Amdor Analytics

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Data Analytics- Professional

The course equips learners with  hands-on with Excel, SQL, data visualization, and BI fundamentals to support business decision-making through data-driven insight
  • Length
2 Months
  • Capstone
1 Months
  • Certificate
Yes
  • Level
Professional
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About the course

Data Analytics Professional is a practical, industry-focused program designed to help learners transform raw data into meaningful business insights. The course starts with data fundamentals and progresses through Excel analytics, SQL, Power BI, data cleaning, visualization, and dashboard creation. Learners develop strong analytical thinking skills while working with real-world datasets to uncover trends, generate reports, and support business decision-making. The program also introduces statistical analysis and storytelling techniques that help professionals communicate insights clearly and effectively. Through hands-on projects and case studies, students gain the confidence and practical experience needed for modern data analytics roles.

Course Curriculum

Module 1: Basic Excel Fundamentals
  • Introduction to Microsoft Excel and Ribbon Interface
  • Understanding Workbooks, Worksheets, and Cells
  • Data Entry, Editing, and Formatting (Text, Numbers, Dates)
  • Using AutoFill, Flash Fill, and Basic Data Validation
  • Basic Formulas and Functions:
    • SUM, AVERAGE, COUNT, MAX, MIN
  • Paste special
  • Sorting and Filtering Data
  • Charts and Graphs
  • Data Validation
  • Conditional Formatting
  • Logical Functions: IF, AND, OR, NESTED IF, IFERROR
  • Cell Referencing (Relative, Absolute, and Mixed)
  • Advanced Conditional Formulas (IFS, COUNTIF, COUNTIFS, SUMPRODUCT, SUMIF, SUMIFS, AVERAGEIF, AVERAGEIFS, MAXIFS, MINIFS, IFERROR)
  • Text Functions: CONCAT, LEFT, RIGHT, MID, TRIM, LEN
  • Textsplit
  • Date & Time Functions: TODAY, NOW, DATEDIF
  • Data Cleaning Techniques (Remove Duplicates, Text-to-Columns, Find & Replace)
  • Introduction to Pivot Table
  • Lookup & Reference Functions: VLOOKUP, HLOOKUP, INDEX, MATCH, XLOOKUP
  • Tables and Structured References
  • Charts & Visualizations:
    • Combo Charts, Sparklines, Dynamic Charts
  • Introduction to Power Query (Data Transformation)
  • Introduction to Business Intelligence
    • What is Business Intelligence (BI)?
    • Understanding data-driven decision making
    • Overview of the Power BI ecosystem and components
  • Getting Started with Power BI Desktop
    • Installing Power BI Desktop
    • Power BI interface walkthrough
    • Understanding different Power BI views (Report, Data, Model)
    • Connecting to data sources (Excel, CSV, Web, SQL Server, etc.)
  • Basic Data Loading and Transformation
    • Introduction to Power Query Editor
    • Importing and transforming data
    • Removing duplicates, handling missing data, changing data types
    • Appending and merging queries
  • Creating Basic Visualizations
    • Understanding visualization types (bar, line, pie, map, cards, tables)
    • Creating your first Power BI report
    • Formatting visuals and adding titles/labels
    • Introduction to slicers and filters
  • Data Relationships
    • What are relationships in Power BI?
    • Understanding primary and foreign keys
    • Creating and managing relationships manually and automatically
  • Introduction to Power BI Terminologies
    • Datasets, dashboards, reports, tiles, and workspaces
    • Power BI Desktop vs Power BI Service
  • Advanced Power Query (ETL Process)
    • Applying transformations step-by-step
    • Splitting and merging columns
    • Unpivoting and pivoting data
    • Conditional columns and custom columns
    • Using parameters and functions in Power Query
  • Data Modelling Best Practices
    • Star schema and snowflake schema explained
    • Building efficient data models
    • Managing data relationships and cardinality
  • Introduction to DAX (Data Analysis Expressions)
    • Difference between calculated columns and measures
    • Syntax and logic of DAX
    • Basic functions: SUM, COUNT, DISTINCTCOUNT, AVERAGE, MIN, MAX
  • Advanced Visuals
    • Using matrix, maps, decomposition tree, and waterfall charts
    • Custom visuals from the Power BI marketplace
    • KPI cards, gauge charts, and key influencer visuals
  • Data Storytelling Techniques
    • Understanding your audience
    • Designing for clarity and simplicity
    • Color theory and layout best practices
    • Using bookmarks and buttons for interactivity
  • Dynamic Visuals and Filters
    • Using slicers and page navigation
    • Drill-throughs and tooltips
    • Syncing slicers across pages
  • Dashboard Design Principles
    • Building executive dashboards
    • Real-time dashboards and KPI monitoring
  • Overview of Databases
  • What is Data?
  • What is a Database?
  • Types of Databases (Relational vs Non-Relational)
  • What SQL is used for (CRUD operations)
  • SQL vs NoSQL
  •  Introduction to RDBMS
  • What is RDBMS?
  • Tables, Rows, Columns, Keys
  • Popular RDBMS Tools (MySQL, SQL Server, PostgreSQL, Oracle

  •  Setting Up SQL Environment

    • Installing MySQL / SQL Server / PostgreSQL
    • Using GUI Tools (MySQL Workbench, SSMS, PgAdmin)
    • Connecting to a Database
  1. Basic SQL Syntax
  • SQL Rules & Conventions
  • Case Sensitivity
  • Writing clean queries
  1. Retrieving Data
  • SELECT
  • FROM
  • WHERE (Filtering records)
  • Basic Comparisons (=, !=, <, >, BETWEEN)
  1. Sorting and Limiting
  • ORDER BY
  • LIMIT / TOP
  1. Basic Functions
  • COUNT()
  • MIN(), MAX()
  • SUM(), AVG()

5.Working With Text & Dates

  • UPPER, LOWER, LTRIM, RTRIM, CONCAT
  • Date functions (NOW(), GETDATE(), DATEADD, DATEDIFF)
  1. Grouping Data
  • GROUP BY
  • HAVING
  1. Joins
  • INNER JOIN
  • LEFT JOIN
  • RIGHT JOIN
  • FULL JOIN
  1. Data Modification
  • INSERT
  • UPDATE
  • DELETE
  • Transactions (BEGIN, COMMIT, ROLLBACK)
  • Publishing reports to Power BI Service
  • Creating dashboards from reports
  • Managing datasets and gateways

Course Structure

  • Saturday Live Classes for 2 months
  • 1-Month Capstone
  • CV Review
  • LinkedIn Optimization
  • Interview Preparation
  • Post-Training Support
  • Mentorship Sessions
  • Career Pathway Guidance

Chinyere Chukwuka

Data analytics facilitator

Chinyere Chukwuka is a Data Analyst and Data Scientist with close to a decade of hands-on experience across data, technology, and innovation-driven environments.

Her expertise spans the telecommunications, governance, finance, and edtech sectors, with a strong focus on using data to solve real business and operational problems. She has a solid academic and practical background in economics, covering pure economics, development economics, and econometrics. This foundation informs her analytical approach and enables her to deliver rigorous, evidence-based insights that support strategic decision-making across projects.

As the founder of Amdor Analytics, she has successfully guided individuals with no prior technology skills to smoothly transition into tech and secure their first roles.

Chinyere has personally trained over 6,000 participants