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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.

Quick start: If you did not already create the sample project for this tutorial, access the Customer 360 sample project in the gallery.

The following animated image provides a quick preview of what you’ll accomplish by the end of the Customer 360 use case tutorials. 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, and then explore and visualize the matched data. Click the image to view a larger image.

Animated image

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.

Tech preview This is a technology preview and is not yet supported for use in production environments.

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 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.

Tip: Start the video, then as you scroll through the tutorial, the video moves to picture-in-picture mode. Close the video table of contents for the best experience with picture-in-picture. You can use picture-in-picture mode so you can follow the video as you complete the tasks in this tutorial. Click the timestamps for each task to follow along.

Video timestamps


  • Watch this short video to see how to use the video picture-in-picture and table of contents.

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 an existing Cloud Pak for Data as a Service account, then you can get started with this tutorial. If you have a Lite plan account, only one user per account can run this tutorial.
  • If you don't have a Cloud Pak for Data as a Service account yet, then sign up for a data fabric trial.

Verify the necessary provisioned services

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, verify that you are in the Dallas region. If not, click the region drop down, 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.

    1. Select IBM Match 360 with Watson.

    2. For the region, select Dallas.

    3. Select the Lite plan.

    4. Optional: Type a name for your IBM Match 360 with Watson service instance.

    5. Click Create.

  5. Repeat these steps to verify or provision the following services:

    • Watson Knowledge Catalog
    • Cloud Object Storage

Checkpoint for Provisioned services Check your progress

The following image shows the provisioned service instances:

Provisioned services

Create the sample project

To preview this task, watch the video beginning at 01:29.

Follow these steps to create the sample project for this tutorial:

  1. Access the Customer 360 sample project in the gallery.

  2. Click Create project.

  3. If prompted to associate the project to a Cloud Object Storage instance, select a Cloud Object Storage instance from the list.

  4. Click Create.

  5. Wait for the project import to complete, and then click View new project to verify that the project and assets were created successfully.

    Note: If this occasion is your first time accessing a project, you see a guided tour asking if you want a tour of projects. For now, click Maybe later.
  6. Click the Assets tab to view the project's assets.

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.

Checkpoint for Sample project 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 user interface, close the window.

Task 1: Create a catalog

To preview this task, watch the video beginning at 02:12.

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 verify that you are an editor of the catalog that you wish to use.

  1. From the Cloud Pak for Data navigation menu Navigation menu, choose Catalogs > View all catalogs

  2. Open the catalog that you wish to use for this tutorial.

  3. Click the Access control tab.

  4. Verify that your account has the Editor role. If your access is Viewer, then contact your administrator to request Editor access.

Otherwise, follow these steps to create the Customer 360 catalog:

  1. On the Catalogs page, click Create Catalog.

  2. For the Name, copy and paste the catalog name exactly as shown with no leading or trailing spaces:

    Customer 360 Catalog
    
  3. Select Enforce data protection rules, confirm the selection, and accept the defaults for the other fields.

  4. Click Create to use the default settings. Your new catalog opens.

Checkpoint for Catalog 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.

Catalog

Task 2: Set up and add assets to master data

To preview this task, watch the video beginning at 02:46.

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 while completing this tutorial in the Cloud Pak for Data user interface, close the window.
  2. If you need to set up master data, click Set up master data and follow the steps to associate the required project and services with master data. Otherwise, click Go to configuration and continue to the next step.1. Select your Cloud Object Storage service, then click Next.

    1. Select your Customer 360 project, then click Next.

    2. Select your existing catalog named Customer 360 Catalog, then click Finish.

    3. Click Continue with configuration to complete the setup.

  3. Click Start with data assets.

  4. Click Add data.

  5. Insert all three of the data assets in the project:

    1. Click the Find and add data Find and add data icon to open the Data assets panel if it is hidden.

    2. Select the Project tab.

    3. Hover over each file in the project and click the Insert Insert icon of Campaign Prospects.csv, Customers.csv, and Experiancc.csv.

  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 the checkbox of the Campaign Prospects.csv, Customers.csv, and Experiancc.csv assets and click Set asset properties.

    2. For each asset, click the Select data asset type drop-down menu, and select the Person data asset type.

    3. Click Save.

Checkpoint for Assets added to master data 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

To preview this task, watch the video beginning at 03:56.

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 begin mapping the columns of your data assets to the appropriate attributes.

  2. In the Asset list panel, select Campaign Prospects.csv.

  3. If you need to profile your data, click Profile and when prompted, click Start profiling. Profiling your data is a prerequisite to automatically mapping columns of your data to attributes of the IBM Match 360 data model. Profiling takes 2-5 minutes. A message that says Profiling is complete displays when your data is finished being profiled.

  4. When profiling is complete, you can automatically map columns of your data by clicking Yes, automap in the prompt or Automap from the mapping menu of your asset.

  5. Refer to Table 1: Campaign Prospects.csv mapping to manually map all of the columns that have the status Not mapped or not mapped correctly according to Table 1: Campaign Prospects.csv mapping. To map a column to an attribute, you can follow the example: map an existing attribute. To exclude a column, you can follow the example: exclude columns from mapping.

  6. Ensure that all of the columns in your asset have a status of either Mapped, Automapped, or Excluded, and click Map and save to data model. Otherwise, repeat Task 3, step 5.

  7. Repeat Task 3 for your Customers.csv and Experiancc.csv assets. Use the respective tables to map the columns for your 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 or exclude a column from mapping.

Example 1: Map an existing attribute

To preview this task, watch the video beginning at 04:35.

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. Click the column legal_name.full_name.

  2. From the Mapping targets panel, in the search field, type Legal name - Full name.

  3. Click Map and Save to data model to map the column to the attribute. The column displays as Mapped and Mapped to: Legal name - Full name.

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 2: Exclude columns from mapping

To preview this task, watch the video beginning at 05:58.

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. Click the column that is named Source.

  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 Exclude this column from mapping Exclude column from mapping
ID Exclude this column from mapping Exclude column from mapping
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 Mobile telephone - Phone number Map an existing attribute
personal_email.email_id Personal email - Email address Map an existing attribute
Lead Quality Exclude this column from mapping Exclude column from mapping
Product Interest Exclude this column from mapping Exclude column from mapping


Table 2. Customers.csv suggested mapping

Column Target Method
Customer Number Exclude this column from mapping Exclude column from mapping
NAME Legal name - Full name Map an existing attribute
COUNTRY Exclude this column from mapping Exclude column from mapping
LATITUDE Exclude this column from mapping Exclude column from mapping
LONGITUDE Exclude this column from mapping Exclude column from mapping
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 Exclude this column from mapping 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 Exclude this column from mapping Exclude column from mapping
CREDITCARD_TYPE Exclude this column from mapping Exclude column from mapping
CREDITCARD_EXP Exclude this column from mapping Exclude column from mapping
CREDITCARD_CVV Exclude this column from mapping Exclude column from mapping
EDUCATION Exclude this column from mapping Exclude column from mapping
EMPLOYMENT_STATUS Exclude this column from mapping Exclude column from mapping
INCOME Exclude this column from mapping Exclude column from mapping
MARITAL_STATUS Exclude this column from mapping Exclude column from mapping
CUSTOMER_LIFETIME_VALUE Exclude this column from mapping Exclude column from mapping
Product Line Exclude this column from mapping Exclude column from mapping


Table 3. Experiancc.csv suggested mapping

Column Target Method
source Exclude this column from mapping Exclude column from mapping
Experian_ID Exclude this column from mapping Map an existing attribute
birth_date.value Birth date Map an existing attribute
drivers_licence.identification_number Exclude this column from mapping 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 Exclude this column from mapping 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 Exclude this column from mapping Exclude column from mapping
primary_residence.zip_postal_code Primary residence - Postal code Map an existing attribute
Credit score Exclude this column from mapping Exclude column from mapping
Wealth_decile Exclude this column from mapping Exclude column from mapping
CREDITCARD_NUMBER Exclude this column from mapping Exclude column from mapping
CREDITCARD_TYPE Exclude this column from mapping Exclude column from mapping


Checkpoint for Master data with all assets mapped 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

To preview this task, watch the video beginning at 06:37.

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. After you map the last column of your last data set, you can either click Publish model in the window that displays or the Publish model icon. This option displays after you finish mapping all of the columns in your three data assets. Publishing your model takes up to 1 minute. 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. The data takes 5-10 minutes to load into service.

Checkpoint for Published data model 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 and run matching

To preview this task, watch the video beginning at 07:11.

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. For this tutorial, you can accept the default attributes that are already selected. Here you can choose attributes that can help distinguish records from each other like birth dates, email addresses, or phone numbers to help the matching algorithm.

  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 for Match results 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 publish the matched data to a catalog.

Match results

Task 5: Publish the matched data to a catalog

To preview this task, watch the video beginning at 07:50.

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. Choose your Customer 360 sample project.

  3. Select the Assets tab, and click New asset.

  4. In the Data access tools section, select Connection, and select the IBM Match 360 connection type.

  5. Click Select to add a connection for an IBM Match 360 service instance.

  6. Type the connection asset name, Customer 360 Connection.

  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. In the Connection details, paste 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.

  12. If asked to confirm you want to create the connection without setting location and sovereignty, click Create.

Checkpoint for Connection asset Check your progress

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

Connection asset

Import connected data asset

To preview this task, watch the video beginning at 9:39.

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 Import asset.

  2. On the Import asset page, select Connected data.

  3. Select Customer 360 connection > person > person_entity.

  4. Click Select.

  5. Type the name for your connected data asset, Golden Bank 360 View.

  6. Click Import.

Checkpoint for Connected data asset 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

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

Follow these steps to publish the consolidated, matched data to that catalog.

  1. In your Customer 360 project, verify that you are on the Assets tab.

  2. Click the open and close list of options icon for your connected data asset Golden Bank 360 View, and choose Publish to catalog.

  3. Select the catalog you wish to use from the list.

  4. Click Publish to use the default values and publish your connected data asset to your catalog.

  5. To view the asset in the catalog, from the Cloud Pak for Data navigation menu Navigation menu, choose Catalogs > View all catalogs.

  6. Click the Golden Bank 360 View asset.

  7. Click the Asset tab to preview the data.

Checkpoint for Asset in catalog 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