In this course, you'll walk through Trifacta basics step by step. We'll take you through not only how to use Trifacta and its transforms and functions, but also what common pitfalls you might encounter along the way while cleaning data. You'll see the real experience of data cleaning. Data cleaning isn't always clearcut, and this is why we'll show you what it looks like to iterate changes on your dataset as new information presents itself during the data preparation/data munging process.
By the end of this course, you'll feel like you're one of the data pros. All you'll need to do is continue using your newly acquired skills to keep them fresh!
Note: Data analysts and scientists spend up to 80 percent of their time preparing and cleaning their data. This is a lot of time that could be used in more important phases of the data life cycle, so saving time at the data preparation stage gives you a competitive edge in the data space because you can use saved time toward more important things, like analyzing your data.
Forrester research identifies data preparation tools as “must haves” and ranks Trifacta and one other competitor in the lead. Not only that, the product is guided by a board of advisors that has the likes of DJ Patil and Jeff Hammerbacher, among other notables. The company has designed the product to guide you through the data prep, requiring less coding skills.
This tests your understanding of Trifacta basics
This tests your understanding of pattern symbols.
This quiz tests on the various operators we've covered in this section.
Hi there! I'm Curtis Seare, and I'm Ginette Methot, and we cohost an Austin-based podcast called. We are passionate that, no matter where you are or what work you do, you can learn to be data literate in a data-focused world, not only to understand a changing world culture, but also to do fascinating things, because you can with the right tools and instruction. We're excited to introduce you to a new world of wonder.
I didn't know I would end up working with data. In fact, I thought I was headed to get a PhD in Chemistry, but that all changed when I decided to go into business instead. Now I've worked for over eight years in the data space. I received my master's from Northwestern in Predictive Analytics, and I am now the Director of Analytics at an Austin-based startup, where I work in the thick of data every day. I'll teach you what I've learned over the years.
I'm new to data (so that's why I know that if I can pick it up, you definitely can!). My degrees are in the humanities and English, and I've worked as an editor and writer for many years—so very far from data. But is it? There's a TON of work being done in traditionally non-data-focused fields, including English and humanities. So let your imagination run wild with what might be possible with data in your field, and gain the tools to bring that dream to life.