DS30
Data Services – Data Quality Mangement
- Solution:SAP BusinessObjects
Level:Basic Processes & Foundation
Languages:English
Goals
- Use Address Cleanse Transforms to parse, standardize, cleanse and enhance address records
- Use Data Cleanse Transforms to parse, standardize, cleanse and enhance data records
- Use the Match Transform to match and consolidate data records
- Use the Text Data Processing Entity Extraction Transform to parse unstructured data for analysis and reporting
Audience
- Application Consultant
- Business Analyst
- Data Consultant / Manager
- User
Prerequisites
Essential
- DS10Data Services
Course based on software release
- SAP Data Services 4.2
Content
- Overview: Data Services Data Quality Management
- Define Data Quality Management
- Data Quality Transforms
- Defining Data Quality Processes
- Use Addresss Cleanse Transforms
- Preparing Data for Address Cleanse
- Using Address Cleanse Transforms
- Data Cleanse Transforms
- Parsing for Data Cleanse
- Using Data Cleanse Transforms
- Match and Consolidate Data
- Determining the Need for Record Deduplication
- Using the Match Wizard
- Configuring the Match Transform
- Performing Post-Match Processing
- Consolidating Matching Records
- Using Advanced Match Strategies
- Text Data Processing
- Using Text Data Processing