Updated on 2023-03-03 GMT+08:00

Example Scenario

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

It uses taxi trip data of a city as an example to demonstrate how to use DataArts Studio to govern data in an MRS Hive data lake, mask standard data using DataArts Security, and open data using DataArts DataService. 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





Step 1: Process Design

Before using DataArts Studio, conduct a service survey and requirement analysis.

Requirement analysis, service survey, and process design

Requirement Analysis

Service Survey

Process Design

Step 2: Preparations

If you are new to DataArts Studio, create a DataArts Studio instance and a workspace.

Preparations before using DataArts Studio


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: DataArts 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.


Adding Reviewers

Configuration Center Management

Subject design

Designing a Subject

Standard management

Creating and Publishing Lookup Tables

Creating and Publishing Data Standards

ER modeling

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

Creating and Publish Summary Tables for the DM Layer

Step 6: DataArts Factory

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

Data quality control

Viewing Quality Jobs

Step 8: DataArts Catalog

In the DataArts Catalog module, you can view data maps.

Data maps

Viewing Logical Assets and Technical Assets

(Optional) Step 11: Unsubscribing from a Service

Unsubscribe from the service to avoid unnecessary billing.

Unsubscribing from the service

(Optional) Unsubscribing from the Service