Data Collection

In Data Collection and Working with Excel®, participants learn how to build flexible models in Excel®, load data from files and the web, analyze data in tables and pivot tables, shape data through text processing, handle errors in formulas, use lookup tables, and construct customized charts and graphs.


Introduction to the Data Analytics Pipeline

  • Overview and Learning Objectives
  • The Data Analytics Pipeline

Essentials of Excel

  • Value, Type, and Format
  • Conditional Formatting
  • References and Formulas
  • Named Ranges
  • Working with Dates
  • Testing Conditions

Loading Data

  • Sources of Data
  • Delimited Files
  • Web Scraping

Working with Data in Tables

  • Tables
  • Slicers
  • Pivot Tables

Shaping Data with Text Processing

  • Data Shaping
  • Text Processing Functions
  • Converting Text to Numbers

Exploring Data Through Charts and Graphs

  • Common Charts
  • Customizing Charts
  • Sparklines

Building Flexible Models with Lookup Tables

  • Exact Match Lookup
  • Approximate Match
  • Handling Errors
  • Alternate Lookup Functions

Practicum (optional)

Data Collection Summary

Practical Application and Demonstrations

The Data Collection portion of the program features over 10 demonstrations, 5 hands-on exercises, examples, and formal discussions.

Provided with multiple real-world data sets, participants gain in-depth practice using Microsoft® Excel.


The day culminates with a practicum, where participants work individually to build a complete spreadsheet model.