trainings
    • Anything else that you want to know, we are here for you!

    Let's chat!