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Customer 360 tutorial: Configure a 360-degree view
Customer 360 tutorial: Configure a 360-degree view

Customer 360 tutorial: Configure a 360-degree view

Take this tutorial to configure a 360-degree view of customers with the Customer 360 use case of the data fabric trial. The goal of this tutorial is to combine customer data with credit score data to resolve entities across the data and create a consolidated 360 view of customers.

The following animated image provides a quick preview of what you’ll accomplish by the end of the Customer 360 use case tutorials where you will set up and add assets to master data, map the data asset attributes, publish the data model and run matching, publish the matched data to a catalog, explore and visualize the matched data.

Customer 360 preview

Golden Bank wants to run a campaign to offer lower mortgage rates. As a data engineer, you must use IBM Match 360 to set up, map, and model your data for a 360-degree view of the customer.

In this tutorial, you can complete the following tasks:

  1. Create a catalog for the matched data.
  2. Set up and add assets to master data
  3. Map the data asset attributes.
  4. Publish the data model and run matching.
  5. Publish the matched data to a catalog.

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 as a Service in one browser tab, and keep this tutorial page open in another browser tab to switch easily between the two applications.

Preview the tutorial

Watch Video Watch this video to preview the steps in this tutorial. There might be differences between the written tutorial and the video tutorial.

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

Prerequisites

Sign up for Cloud Pak for Data as a Service

You must sign up for Cloud Pak for Data as a Service and provision the necessary services for the Customer 360 use case. If you have a Lite plan account, only one user per account can run this tutorial.

You can sign up for Cloud Pak for Data as a Service in any of these ways:

Provision the necessary services

Watch Video To preview this task, watch the video beginning at 00:50.

Important: The Match 360 service is available in the Dallas region only. If necessary, switch to the Dallas region before continuing.

Follow these steps to verify or provision the necessary services.

  1. In Cloud Pak for Data, click your profile icon to verify that you are in the Dallas region. If not, click Change region, and then select Dallas.
    Change region
  2. From the Cloud Pak for Data navigation menu Navigation menu, choose Services > Service instances.
  3. Use the Product drop-down box to determine whether an IBM Match 360 with Watson service instance exists.
  4. If you need to create a IBM Match 360 service instance, click Add service.
  5. Select IBM Match 360 with Watson.
    1. For the region, select Dallas.
    2. Select the Lite plan.
    3. Click Create.
  6. Repeat these steps to verify or provision the following services:
    • Watson Knowledge Catalog
    • Cloud Object Storage

Checkpoint Check your progress

The following image shows the provisioned service instances.

Provisioned services

Create the sample project

Watch Video To preview this task, watch the video beginning at 01:30.

If you need to create the sample project for this tutorial, follow these steps:

  1. From the Cloud Pak for Data navigation menu Navigation menu, choose Projects > View all projects.
  2. Click New project.
  3. Click Create a project from a sample or file
  4. Click the From sample tab.
  5. Select the Customer 360 guided tutorial sample project in the gallery.
  6. If you are prompted to associate the project to a Cloud Object Storage instance, select a Cloud Object Storage instance from the list.
  7. Click Create.
  8. Click View new project to verify that the project and assets were created successfully.

Checkpoint Check your progress

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

Sample project

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

Task 1: Create a catalog

Watch Video To preview this task, watch the video beginning at 02:08.

You need a catalog for the master data and for access to the matched data. With the Watson Knowledge Catalog Lite plan, you can create two catalogs. If you already have two catalogs, you can use one of your existing catalogs and skip this step. Otherwise, follow these steps to create a catalog to use the automap feature and publish your consolidated data asset.

  1. From the Cloud Pak for Data navigation menu Navigation menu, choose Catalogs > View all catalogs.
  2. If you see a catalog on your Catalogs page, then skip to Task 2: Set up and add assets to master data. Otherwise, follow these steps to create a new catalog.
  3. Click Create Catalog.
  4. For the Name, copy and paste the catalog name exactly as shown with no leading or trailing spaces: Customer 360 Catalog
  5. Select Enforce data policies, confirm the selection, and accept the defaults for the other fields.
  6. Click Create to use the default settings. Your new catalog opens. You can start adding assets and collaborators to it.

Checkpoint Check your progress

The following image shows your catalog. Now that you have a catalog, you can set up master data and add the data assets.

Customer 360 Catalog

Task 2: Set up and add assets to master data

Watch Video To preview this task, watch the video beginning at 02:43.

You must add all of the data assets that you want to consolidate to master data. The sources of data can be from sources that include your computer's hard disk or a data asset from a project or catalog.

  1. From the Cloud Pak for Data navigation menu Navigation menu, choose Data > Master data. Tip: If you encounter a guided tour after launching Master data, click Maybe later.
  2. If you need to set up master data, click Set up master data and follow the steps to associate the required services. Otherwise, click Go to configuration and continue to the next step.
    1. Select your Cloud Object Storage service, then click Next.
    2. Select your Customer 360 service, then click Next.
    3. Select your existing catalog named Customer 360 Catalog, then click Finish.
    4. Click Continue with configuration to complete the setup.
  3. Click Start with data assets.
  4. Click Add data.
  5. Add all 3 of the data assets in the project:
    1. Click the Find and add data icon to open the Data assets panel.
    2. Select the Project tab.
    3. Hover over each file in the project and click the checkbox of Campaign Prospects.csv, Customers.csv, and Experiancc.csv.
    4. Click the Insert icon and click Add data to confirm.
  6. Assign the Person record type to your data assets. Record Type provides information about the type of data that an asset contains. Each asset needs to have an assigned record type so that IBM Match 360 can find the part of the model that best fits the data.
    1. Select each checkbox of the Campaign Prospects.csv, Customers.csv, and Experiancc.csv assets and click Set asset properties.
    2. For each asset, click the Record type drop-down menu, and select Person.
    3. Click Save.

Checkpoint Check your progress

The following image shows the assets added to master data. Now that you set up master data and added the three data assets, you are ready to begin mapping the data asset attributes.

Assets added to master data

Task 3: Map the data asset attributes

Watch Video To preview this task, watch the video beginning at 04:06.

For IBM Match 360 to match all of your data, you must specify which columns of each data set are mapped to specific attributes that are understood by IBM Match 360. Follow these steps to map the data asset attributes.

  1. Click the Mapping tab to map the columns of the Campaign Prospsects.csv data asset to the IBM Match 360 data model as suggested in Table 1: Campaign Prospects.csv mapping.
  2. In the Asset list panel, select Campaign Prospects.csv.
  3. Click Profile and when prompted, click Start profiling to prepare IBM Match 360 to map the data automatically.
  4. When the profiling is complete, click Yes, automap.
  5. Click each column to review the automapped data and ensure that each source column is mapped to the same target attributes that are suggested in Table 1: Campaign Prospects.csv mapping. You can select a column to change its mapping by either selecting an existing attribute, creating a new simple attribute, or excluding columns, then click Map and save to data model.
  6. Repeat Task 3 for the Customers.csv and Experiancc.csv assets. Use the respective tables to map the columns for the Customers.csv and Experiancc.csv assets to the IBM Match 360 data model as suggested in Table 2: Customers.csv suggested mapping and Table 3: Experiancc.csv suggested mapping.

Refer to the examples that explain how to manually map individual attributes. You can either Map a column to an existing attribute, create a simple attribute for mapping, or exclude a column from mapping.

Example: Map an existing attribute

Watch Video To preview this task, watch the video beginning at 04:44.

This example explains how to map the Source column in the Campaign Prospects.csv data asset to the existing attribute Record source. IBM Match 360 provides some attributes that are commonly associated with customer records that you can choose to map the columns in your data set to.

  1. From the Asset list, select Campaign Prospects.csv and click the column that is named Source.
  2. From the Mapping targets panel search field that appears, in the search field, type the name of the existing attribute Record source.
  3. Click Map and Save to data model to map the column to the attribute. The column displays as Mapped and Mapped to: Record source.

You can repeat these steps to map other columns of your data assets to existing attributes that either you previously created or provided by IBM Match 360.

Example: Create a simple attribute

Watch Video To preview this task, watch the video beginning at 05:08.

This example explains how to create a new simple attribute to map the Lead Quality column in the Campaign Prospects.csv data asset with the same name as the column. If no existing attribute that you want to map the column you selected to, you can create an attribute.

  1. From the Asset list, select Campaign Prospects.csv and click the column that is named Lead Quality. You might need to scroll the data view for the column to appear.
  2. From the Mapping targets panel that appears, click + > Create attribute.
  3. Complete the required fields:
    • Attribute type → Simple attribute
    • Attribute label → Lead Quality
    • Attribute name → lead_quality
    • Description → Lead Quality
  4. Click Create > Create and map to accept the rest of the default values and create a new attribute and map the selected column to it. The column displays as Mapped and Mapped to: Lead Quality.

You can repeat these steps to create simple attributes for mapping other columns of your data assets.

Example: Exclude column from mapping

Watch Video To preview this task, watch the video beginning at 05:47.

This example explains how to exclude a column from the data asset mapping. You can exclude columns from the mapping if they are not useful to IBM Match 360 during the matching process or if you do not want to include them in your matched data output.

  1. From the Asset list, select Customers.csv and click the column that is named STATE_CODE.
  2. Click the checkbox Exclude this column from mapping.
  3. Click Map and Save data model to map the column to the attribute. The column displays as Excluded.

You can repeat these steps to exclude other columns of your data assets.

Table 1. Campaign Prospects.csv suggested mapping

Column Target Method
Source Record source Map an existing attribute
ID Record identifier Map an existing attribute
birth_date.value Birth date Map an existing attribute
gender.value Gender Map an existing attribute
legal_name.full_name Legal name - Full name Map an existing attribute
mobile_telephone.phone_number Home telephone - Phone number Map an existing attribute
personal_email.email_id Personal email - Email address Map an existing attribute
Lead Quality Lead Quality Create a simple attribute
Product Interest Product Interest Create a simple attribute


Table 2. Customers.csv suggested mapping

Column Target Method
Customer Number Record Identifier Map an existing attribute
NAME Legal name - Full name Map an existing attribute
COUNTRY Primary residence - Country value] Map an existing attribute
LATITUDE Primary residence - Latitude degrees Map an existing attribute
LONGITUDE Primary residence - Longitude degrees Map an existing attribute
STREET_ADDRESS Primary residence - Address line 1 Map an existing attribute
CITY Primary residence - City Map an existing attribute
STATE Primary residence - State/Province value Map an existing attribute
STATE_CODE None Exclude column from mapping
ZIP_CODE Primary residence - Postal code Map an existing attribute
EMAIL_ADDRESS Personal email - Email address Map an existing attribute
PHONE_NUMBER Home telephone - Phone number Map an existing attribute
GENDER Gender Map an existing attribute
CREDITCARD_NUMBER None Exclude column from mapping
CREDITCARD_TYPE None Exclude column from mapping
CREDITCARD_EXP None Exclude column from mapping
CREDITCARD_CVV None Exclude column from mapping
EDUCATION None Exclude column from mapping
EMPLOYMENT_STATUS None Exclude column from mapping
INCOME None Exclude column from mapping
MARITAL_STATUS Marital Status Create a simple attribute
CUSTOMER_LIFETIME_VALUE Customer Lifetime Value Create a simple attribute
Product Line None Exclude column from mapping


Table 3. Experiancc.csv suggested mapping

Column Target Method
source Record source Map an existing attribute
Experian_ID Record identifier Map an existing attribute
birth_date.value Birth date Map an existing attribute
drivers_licence.identification_number None Exclude column from mapping
gender.value Gender Map an existing attribute
home_telephone.phone_number Home telephone - Phone number Map an existing attribute
legal_name.given_name Legal name - Given name Map an existing attribute
legal_name.last_name Legal name - Last name Map an existing attribute
mobile_telephone.phone_number Mobile telephone - Phone number Map an existing attribute
passport.identification_number None Exclude column from mapping
personal_email.email_id Personal email - Email address Map an existing attribute
primary_residence.address_line1 Primary residence - Address line 1 Map an existing attribute
primary_residence.address_line2 Primary residence - Address line 2 Map an existing attribute
primary_residence.city Primary residence - City Map an existing attribute
primary_residence.province_state Primary residence - State/Province value Map an existing attribute
primary_residence.zip_postal_code Primary residence - Postal code Map an existing attribute
Credit score Credit Score Create a simple attribute
Wealth_decile None Exclude column from mapping
CREDITCARD_NUMBER None Exclude column from mapping
CREDITCARD_TYPE None Exclude column from mapping


Checkpoint Check your progress

The following image shows all of the mapped data assets. Now that you mapped the attributes for all three data assets, you can publish the data model and run matching.

Master data with all assets mapped

Task 4: Publish the data model and run matching

Watch Video To preview this task, watch the video beginning at 06:50.

The data model is created after you map all of the columns from your data assets to attributes. Your published data model is used by IBM Match 360 to resolve single entities from all of your data sources. Follow these steps to publish the data model.

  1. When you map the last column of your last data set, click Publish model. This option displays after you finish mapping all of the columns in your three data assets. You receive a notification when your data model is successfully published.
  2. Click the Publish all data icon, then click Publish data to load the mapped data assets into the IBM Match 360 data model based on the mapping. The statuses of the assets change from Loading-in-progress to Loaded-into-Service.

Checkpoint Check your progress

The following image shows the data assets listed as loaded into service indicating that the data model was published successfully. Next, you can run matching.

Published data model

Complete matching setup to run matching

Watch Video To preview this task, watch the video beginning at 07:26.

IBM Match 360 uses your published data model to consolidate all of the records of your data sources into single entities to create a data asset with more complete records. Follow these steps to run matching:

  1. Click the Data setup drop-down, and select Matching setup from the menu.
  2. Select the Attribute selection tab. You can select which attributes that are used for matching. Choose attributes that can help distinguish records from each other like birth dates, email addresses, or phone numbers. For this tutorial, you can accept the default attributes that are already selected.
  3. Select the Match results tab, and click Run matching. You receive a notification when the matching process is complete and the matching results are displayed.

Checkpoint Check your progress

The following image shows the results after you ran matching. Now that you published the data model and ran matching, you are ready to published the matched data to a catalog.

Match results

Task 5: Publish the matched data to a catalog

Watch Video To preview this task, watch the video beginning at 07:51.

Create a connection asset for IBM Match 360

To access the matched data in a project, you need to create a connection asset to IBM Match 360. The IBM Match 360 connection asset connects data that is matched with the IBM Match 360 service to a connected data asset. Follow these steps to create the connection asset.

  1. From the Cloud Pak for Data navigation menu Navigation menu, choose Projects > View all projects.
  2. Select your Customer 360 sample project.
  3. Select the Assets tab, and click New asset.
  4. Select Connection, and select the Match 360 connection type.
  5. Click Select to add a connection for an IBM Match 360 service instance.
  6. Type Customer 360 connection to name your connection asset.
  7. Retrieve the CRN of your IBM Match 360 with Watson service instance:
    1. From the IBM Cloud console resource list page, click Services and software to expand the list of your service instances.
    2. In the Product column, click IBM Match 360 with Watson.
    3. In the details panel that opens, click the Copy to clipboard icon for the CRN of your selected IBM Match 360 with Watson service.
  8. Complete the Connection details field with the CRN that corresponds with your IBM Match 360 with Watson service instance.
  9. Create an IBM Match 360 API key:
    1. From the IBM Cloud console, click Manage > Access (IAM).
    2. Click the API keys page.
    3. Click Create an IBM Cloud API key.
    4. Type a name and description.
    5. Click Create.
    6. Copy the API key.
    7. Download the API key for future use.
  10. Complete the Credentials field with the API key that you created.
  11. Click Create.

Checkpoint Check your progress

The following image shows the IBM Match 360 connection asset. Now you can created a connected data asset from this connection.

Connection asset

Create a connected data asset

Watch Video To preview this task, watch the video beginning at 09:40.

Now use the IBM Match 360 connection to create a new connected data asset of your consolidated data from IBM Match 360. Follow these steps to create a connected data asset.

  1. Click New asset.
  2. Select Connected data.
  3. Click Select source.
  4. Click Match 360 connection > person > person_entity.
  5. Click Select.
  6. Type Golden Bank 360 View to name your connected data asset.
  7. Click Create.

Checkpoint Check your progress

The following image shows the connected data asset. Now that you created the connected data asset for your consolidated, matched data, you can publish that asset to a catalog.

Connected data asset

Publish the connected data asset to your catalog

Watch Video To preview this task, watch the video beginning at 10:13.

In Task 1, you created a catalog. Follow these steps to publish the consolidated, matched data to that catalog.

  1. Click the open and close list of options icon of your connected data asset that is named Golden Bank 360 View, and select Publish to catalog.
  2. Click Publish to use the default values and publish your connected data asset to your catalog.

Checkpoint Check your progress

The following image shows the data asset in the catalog.

Asset in catalog

As a data engineer for Golden Bank, you successfully used IBM Match 360 to set up, map, and model your data for a 360-degree view of the customer. You then published the complete 360-degree view of your matched data to your catalog for others in your organization to access.

Next steps

Now that you finished matching, you can now explore your matched data with the master data explorer. Then you can tune the matching algorithm to see how it affects the matching results. Continue to the Explore your customers tutorial to learn how IBM Match 360 resolved entities and provides a complete 360-degree view of Golden Bank's customers.

Learn more

Parent topic: Data fabric tutorials