Top Ten Tips: Data Analysis

Top Ten Tips: Data Analysis
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£18.00 per seat

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In a world where we are constantly bombarded with information, making sense of it all can sometimes be difficult and time-consuming. This is particularly true of Excel.

Analysing large amounts of data and presenting information that makes sense to your audience is an essential skill for many professionals, especially accountants, bookkeepers, marketing professionals, salespeople and those who need to learn the tools, techniques and most useful formulas for analysing data.

In this short, ten module course we aim to teach you the basic skills you need to analyse data effectively and efficiently. From Pivot Tables and Conditional Formatting to Lookup Formulas and beyond, 'Excel Data Analysis' will set you up with a great foundation upon which to build further skills.


  • PC or Mac with the full version of Microsoft Excel (any version from 2007 onwards but most suited to PC version 2013/2016 or Office 365).
  • A basic knowledge of Excel's structure, layout and ribbons.
  • Not a requirement but a benefit to have at least a basic working knowledge of Excel commands and functionality.

Relevant audiences

  • Anyone who needs to make sense of large amounts of data.
  • Accountants, bookkeepers, marketing professionals, salespeople - anyone who wants to learn the tools, techniques and most useful formulas for analysing data.

Learning Outcomes

  • Clean raw data in order to prepare it for a PivotTable.
  • Build a PivotTable from scratch and use it to perform deep analysis on your data, including creating visually appealing PivotCharts.
  • Utilise helpful lookup functions to lookup a value in one column and return the value in another.
  • Perform logical tests using IF Statements.
  • Create Conditional Formatting rules to highlight data based on specific criteria in order to quickly visualise data in a spreadsheet.
  • Build an interactive dashboard to display information in a visual way and make it easy to analyse for others using interactive tools.


Section 1: Introduction

  • Unit 1.1 - Getting Started

Section 2: Building a Good Foundation

  • Unit 2.1 - Preparing Data for Analysis

Section 3: Analysing Large Datasets

  • Unit 3.1 - PivotTables

Section 4: Looking Up Information

  • Unit 4.1 - Lookup Functions

Section 5: Decision Making

  • Unit 5.1 - Logical Functions

Section 6: Presenting Data

  • Unit 6.1 - Conditional Formatting

Section 7: Creating an Impact

  • Unit 7.1 - Building an Interactive Dashboard