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Explore Data in Cloud Storage in SAP Data Intelligence, Trial Edition

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Explore Data in Cloud Storage in SAP Data Intelligence, Trial Edition

Explore Data in Cloud Storage in SAP Data Intelligence, Trial Edition

June 4, 2020
Created by
October 19, 2018
Explore data in Cloud Storage (including profiling) by using SAP Data Intelligence, trial edition.

You will learn

  • How to use SAP Data Intelligence Metadata Explorer
  • How to use Browse Connection
  • How to Profile a Dataset
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SAP Data Intelligence Metadata Explorer allows you to learn more about data residing in external storages, for example, Google Cloud Storage, AWS S3 or Windows Azure Storage Blob by profiling, previewing and viewing the metadata.

The Metadata Explorer gathers information about the location, attributes, quality, and sensitivity of data. With this information, you can make informed decisions about which datasets to share with other users and determine who has access to viewing or modifying the datasets.

Step 1: Discover and prepare data in Cloud Storage

In this section, you will use the data preparation tool to create a copy of a csv dataset that you will be working on and modifying throughout the four parts of this tutorial. A more in depth exercise of the data preparation tool will be covered in part 3.

  1. Log on as the system user and navigate to the Metadata Explorer application by clicking on the title at the launchpad.

    launchpad of Data Intelligence
  2. Go to Browse Connections. Connections are displayed in the grid view by default.

    • Click Browse Connections.

    • It can be changed into list view by selecting the “List View” button on the upper right.

    Go to Browse Connections
  3. Click the CLOUD_STORAGE connection to display the directories / files. The type of the CLOUD_STORAGE connection depends on the cloud provider you are using for the trial.

  4. On the Contacts.csv file use the more actions button to Prepare Data

    Prepare data
  5. Select Run Preparation under the Actions menu. In a few moments a copy of this CSV file will be written into CLOUD_STORAGE with the filename Contacts_USA.csv

    Write to Cloud Storage

    Return to the connection browser using the < icon in the upper left corner. After a minute or less a new copy of the file will appear. You may need to use the refresh button in the upper right corner to scan for changes.

    File copy: Customer_USA

You now have a copy of the original dataset with the new name Contacts_USA.csv that you will run data preparation on in a later section of this tutorial.

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Step 2: Profile dataset

Profiling produces additional metadata about the values in the dataset. For example, you can view the unique or distinct values, the minimum and maximum values, average length, and whether there are null, blank, or zero values. This information can help you determine which datasets may need cleansing, masking, or any number of options available in SAP Data Intelligence.

In this section, you will use the Metadata Explorer in SAP Data Intelligence to profile the Contacts_USA.csv dataset that you copied in the previous section.

  1. Begin by going to the Browse connection button via the Metadata Explorer drop down menu or the Metadata Explorer front page

    Go to Browse Connections
  2. Open the CLOUD_STORAGE connection

  3. Start profiling.

    • Click on the More Actions button for Contacts_USA.csv and from the context menu, click Start Profiling.

    • Click Yes to start the profiling task.

    • A pop-up message confirms that profiling has started. It can take up to several minutes for the profiling process to complete.

    Start profiling
  4. As soon as the profiling started, you will see a notification in the top right corner and you will see more details after you click on the icon.

  5. This process can take several minutes to complete and can be monitored using the Monitor Tasks menu

    Monitor TasksMonitor profiling job

In the next section you will inspect the fact sheet of the dataset that was generated by the profiling job.

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Step 3: View metadata and fact sheet
  1. After profiling is completed use the Refresh button in the Metadata Explorer application to update the file’s status and then More Options to view the fact sheet for the file Contacts_USA.csv.

    View Factsheet
  2. The fact sheet displays the dataset’s columns as well as its inferred data types. It can also display minimum and maximum values of the columns, percentage distribution between null values and top 10 distinct values.

    Factsheet, Details
  3. Select the column name Country and observe that you have multiple variations of USA. Note that the “no value” also includes null values. Also observe that the column ZipCode was automatically selected to be of data type Integer. You will be working with these two columns in the next section.

Take a moment to explore this dataset using Data Preview and the More Actions button on each of the columns.

Which value is ranked 1st under Top 10 distinct values for the column TITLE?

Next Steps

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