Microsoft Excel for Data Analysis

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Duration 2 days – 14 hrs

 

Overview

 

This practical training course is designed to equip participants with the essential skills to leverage Microsoft Excel for data preparation, analysis, and visualization. Through hands-on exercises, learners will explore how to clean and structure data, use analytical functions, create pivot tables, and build dynamic charts. The course is ideal for professionals looking to enhance their data-driven decision-making skills using Excel.

 

Objectives

 

  • Import, clean, and organize raw datasets in Excel
  • Apply key Excel functions for data transformation and analysis
  • Use PivotTables and PivotCharts for summarizing and visualizing data
  • Create interactive dashboards using Excel tools
  • Perform basic statistical analysis to support business insights

 

Audience

  • Business professionals handling data regularly
  • Analysts and administrative staff
  • Marketing, finance, HR, and operations teams
  • Anyone seeking to improve their Excel skills for data analysis

 

Pre- requisites 

  • Basic knowledge of Microsoft Excel (e.g., formulas, cell formatting)
  • No prior experience in data analysis is required

Course Content

 

Day 1: Foundations of Data Analysis in Excel

 

Getting Started with Excel for Data Analysis

 

  • Overview of Excel’s capabilities for data work
  • Setting up data-friendly spreadsheets

 

Data Cleaning and Preparation

 

  • Removing duplicates
  • Data validation
  • Text to Columns, Flash Fill, Find & Replace
  • Sorting and filtering data

 

Essential Excel Functions for Analysis

 

  • Logical: IF, AND, OR
  • Lookup: VLOOKUP, HLOOKUP, XLOOKUP
  • Text: LEFT, RIGHT, MID, LEN, TRIM
  • Date and Time: TODAY, NOW, DATEDIF
  • Math and Statistics: SUMIF(S), COUNTIF(S), AVERAGEIF(S)

 

Hands-On Exercise:

 

  • Cleaning and analyzing a sample dataset

 

Day 2: Data Summarization, Visualization, and Reporting

 

Using Tables and Named Ranges

 

  • Converting data to tables
  • Structured references

 

PivotTables and PivotCharts

 

  • Creating and customizing PivotTables
  • Adding slicers and timelines
  • Building PivotCharts for summaries

 

Data Visualization Techniques

 

  • Column, bar, line, pie, and combo charts
  • Conditional formatting and sparklines
  • Creating summary dashboards

 

Basic Data Analysis Techniques

 

  • Descriptive statistics using Excel
  • Trend identification and forecasting basics

 

Capstone Activity:

 

  • Build a mini-dashboard from a raw dataset
  • Present insights using visualizations

 

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