Start tracking your progress
Trailhead Home
Trailhead Home

Build Your Einstein Analytics Dataset

Learning Objectives

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

There Are Insights Buried in Your Data

Your data contains hints that can point to valuable insights. But it’s difficult to identify those hints and excavate insights 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 must 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 vast amount of data is an immense undertaking. Luckily, we have Einstein Discovery to help us power through this challenge. It quickly analyzes all the many rows and columns of data to identify and expose correlations that we can investigate. It shows us where to look first by surfacing insights according to statistical significance. It makes predictions on what could happen, and even suggests ways in which to improve predicted outcomes.

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.
Note

Note

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 required to access 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 features.

Sign-up Steps

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

  1. Go to developer.salesforce.com/promotions/orgs/analytics-de.
  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 yourname@analyticsrocks.de, 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.
  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.

Note

Note

Consider writing down your credentials. To log in and play, go to login.salesforce.com

Download the Data

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

Note

Note

Our example CSV file contains over 32,000 rows of data. In general, the more rows of data you have to analyze, the better the results. You need a minimum of 50 rows of data. If you want predictions and recommendations, you need 400 rows. Powered by AI and machine learning, you can analyze up to 20 million rows of data with Einstein Discovery!

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. From the App Launcher ( App Launcher icon), find and select Analytics Studio.
  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, and 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 you want to create the dataset. 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 dataset, let’s find out how Einstein Discovery can help you explore what’s in it. You’ll do that in the next unit.