Introduction to Data Analysis with Excel

Introduction to Data Analysis with Excel

Subheading: Explore the key features of Microsoft Excel that make it such an essential tool for Data Analytics

One of the most rapidly developing areas in today's market is data analytics—it is also an area in which businesses are struggling to find qualified staff. In this course, we will explore the key features of Microsoft Excel that make it such an essential tool for data analytics.

Using the data analysis and visualization features that are native to Excel, this course will show you how to extract maximum value most efficiently from the information your organization collects. This course starts off with the fundamentals, walking you through all you need to understand about spreadsheets, from layout to applications. We will cover a variety of topics, including exploring formulas, cleaning data, and identifying data attributes.

This course demonstrates how to analyze data using Excel and tackle complicated criteria. We will use Excel charts to depict data, relationships, and potential outcomes. In addition, we will also be discussing how to use the what-if functionality of the Analysis ToolPak add-in that comes with Excel. Each section includes practical examples that show how to apply these techniques to real-world business problems.

After finishing this course, students will be able to:

• Describe the fundamentals of Excel spreadsheets, from their layout to the applications
• View, enter, and format data types in Excel
• Understand and apply Excel formulas and functions
• Import file data and remove duplicates
• Identify data attributes
• Sort data and apply filters, including advanced filtering techniques
• Apply Concatenation and Sum-if formulas to analyze data sets
• Create problem statements to tackle complicated “or” criteria
• Create Pivot tables and charts
• Work with Excel charts, including clustered columns, line graphs, and waterfalls
• Utilize database functions created specifically to work with large datasets
• Apply techniques to recognize and avoid formula errors
• Understand and use the What-If Analysis toolkit which includes the Scenario Manager, Goal Seek, and Data Table functions
• Use the Analysis ToolPak to calculate basic statistical concepts such as correlation and covariance
• Compute descriptive statistics and moving averages and apply exponential smoothing techniques
• Utilize rank and percentile options and generate histograms.