The customer user journey involves multiple processes in the Data Integrity Suite from establishing a new Datasource to Data Governance that ensures data assets stay in compliance with corporate policies and government regulations.
Follow these steps for the successful end-to-end implementation of
the customer user journey:
- Establish a new datasource.
- Initiate discovery and configure the schedule that determines how frequently the data should be updated. Turn on both the Schedule Discovery toggle to enable recurring discovery and the Start discovery now toggle to trigger an immediate discovery.
- Evaluate rules and generate data quality scores.
- View profiles.
- Configure quality pipelines to enhance the data quality.
- Configure Governance requirements.
List of videos
The table below provides details of all the videos related to the implementation of the customer user journey.
| Videos | Description |
|---|---|
| Create a Databricks connection | Get familiar with the process of seamlessly adding a new Databricks connection. Discover the steps taken to integrate, connect, and catalog with Databricks. |
| Create and manage datasources | Get familiar with the process of establishing data connections and manage datasources. This video demonstrates how to seamlessly add new connections and initiate cataloging by providing key details such as account information, user credentials, roles, warehouse, database, and schema. |
| Overview of rules and scoring | Get familiar with the functionalities of rules and scoring and how these can be used to assess the quality of your data. |
| Configure quality pipelines | Get familiar with the process of creating data quality pipelines to automate the movement and transformation of data. This video provides an overview of generating a data sample and the series of steps required to create a pipeline to transform the data and ensure accuracy, consistency, uniqueness, integrity, and validity. |
| Overview of Data Governance | Get familiar with how Governance uses a flexible meta model to adapt to how your business runs and communicate the trustworthiness of data to ensure outcomes are achieved and socialized across all users. |