There's a joke in the data community that goes:
"You'll spend 90% of your time cleaning data, and the other 10% of your time complaining about cleaning your data."
Do you deal with badly formatted data that takes you hours to tidy up, preventing you from making progress on your "real" work?
Do you ever find yourself repeating a process manually, like extracting a zip code from an address?
Ever wondered what the heck a Pivot Table is, and why you should care about them?
This course is designed to help you work with messy, real-world datasets, and it's a fit for beginner-to-intermediate level Google Sheets users.
Through four hours of video tutorials, you'll learn techniques and best practices for cleaning data and preparing it for analysis and reporting -- saving you hours of tedious, repetitive work, and helping you get accurate results for your company.
What is Data Cleaning?
Data cleaning is the process of identifying and correcting errors, fixing incomplete data or dealing with irrelevant data in your data sets.
The goal of data cleaning is to create a consistent, clean data set, which gives you the confidence that any subsequent analysis and conclusions you draw will be accurate and thorough.
Why should you care?
Data cleaning is a crucial first step in the data analysis pipeline, yet one that people often overlook.
If you start with "bad" data -- if your data contains duplicate records for example -- you're inevitably going to end up with "bad" conclusions. You might end up double counting revenue, for example, which could have disastrous consequences for your business down the line.
This training course runs through professional techniques and best practices, using formulas and pivot tables, to clean your data, in a Google Sheets setting. Once you've grasped these concepts, you (and your boss!) will feel confident that your conclusions are based on sound data.What this course covers
What you get with this course:
Who is this course for?
What are the prerequisites?
"Before this course I had used a few simple formulas (okay Average and Sum only) but now I know how to use a vlookup as well as create Pivot Tables.
I’ve been making “Pivot Tables” wrong for years, entering all of the raw data myself. I am now able to make a Pivot Table that will update as needed. I like how Ben shows multiple ways to do data cleaning and why you would choose one method over the other. I enjoyed the case studies at the end because they brought the entire course together.
I will definitely be on the lookout for additional courses from Ben."
- Rachelle L.
"The course starts with a data cleaning section which is highly actionable and relevant to real world data sets that we all work with. My pivot table knowledge was pretty basic before this course and I am confident to say that I am now going to be able to implement them into my data analysis workflow.
This course also took my efficiency to the next level which is exactly what I needed as more of my time and analysis is starting to take place in sheets. I can't recommend this enough."
- John R.
"I am an academic librarian who has worked for years with massive raw data sets and pivot tables, and even gives related presentations at our regional conferences, and yet I learned from Ben's course several very useful tips and techniques that I didn't already know about and that will save me a lot of work.
I plan to recommend it to my colleagues as a very thorough course in getting data ready for the kind of data visualization contexts we need to provide to our decision-makers and stakeholders."
- Melissa B.
Ben Collins is an experienced data analytics instructor and freelance spreadsheet developer, helping businesses better understand their data through analytical insights and visualizations, including dashboards. He works primarily with Google Sheets, Apps Script and Data Studio, and also has extensive experience with Excel, SQL and Tableau. He previously taught data courses and workshops for General Assembly in Washington, D.C.