Using DataFlux® Data Management Studio
DQFT : DQFT29
This course introduces DataFlux Data Management Studio and includes topics for data profiling, data jobs to perform data management tasks (such as data quality and entity resolution), data monitoring, usage of DataFlux Expression Engine Language, macro variables, and process jobs.
Learn How To
- Understand data explorations.
- Create and review data profiles.
- Create data jobs to improve data quality.
- Create data jobs to perform entity resolution.
- Establish monitoring aspects for your data.
- Work with the DataFlux Expression Engine Language.
- Define and use macro variables.
- Create process jobs.
Prerequisites
There are no prerequisites for this course.
SAS Products Covered
DataFlux Data Management Server;DataFlux Data Management Studio
Course Outline
Architecture and Methodology
- Introduction to DataFlux Data Management offerings and architecture.
- Methodology and course flow.
- Navigating the Data Management Studio Interface.
- Verifying quality knowledge base and reference sources.
- Working with data connections.
- Creating a DataFlux repository.
- Creating and exploring data profiles.
- Profiling a subset of data.
- Profiling data in text files.
- Setting DataFlux Data Management Studio options.
- Creating, documenting, and running a simple data job.
- 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.
- Creating match codes.
- Clustering records.
- Adding survivorship to the entity resolution job.
- Adding field-level rules for the surviving record.
- Defining business rules.
- Data profiling with business rules and alerts.
- Working with data jobs and business rules.
- Creating and executing a task.
- Introduction and overview of DataFlux Expression Engine Language (EEL).
- Creating dynamic fields for a profile using EEL.
- Working with the Expression node.
- Reviewing the IF/ELSE statement.
- Reviewing return status.
- Creating a macro file.
- Using macros in a data profile.
- Using macros in a data job.
- Introduction to process jobs.
- Examining source bindings in a simple process job.
- Working with conditional processing.
- Working with work tables and events.
- 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.
Live Class Schedule
Duration: 28 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.