There are many ways to bring your data into your project, in this section we'll cover using from the following data sources:
Using virtualized data
Note: The lab instructions below assume you have your project already available. If not, follow the instructions in the pre-work section to create a project.
For this section we'll explore the data that is available from the virtualized views that have been created in Data Virtualization. This data may come from various data sources or tables within a single source, but will appear as a single data asset. We will add this data to an analytics project so that it can be used in subsequent modules of this workshop (i.e for data analysis and to build ML models).
From the upper-left (☰) navigation menu, click on
Click on the
My virtualized data option from the data virtualization sub-menu. Here you should see the data you have virtualized or that you have been given access to (or that the administrator has assigned to you).
Select the checkbox next to the data sets you want to use in your project and click the
Assign button to start importing it to your project.
Note: The name of the data assets to select may vary based on names chosen during data virtualization. The default names to select are: LOANS, APPLICANTFINANCIALDATA, APPLICANTPERSONALDATA, APPLICANTFINANCIALPERSONALDATA AND APPLICANTFINANCIALPERSONALLOANDATA
In the 'Assign virtual objects' screen, choose your analytics project from the drop down list. If there is a
Submit to catalog checkbox on the top right, unselect it and, finally, click the
Assign button to add the data to your project.
In the pop up panel, you will receive a confirmation that the objects have been assigned to your project. Click the
Go to project button.
In the project page, clicking on the
Assets tab will show the virtualized tables and joined tables that are now in your project (along with other assets that are in the project).
Do not go to the next section until you see the data assets in your project.
This lab shows just one of the ways to gather data for your analytics projects in Cloud Pak for Data. In this case you used data that was previously virtualized. Other ways might include: browsing the catalogs, importing flat files, or importing data from connections directly in the project.