Example Scenario

This getting-started guide describes how to complete end-to-end data operations on DataArts Studio.

In this case, MRS Hive is used as the data lake foundation, and DataArts Studio is used for end-to-end governance of taxi trip data of a city. The following objectives are expected to be achieved through data governance:

Standardized data and models
Unified statistics standards and high-quality data reports
Data quality monitoring and alarm
Daily revenue statistics
Monthly revenue statistics
Statistics on the revenue proportion of each payment type

Process Overview

You can govern data in the example scenario based on the process in Table 1.

**Table 1** Process of data governance using DataArts Studio
Process	Description	Subtask	Operation
Step 1: Design a Process	Before using DataArts Studio, conduct a service survey and requirement analysis.	Requirement analysis, service survey, and process design	Requirement Analysis Service Survey
Step 2: Prepare Data	If you are new to DataArts Studio, create a DataArts Studio instance and a workspace.	Preparations before using DataArts Studio	Preparations
Step 3: DataArts Migration	Use DataArts Studio to upload data from data sources to the cloud. You can migrate offline or historical data. DataArts Migration can migrate a single table, file, entire database, and incremental data. You can use it to migrate data between homogeneous and heterogeneous data sources such as on-premises and cloud-based file systems, relational databases, data warehouses, NoSQL databases, big data services, and object storage.	Data integration	Creating a Cluster Creating Source and Destination Links for Data Migration Creating a Table/File Migration Job
Step 4: Metadata Collection	Collect metadata of raw data for data management and monitoring.	Metadata collection	Collecting and Monitoring Metadata
Step 5: Design Data Architecture	Use DataArts Architecture to create entity-relationship (ER) models and dimensional models to standardize and visualize data development and output data governance methods that can guide development personnel to work with ease.	Preparations	Adding Reviewers Configuration Center Management
		Subject design	Designing a Subject
		Standard management	Creating and Publishing Lookup Tables Creating and Publishing Data Standards
		ER modeling	Data Warehouse Planning: Creating Two ER Models for the SDI and DWI Layers
		Dimensional modeling	Creating and Publishing Dimensions for the DWR Layer Creating and Publishing a Fact Table for the DWR Layer
		Metric design	Creating and Publishing Technical Metrics
		Data mart building	Data Mart: Creating and Publishing Summary Tables for the DM Layer
Step 6: Develop Data	Use DataArts Factory to manage diverse big data services. DataArts Studio enables a variety of operations such as data management, script development, job development, job scheduling, O&M, and monitoring, facilitating data analysis and processing.	Data management	Managing data
		Script development	Developing a Script
		Job development.	Developing a Batch Job
		O&M scheduling	O&M Scheduling
Step 7: DataArts Quality	Use DataArts Quality to monitor metrics. You can filter out unqualified data in a single column or across columns, rows, and tables from the following perspectives: integrity, validity, timeliness, consistency, accuracy, and uniqueness. DataArts Studio uses automatically generated quality rules to standardize data, and supports periodic monitoring.	Metric monitoring	Monitoring Business Metrics
Step 7: DataArts Quality		Data quality control	Viewing Quality Jobs
Step 8: View Data Assets	In the DataArts Catalog module, you can view data maps.	Data maps	Viewing Logical Assets and Technical Assets
Step 9: Unsubscribe from Services	Unsubscribe from the service to avoid unnecessary billing.	Unsubscribing from the service	(Optional) Unsubscribing from the Service