使用数据质量服务(DQS)清理数据

Data Cleansing with Data Quality Services (DQS)

A straightforward, no-nonsense approach to improving your data cleansing skills with SQL Server Data Quality Services (DQS).

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微软
edX
  • 完成时间大约为 4
  • 中级
  • 英语
注:因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

The discipline of Data Quality Assurance

SQL Server DQS capabilities and features

Creating DQS solutions

The SSIS DQS Cleansing component

Matching Policies and Projects

Administering DQS

课程概况

Is your data messy? Do you need to learn how to clean it up? In this computer science course, we will discuss the discipline of Data Quality Assurance and Data Quality Services (DQS). You will learn why your data needs cleansing, the capabilities and features of DQS, what a DQS solution looks likes and how data cleansing integrates with an Integration Services (SSIS) data flow. We will demonstrate a variety of critical data quality activities such as knowledge discovery, domain management, matching policies for the de-duplication of data, and administration topics covering installation, configuration and security.

课程大纲

Module 1

Introducing DQS
Discipline of Data Quality Assurance
SQL Server DQS, overview of capabilities and features; concepts; support by SQL Server version and edition
Installation and setup
Creating DQS Solutions
Knowledge bases; Domains; Composite domains; DQ Projects
Exploring an existing solution

Module 2

Cleansing Data with DQS
Rules; Values
Creating a knowledge base to cleanse data in a DQ Project
Cleansing Data with DQS in SSIS
SSIS DQS Cleansing component
Integrating cleansing in SSIS data flow
Creating knowledge base, cleanse data in a DQ Project and SSIS data flow

Module 3

Matching Data with DQS
Matching policies; Matching projects
Creating a matching policy, and de-duplicating data in a DQ project
De-duplicating data in a DQ Project 
Administering DQS
Installation; Configuration; Security
Install, configure and secure a DQS instance

Module 4

Final Assessment

预备知识

A basic understanding of the Business Intelligence process.
A basic understanding of database design and storage.

Suggested prerequisites / Supporting Material:

Delivering a Relational Data Warehouse
Implementing ETL with SQL Server Integration Services (SSIS)

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