Course structure
Architecture and Methodology
- Introduction to DataFlux Data Management offerings and architecture.
- Methodology and course flow.
DataFlux Data Management Studio: Getting Started
- Navigating the Data Management Studio Interface.
- Verifying quality knowledge base and reference sources.
- Working with data connections.
- Creating a DataFlux repository.
PLAN
- Creating and exploring data profiles.
- Profiling a subset of data.
- Profiling data in text files.
ACT: Introduction to Data Jobs
- Setting DataFlux Data Management Studio options.
- Creating, documenting, and running a simple data job.
ACT: Quality
- Performing a simple exploration of the QKB.
- Investigating standardization using standardization definitions and standardization schemes.
- Working with a Field Layout node.
- Working with parsing and casing.
- Investigating right fielding and identification analysis.
ACT: Entity Resolution
- Creating match codes.
- Clustering records.
- Adding survivorship to the entity resolution job.
- Adding field-level rules for the surviving record.
MONITOR
- Defining business rules.
- Data profiling with business rules and alerts.
- Working with data jobs and business rules.
- Creating and executing a task.
DataFlux Expression Engine Language
- Introduction and overview of DataFlux Expression Engine Language (EEL).
- Creating dynamic fields for a profile using EEL.
Expression Node in Data Jobs
- Working with the Expression node.
- Reviewing the IF/ELSE statement.
- Reviewing return status.
Parameterization with Macros
- Creating a macro file.
- Using macros in a data profile.
- Using macros in a data job.
Essentials of Process Jobs
- Introduction to process jobs.
- Examining source bindings in a simple process job.
Creating Advanced Process Jobs
- Working with conditional processing.
- Working with work tables and events.
Tips, Tricks, and Other Topics
- Examining how data is processed in a data job.
- Considering job optimization techniques.
- Exploring tips for building and testing jobs.
- Working with the Data Management Server.
- Examining steps for promotion to production.
