Data integration tutorial: Virtualize external data

Take this tutorial to virtualize data stored in three external data sources with the Data integration use case of the data fabric trial. Your goal is to use Watson Query to create virtual tables and to join the virtual tables together from the existing data that lies across three data sources: a Db2 Warehouse, a PostgreSQL database, and a MongoDB database. If you completed the Integrate data tutorial, then you did many of the same tasks using DataStage that this tutorial accomplishes using Watson Query.

The following animated image provides a quick preview of what you’ll accomplish by the end of this tutorial. You will connect to external data sources, create virtual tables and views, and add them to a project. Right-click the image and open it in a new tab to view a larger image.

Screenshots of the tutorial

The story for the tutorial is that Golden Bank needs to adhere to a new regulation where it cannot lend to underqualified loan applicants. You will use Watson Query to combine data from different data sources without data movement, and make the virtual data available to other data scientists and data engineers in a project.

In this tutorial, you will complete these tasks:

Task 1: Verify the Platform assets catalog.
Task 2: Add data connections to the Platform assets catalog.
Task 3: Add data sources to Watson Query.
Task 4: Virtualize data tables.
Task 5: Create virtual join views by joining virtual tables.
Task 6: Access the virtual join view in the project.
Cleanup (Optional)

If you need help with this tutorial, ask a question or find an answer in the Cloud Pak for Data Community discussion forum.

Tip: For the optimal experience completing this tutorial, open Cloud Pak for Data in one browser window, and keep this tutorial page open in another browser window to switch easily between the two applications. Consider arranging the two browser windows side-by-side to make it easier to follow along.

Side-by-side tutorial and UI

Preview the tutorial

Watch Video Watch this video to preview the steps in this tutorial. There might be slight differences in the user interface shown in the video. The video is intended to be a companion to the written tutorial.

This video provides a visual method as an alternative to following the written steps in this documentation.

Prerequisites

The following prerequisites are required to complete this tutorial.

Access type	Description	Documentation
Services	- Watson Query - Watson Knowledge Catalog (Optional)	- Watson Query - Watson Knowledge Catalog
Role	Data Engineer	- Predefined roles and permissions - Manage roles
Additional access	- Editor access to Platform connections - Editor access to Default catalog (Optional) - Engineer access to Watson Query service	- Add collaborators - Manage roles for users and groups in Watson Query
Additional configuration	Disable Enforce the exclusive use of secrets	Require users to use secrets for credentials

Follow these steps to verify your roles and permissions. If your Cloud Pak for Data account does not meet all of the prerequisites, contact your administrator.

Click your profile image in the toolbar.
Click Profile and settings.
Select the Roles tab.

The permissions that are associated with your role (or roles) are listed in the Enabled permissions column. If you are a member of any user groups, you inherit the roles that are assigned to that group. These roles are also displayed on the Roles tab, and the group from which you inherit the role is specified in the User groups column. If the User groups column shows a dash, that means the role is assigned directly to you.

Roles and permissions

Create the sample project

If you already have the sample project for this tutorial, then skip to Task 1. Otherwise, follow these steps:

Download the Data-Integration.zip file.
From the Cloud Pak for Data navigation menu , choose Projects > All projects.
On the Projects page, click New project.
Select Create a project from a file.
Upload the previously downloaded ZIP file.
On the Create a project page, copy and paste the project name and add an optional description for the project.
```
Data Integration
```
Click Create.
Click View new project to verify that the project and assets were created successfully.
Click the Assets tab, to view the project's assets.

Check your progress

The following image shows the Assets tab in the sample project. You are now ready to start the tutorial.

Tip: If you encounter a guided tour while you are completing this tutorial in the Cloud Pak for Data as a Service user interface, click Maybe later or close out the tour window.

Task 1: Verify the Platform assets catalog

You can add connections to external data sources at either the platform level or the service level. When you add the connections at the platform level by using the Platform assets catalog, you can easily include those connections in projects, catalogs, and Watson Query data sources. Follow these steps to verify the Platform assets catalog.

From the Cloud Pak for Data navigation menu , choose Data > Platform connections.
If you see existing connections, then you already have a Platform assets catalog, and you can skip to Task 2. If you don't see any connections, but you see an option to create a new connection, then you can skip to Task 2.
If you don't have access to add a connection to the Platform assets catalog, then contact your administrator.

Check your progress

The following image shows the Platform Connections catalog. On the Connections tab, you can create connections. Since the sample project includes the connections, you can add the connections for the external data sources to this catalog from the sample project.

Task 2: Add data connections to the Platform assets catalog

The Data integration sample project includes several connections to external data sources. Next, you add three connections to the Platform assets catalog, and then you can make these connections available in Watson Query. Follow these steps to publish the connections from the sample project to the Platform assets catalog.

From the Cloud Pak for Data navigation menu , choose Projects > All projects.
Click the Data integration project.

Note: You might see a guided tour showing the tutorials that are included with this use case. The links in the guided tour will open these tutorial instructions. If you already have the tutorial instructions open in a new window, then close out this guided tour.
Click the Assets tab.
Under Asset types, click Data access > Connections.
Select the following connection assets:
- Data Fabric Trial - Db2 Warehouse
- Data Fabric Trial - MongoDB
- Data Fabric Trial - Databases for PostgreSQL
Click Publish to catalog.
For the Target, select Platform assets catalog.
Click Publish.
From the Cloud Pak for Data navigation menu , choose Data > Platform connections to see the three connections that are published to the catalog.

Check your progress

The following image shows the Platform assets catalog with three connections. You are now ready to add data sources.

Task 3: Add data sources to Watson Query

Now you can add these external data sources from the Platform assets catalog to Watson Query. Follow these steps to add the data sources:

From the Cloud Pak for Data navigation menu , choose Data > Data virtualization.

Note: If you see a notification to *Set up a primary catalog to enforce governance*, you can safely close this notification. Setting up a primary catalog is optional.
From the service menu, choose Data sources.
On the Data sources page, in the Table view, click Add connection > Existing platform connection.
Select Data Fabric Trial - Db2 Warehouse.
Click Add.
On the Add to a remote connector page, click Skip.
Repeat these steps to add the Data Fabric Trial - Mongo DB and Data Fabric Trial - Databases for PostgreSQL connections.

Check your progress

The following image shows the data sources. You are now ready to create a virtual table from data stored in those external data sources.

Task 4: Virtualize data tables

You want to virtualize the MORTGAGE_APPLICATION, MORTGAGE_APPLICANT, and CREDIT_SCORES tables. Later, you can join the first two virtual tables with the third table to create a new virtual join view. Follow these steps to virtualize the data tables:

From the service menu, click Virtualization > Virtualize.
If necessary, change to List view, and wait while the tables load, which might take up to 30 seconds. You may need to click Refresh to see the complete list of tables.
On the Tables tab, filter the tables based on the following criteria:
1. Source type: IBM Db2 Warehouse and PostgreSQL
2. Database: Data Fabric Trial - Db2 Warehouse and Data Fabric Trial - Databases for PostgreSQL
3. Schema: BANKING
Select the MORTGAGE_APPLICATION, MORTGAGE_APPLICANT, and CREDIT_SCORE tables to virtualize. You can hover over a table name to see the full name to verify that you are selecting the correct table names.
Click Add to cart.
Click View cart to view your selection. From here, you can edit the table and schema names, or remove a selection from your cart.
For now, clear the checkbox next to Assign to project. This action will make the virtual tables available on the Virtualized data page.
Click Virtualize.
Click Confirm to begin virtualizing the tables.
When virtualization is complete, click Go to virtualized data to see your newly created table.

Check your progress

The following image shows the Virtualized data page. You are now ready to create a virtual table by joining these virtual tables.

Task 5: Create a virtual join view by joining virtual tables

You want to create a virtual join view by joining the MORTGAGE_APPLICANT and MORTGAGE_APPLICATION virtual tables. Then, you want to join the resulting virtual object with the CREDIT_SCORE virtual table to create a second virtual join view.

Virtual join view 1: Join the MORTGAGE_APPLICANT and MORTGAGE_APPLICATION virtual tables

Follow these steps to create the first virtual join view:

From the Virtualized data page, select the MORTGAGE_APPLICATION and MORTGAGE_APPLICANT tables to virtualize.
Make note of the schema name. You will need that name later to run an SQL query.
Click Join.
In the list of columns for MORTGAGE_APPLICATION table, drag to connect the ID column with the ID column in the MORTGAGE_APPLICANT table.
Click Preview to see a preview of the joined tables.
Close the preview window.
Click Open in SQL editor, and then click Continue at the notice that you are not able to return to the join canvas. The SQL Editor lets you run queries on the data set. In this case, you want to preview what records the data set will contain when you filter on California applicants.
1. Copy your schema, and then delete the existing query. You will need to insert your schema in the next SQL statement.
2. Copy and paste the following SELECT statement for the new query. Replace <your schema> with the schema name that you noted earlier.
```
SELECT * FROM <your-schema>.MORTGAGE_APPLICANT WHERE STATE_CODE LIKE 'CA'
```
  Your query looks similar to SELECT * FROM DATAENGINEER.MORTGAGE_APPLICANT WHERE STATE_CODE LIKE 'CA'
3. Click Run all.
4. After the query completes, select the query on the History tab. On the Results tab, you can see that the table is filtered to only applicants from the state of California.
5. Click Back to close the SQL editor.
Now that you previewed the data set filtered on California applicants, you will add this filter criteria to the virtual join view. For the MORTGAGE_APPLICANT table, copy and paste the following statement for the filter criteria. Replace <your schema> with the schema name that you noted earlier.
```
"<your-schema>"."MORTGAGE_APPLICANT"."STATE_CODE"='CA'
```
Your filter criteria looks similar to "DV_IBMID_663002GN1Q"."MORTGAGE_APPLICANT"."STATE_CODE"='CA'
Click Next.
You can edit the column names to differentiate between columns with the same name in both tables. In this case, keep the default column names, and click Next.
On the Assign and review page, for the View name, type APPLICANTS_APPLICATIONS_JOINED.
For now, clear the Assign to project option. Later, you create a virtual object and assign that to the Data integration project.
Click Create view.
When virtualization is complete, click Go to virtualized data to see your newly created join view.

Check your progress

The following image shows the Virtualized data page. You are now ready to create a second virtual join view.

Virtual join view 2: Join the APPLICANTS_APPLICATIONS_JOINED and CREDIT_SCORE virtual tables

Follow these steps to create the second virtual join view:

From the Virtualized data page, select the APPLICANTS_APPLICATIONS_JOINED and CREDIT_SCORE tables to virtualize.
Click Join.
In the list of columns for APPLICANTS_APPLICATIONS_JOINED table, drag to connect the EMAIL_ADDRESS column with the EMAIL_ADDRESS column in the CREDIT_SCORE table.
Click Preview to see a preview of the joined tables.
Close the preview window.
Click Next.
Accept the default column names, and click Next.
On the Assign and review page, for the View name, type APPLICANTS_APPLICATIONS_CREDIT_SCORE_JOINED.
This time, keep Assign to project selected, and then choose the Data integration project.
Click Create view.
When virtualization is complete, click Go to virtualized data to see your newly created join view.

Check your progress

The following image shows the Virtualized data page. You are now ready to work with the virtual data in your project.

Task 6: Access the virtual join view in the project

The virtual table was added to your project along with a connection to Watson Query. Follow these steps to open the project to see the virtual data and the connection information that is required to access the virtual data.

From the Cloud Pak for Data navigation menu , choose Projects > All projects.
Open the Data integration project.
Click the Assets tab.
Open any of the virtualized data. For example, click the APPLICANTS_APPLICATIONS_CREDIT_SCORE_JOINED data asset to view it.
Provide your credentials to access the data asset.
For the Authentication method, select Username and password.
Paste your Cloud Pak for Data Username and Password.
Click Connect.
Scroll through the data asset to see all of the applicants from the state of California.

Check your progress

The following image shows the virtual data in the project. You are now ready to analyze the virtual data.

As a data engineer at Golden Bank, you used Watson Query to combine data from different data sources and with different types. You used SQL syntax and accessed and combined data without data movement.

Cleanup (Optional)

If you would like to retake the tutorials in the Data integration use case, delete the following artifacts.

Artifact	How to delete
Connections in the Platform assets catalog	Remove an asset from a catalog
Virtualized data	Navigate to Data > Data virtualization; On the Virtualized data page, access the Overflow menu for a table, and select Remove.
Data sources	Navigate to Data > Data virtualization; On the Data sources page, click the Delete icon for a connection.
Data integration sample project	Delete a project

Next steps

Try other tutorials:
Sign up for another Data fabric use case.

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Parent topic: Data fabric tutorials