Data Analysis and Visualization with Excel

You’re too smart to settle for boring spreadsheets! From PivotTables to sleek dashboards, we’ve got you covered.

(DATA-VIS-XLS.AD1) / ISBN : 978-1-64459-259-5
This course includes
Interactive Lessons
Gamified TestPrep
Hands-On Labs
AI Tutor (Add-on)
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About This Course

This Excel data analysis and visualization course is your backstage pass to developing the advanced analytical skills required for career progression. You’ll learn how to build dynamic PivotTables, craft eye-catching charts, and design interactive dashboards that impress. In this advanced course, we’ll walk you through powerful tools like Power Query and Power Pivot to improve your skills and transform raw data into crystal-clear insights.

Skills You’ll Get

  • Create, modify, sort, and filter tables for Excel skill development
  • Design and format charts, graphs, and visual elements to present data effectively 
  • Learn Excel functions like lookup and logical functions for efficient data analysis 
  • Create and analyze data with PivotTables and visualize insights with PivotCharts
  • Build interactive dashboards with slicers, timelines, and other visualization tools
  • Create and customize map charts to analyze geographic data
  • Use Excel’s trendlines, sparklines, and Data Analysis ToolPak for statistical insights 
  • Connect, clear, and transform data from various sources using Power Query 
  • Develop complex data models and perform advanced data analysis with Power Pivot 
  • Design professional reports and templates for presenting insights and data findings

1

Introduction

  • Course Description
  • How to Use This Course
  • Course-Specific Technical Requirements
2

Data Analysis Fundamentals

  • Topic A: Introduction to Data Science
  • Topic B: Create and Modify Tables
  • Topic C: Sort and Filter Data
  • Summary
3

Visualizing Data with Excel

  • Topic A: Visualize Data with Charts
  • Topic B: Modify and Format Charts
  • Topic C: Apply Best Practices in Chart Design
  • Summary
4

Analyzing Data with Formulas and Functions

  • Topic A: Analyze Data with Formulas and Named Ranges
  • Topic B: Analyze Data with Functions
  • Topic C: Implement Data Validation, Forms, and Controls
  • Topic D: Create Conditional Visualizations with Lookup Functions
  • Summary
5

Analyzing Data with PivotTables

  • Topic A: Create a PivotTable
  • Topic B: Analyze PivotTable Data
  • Summary
6

Presenting Visual Insights with Dashboards in Excel

  • Topic A: Visualize Data with PivotCharts
  • Topic B: Filter Data Using Slicers and Timelines
  • Topic C: Create a Dashboard in Excel
  • Summary
7

Creating Geospatial Visualizations with Excel

  • Topic A: Create Map Charts in Excel
  • Topic B: Customize Map Charts in Excel
  • Summary
8

Performing Statistical Analysis

  • Topic A: Visualize Trendlines and Sparklines with Excel
  • Topic B: Analyze Data with the Data Analysis ToolPak
  • Summary
9

Getting and Transforming Data

  • Topic A: Connect to Data with Queries
  • Topic B: Clean and Combine Data
  • Topic C: Shape and Transform Data
  • Summary
10

Modeling and Analyzing Data with Power Pivot

  • Topic A: Install Power Pivot in Excel
  • Topic B: Create Data Models with Power Pivot
  • Topic C: Create Power Pivots
  • Topic D: Perform Advanced Data Analysis and Visualization
  • Summary
11

Presenting Insights with Reports

  • Topic A: Plan a Report
  • Topic B: Create a Report
  • Summary

1

Data Analysis Fundamentals

  • Analyzing Data
  • Creating and Modifying a Table
  • Sorting and Filtering Data
2

Visualizing Data with Excel

  • Creating Charts
  • Modifying and Formatting Charts
  • Applying the Best Practices of Chart Design
3

Analyzing Data with Formulas and Functions

  • Analyzing Data Using Formulas
  • Analyzing Data Using Functions
  • Working with Logical Functions
  • Implementing Data Validation
  • Implementing Form Controls
  • Using LOOKUP Functions
4

Analyzing Data with PivotTables

  • Creating PivotTables
  • Analyzing the PivotTable Data
5

Presenting Visual Insights with Dashboards in Excel

  • Visualizing Data with PivotCharts
  • Filtering Data Using Slicers
  • Filtering Data Using Timelines
  • Creating a Dashboard in Excel
6

Creating Geospatial Visualizations with Excel

  • Creating Map Charts in Excel
  • Formatting and Customizing Map Charts
7

Performing Statistical Analysis

  • Visualizing Trendlines in Excel
  • Visualizing Sparklines in Excel
  • Installing and Activating the Data Analysis ToolPak
  • Performing Statistical Analysis with the Data Analysis ToolPak
8

Getting and Transforming Data

  • Connecting to Data with Microsoft Power Query
  • Cleaning and Combining Data using the Power Query Editor
9

Modeling and Analyzing Data with Power Pivot

  • Installing and Activating Power Pivot
  • Creating Data Models with Power Pivot
  • Creating Power Pivots
  • Creating a KPI
  • Creating a New Perspective
10

Presenting Insights with Reports

  • Creating a Report in Excel
  • Creating a Template of a Report

Any questions?
Check out the FAQs

Satisfy your curiosity with our dedicated FAQ section on Excel data analysis and visualization.

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Yes! Excel’s advanced tools like Power Query, Power Pivot, and the Data Analysis ToolPak allow users to perform complex data transformations, and statistical analyses, and create sophisticated data models.

Power Query is used to connect, clear, and transform data from different sources, while Power Pivot allows you to create advanced data models and perform complex calculations on large datasets.

To analyze data with PivotTables, organize your data, drag and drop fields to summarize, filter, and sort large datasets, making it easier to extract meaningful insights.

Excel data analysts can pursue careers in fields like business analysis, financial analysis, data science, and marketing analytics. Roles include Data Analysts, Business Intelligence Analysts, and Financial Analysts.

The average salary for a data analyst with advanced Excel skills in the U.S. ranges from $55,000 to $80,000 per year, depending on experience, location, and industry.

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