Talend Data Quality Essentials

Talend Studio for Data Quality enables business users and data management teams to assess the quality of data in any data source. This product also lets you verify data completeness, accuracy, and integrity in preparation for data migration, instance consolidation, and data integration.

This course is designed to help you immediately utilize Talend Studio for Data Quality. You learn how to evaluate data quality according to a set of metrics and thresholds based on indicators, models, and rules for each data item to be analyzed or monitored.

Duration	2 days (14 hours)
Target audience	Anyone who wants to use Talend Studio for Data Quality to assess data quality
Prerequisites	Completion of Introduction to Talend Studio or Talend Data Integration Basics, as well as familiarity with SQL
Course objectives	After completing this course, you will be able to: Connect to a database and run an analysis on it Examine the contents of a connection to a data source Create, configure, and run a column analysis Generate regular expressions for pattern matching in an analysis to test data quality Define indicator thresholds that are flagged in analysis results when violated Create, configure, and run different types of table analysis Define a SQL business rule and set up an analysis to identify rows that conflict with your rule Create, configure, and run a table match analysis to search for duplicates Use advanced matching to enhance identification of duplicates Ensure data privacy by shuffling and masking customer data Display analysis reports in PDF files and on Data Quality Portal
Course agenda	Data quality in context Concepts Analysis summary Data quality analysis Creating a database connection Performing structural analyses Performing a basic column analysis Adding regular expressions Defining indicator thresholds Applying advanced statistics Generating Jobs from an analysis Using a column set analysis Using a business rule analysis Using redundancy analysis Advanced matching Getting ready for match analysis Reviewing the match analysis process Performing a match analysis Configuring additional settings for the table match analysis Using a matching integration Job Deduplicating addresses Data cleansing Cleansing email addresses Standardizing country codes Data privacy Shuffling data for privacy Masking data for privacy Masking data based on a pattern