Practical Excel Data Analysis

Course Overview

The Practical Excel Data Analysis course provides hands-on training in using Microsoft Excel to collect, clean, organize, analyse, and present real-world data. Participants will work with practical datasets to develop skills in formulas, data cleaning, PivotTables, charts, dashboards, statistical analysis, forecasting, and reporting. The course emphasizes practical problem-solving and the application of Excel data analysis techniques to workplace situations.

Target Participants

  • Finance and accounting professionals
  • Business and data analysts
  • Managers and supervisors
  • Monitoring and evaluation professionals
  • Researchers and project officers
  • Human resource professionals
  • Marketing and sales professionals
  • Procurement and supply chain professionals
  • Operations and administrative professionals
  • Entrepreneurs and business owners
  • Students and professionals working with data

Course Objectives

By the end of the course, participants will be able to:

  • Import and organize real-world datasets in Excel.
  • Clean and prepare data for analysis.
  • Apply Excel formulas and functions to practical data problems.
  • Use XLOOKUP, INDEX-MATCH, SUMIFS, COUNTIFS, and related functions.
  • Analyse data using PivotTables and PivotCharts.
  • Perform descriptive, comparative, and trend analysis.
  • Create professional charts and data visualizations.
  • Develop interactive dashboards and KPI reports.
  • Conduct basic forecasting and what-if analysis.
  • Use Power Query to clean and combine datasets.
  • Prepare professional analytical reports.
  • Interpret data and communicate meaningful insights.
  • Apply Excel analysis techniques to practical workplace problems.

Course Outline

Module 1: Practical Excel Data Analysis Fundamentals

  • Understanding data analysis
  • Excel data analysis workflow
  • Setting up analytical workbooks
  • Excel tables and structured references
  • Organizing datasets
  • Practical data analysis exercises

Module 2: Data Cleaning and Preparation

  • Identifying data errors
  • Removing duplicate records
  • Handling missing and inconsistent data
  • Data validation
  • Sorting and filtering
  • Text-to-columns
  • Conditional formatting
  • Practical data-cleaning exercises

Module 3: Excel Formulas for Data Analysis

  • IF and IFS functions
  • SUMIFS and COUNTIFS
  • AVERAGEIFS
  • XLOOKUP
  • INDEX and MATCH
  • Text functions
  • Date functions
  • Error-handling functions
  • Practical formula exercises

Module 4: PivotTables and PivotCharts

  • Creating PivotTables
  • Summarizing datasets
  • Grouping and filtering
  • Calculated fields
  • PivotCharts
  • Slicers and timelines
  • Practical reporting exercises

Module 5: Practical Statistical Analysis

  • Mean, median, and mode
  • Minimum and maximum
  • Range
  • Variance and standard deviation
  • Percentages and ratios
  • Frequency analysis
  • Comparative analysis
  • Practical statistical exercises

Module 6: Data Visualization

  • Selecting appropriate charts
  • Column and bar charts
  • Line charts
  • Pie charts
  • Combination charts
  • Conditional formatting
  • Dynamic charts
  • Presenting analytical findings

Module 7: Practical Dashboards

  • Dashboard design principles
  • KPI development
  • Interactive dashboards
  • Performance scorecards
  • Dynamic visualizations
  • Management reporting
  • Practical dashboard development

Module 8: Forecasting and What-If Analysis

  • Trend analysis
  • Moving averages
  • Basic forecasting
  • Goal Seek
  • Scenario Manager
  • Sensitivity analysis
  • Practical business scenarios

Module 9: Power Query for Practical Analysis

  • Importing data from different sources
  • Cleaning and transforming data
  • Merging datasets
  • Appending datasets
  • Automating data preparation
  • Refreshing analytical reports 

Course Schedules:

Dates Fees Location Apply