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Einstein Analytics Datasets

Learning Objectives

After completing this unit, you’ll be able to:
  • Understand why the story in your data can be difficult to spot.
  • Create an Einstein Analytics dataset.

There’s a Story Buried in the Data

Every dataset tells a story. But it’s difficult to excavate that story when you’re dealing with enormous tables of data and many variables with complex relationships. Take the example we’ve been looking at, shrinking margins in an auto parts supply company. To do a thorough analysis, you need to consider not just inventory, but also particular markets, distributors, incentives, and likely many other factors.

Your company feels the pain of shrinking margins. But learning the source of that pain by sifting through a huge amount of data is a lot of work. Luckily for us, we have Einstein Discovery. It quickly analyzes huge amounts of data to expose correlations that we can investigate. It shows us where to look for solutions, and predicts what might happen based on these correlations.

Put yourself back in the role of VP of operations, and let’s create your first story.

Try Einstein Discovery with a Developer Edition Org

Before you work through this Trailhead module, sign up for a free Analytics-enabled Developer Edition org. This org is a safe environment where you can practice the skills you’re learning.


For this trail, you can’t use an existing Developer Edition org. Instead, sign up for this special Developer Edition org because:

  • It comes provisioned with the Analytics Plus license required for Einstein Discovery.
  • It has Einstein Discovery enabled.
  • It has the Einstein Analytics Plus permission set needed to use Einstein Discovery features.
Even if you already have an Analytics-enabled Developer Edition org, sign up for a new one now. The older Analytics-enabled Developer Edition orgs don’t get recently released features. Therefore, signing up for a new one ensures that you get the latest and greatest.

Sign-up Steps

Let’s get you set up so you can log in and get started.

  1. Go to
  2. Fill out the form using an active email address. Your username must also look like an email address and be unique, but it doesn’t need to be a valid email account. For example, your username can be, or you can put in your company name.
  3. After you fill out the form, click Sign me up. A confirmation message appears.Confirmation message appears, asking you to check your email.
  4. When you receive the activation email, open it and click the link.
  5. Complete your registration, and set your password and challenge question.


    Write down or remember your credentials. To log in and play, go to

  6. Click Save.

    You are logged in to your Analytics Developer Edition org and redirected to the Setup page.

Way to go! You now have a Salesforce org! Let's jump right in.

Download the Data

Before we can create a story, we need the data we want to analyze. We’ve prepared a file with the necessary data to create a dataset for the auto parts company in our example. Download the CSV file called APdist.csv and save it to your computer.

Create and Populate an Einstein Analytics Dataset

The next step is to get the data from the CSV file into an Einstein Analytics dataset.
  1. In your new DE Org, switch to Lightning Experience (if you have not already done so).
  2. Click the App Launcher App Launcher icon, search for Analytics Studio, and then click the tile to launch Analytics Studio.
    App Launcher


    Be sure to set your popup blocker to allow popups. Otherwise, your connected app doesn’t launch.

  3. On the Analytics Studio home tab, click Create | Dataset, and select CSV File.
  4. In the file-selection window that opens, find the CSV file—APdist.csv—you downloaded, select it then click Next.
  5. In the Dataset Name field, change the default name, if you want.
    By default, Analytics Studio uses the file name as the dataset name. The name cannot exceed 80 characters.
  6. Select the app where the dataset will be created.
    By default, Analytics Studio selects your My Private App. To change an app, click the cross on it and select a different one.
  7. Click Next.
    The Edit Field Attributes screen appears. Here, you can preview the data, and view or edit the attributes for each field. Ecit Field Attributes screen
  8. For now, accept the defaults, and click Upload File.
    Analytics Studio uploads the data, prepares and creates the dataset, and shows you progress as it happens. Ecit Field Attributes screen
Now that you’ve built an Einstein Analytics database, let’s find out how Einstein Discovery can help you explore what’s in it. You’ll do that in the next unit.