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Using DataFlux(R) Data Management Studio

EDU Trainings s.r.o.

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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.

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Architecture and MethodologyIntroduction to DataFlux Data Management offerings and architecture.Methodology and course flow.DataFlux Data Management Studio: Getting StartedNavigating the Data Management Studio Interface.Verifying quality knowledge base and reference sources.Working with data connections.Creating a DataFlux repository.PLANCreating and exploring data profiles.Profiling a subset of data.Profiling data in text files.ACT: Introduction to Data JobsSetting DataFlux Data Management Studio options.Creating, documenting, and running a simple data job.ACT: QualityPerforming 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 ResolutionCreating match codes.Clustering records.Adding survivorship to the entity resolution job.Adding field-level rules for the surviving record.MONITORDefining business rules.Data profiling with business rules and alerts.Working with data jobs and business rules.Creating and executing a task.DataFlux Expression Engine LanguageIntroduction and overview of DataFlux Expression Engine Language (EEL).Creating dynamic fields for a profile using EEL.Expression Node in Data JobsWorking with the Expression node.Reviewing the IF/ELSE statement.Reviewing return status.Parameterization with MacrosCreating a macro file.Using macros in a data profile.Using macros in a data job.Essentials of Process JobsIntroduction to process jobs.Examining source bindings in a simple process job.Creating Advanced Process JobsWorking with conditional processing.Working with work tables and events.Tips, Tricks, and Other TopicsExamining 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.
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