Course announcements

  • In Data Services-Data Quality Management, you will learn about cleansing and standardizing address data and non-address data such as names and phone numbers and matching and consolidating records. You will also learn how to parse data from unstructured text such as emails to provide useful and reportable data. As a business benefit, by being able to create efficient data quality projects, you can use the transformed data to help improve operational and supply chain efficiencies, enhance customer relationships, create new revenue opportunities, and optimize return on investment from enterprise applications.

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

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