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Transforming data

1. Transforming data

Nice job so far! Let's move to transforming data.

2. Transforming data

Why do we need to transform data? Well, datasets rarely come in a perfect form and you need to transform the data to fit your needs. Depending on what you want to do, there may be columns you don't need or inconvenient and inconsistent formatting of values. Often there are processing errors that cause extra characters or blank rows. These are just a few examples. This type of transformation is often referred to as "cleaning data".

3. Loading data

Previously when you loaded data, this preview pop-up screen appeared

4. Loading data

and we immediately loaded the data.

5. Loading data

Now, in the next exercises, we will transform first.

6. Power Query Editor

Specifically, you will use the Power Query Editor which is a tool that allows you to edit the data prior to loading it. You can use it to format the dataset and decide what gets loaded. The Power Query loads in another screen shown here and uses a language called M. However, you don't need to know M to use it. Note that because the Power Query Editor opens in a separate window, you'll need to close it to go back to your report.

7. Don't forget to Close & Apply

An important thing to know about Power Query is that you need to close and apply for any changes to be made to the data in the report.

8. Let's practice!

Alrighty, let's get started!

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