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LeapFrogBI generates packages which will create and maintain a data mart based on component definitions. These packages must be run in order of precedence. This course describes the load precedence solution and demonstrates implementation.
After creating components, it is time to build and deploy. Configuration builds, component builds, and build archives are defined and initiated. Lifecycle migration along with a sample migration pattern is introduced.
Fact tables contain numeric measures and pointers to related dimensions. Fact components provide a simple interface for common tasks such as setting up dimension relationships, selecting degenerate dimensions, and creating calculations.
The attributes which describe related fact records are stored in dimension tables. It is the role of the dimension component to make creating and loading dimensions a very simple task. Set the dimension keys and selecting history tracking methods are a couple of common dimension tasks.
Pivot, unpivot, filter, union, join, aggregate, etc… can all be done in transformation components. Dealing with data quality issues and structuring source records in a way that is appropriate for target dimensions & facts is the role of transform components.
A resilient data mart should include a consolidated view of all source system records collected. This is the role of the persistent stage area (PSA) component. PSA provides a dependable source for all downstream components designed to support agile development processes.
Are you ready to start collecting data? Stage components move data from a source system to controlled destination. In this course you will learn how to create a source system profile and incrementally extract source records using stage components.
Connection components define connection details for each project lifecycle. All other components reference connection components to define their source and destination. LeapFrogBI manages the creation of all required objects based on these definitions.
After collecting requirements and creating a target data model, it is time to create a source to target map known as an ETL Data Flow Diagram (DFD). This course both describes the role of a DFD and demonstrates the creation of a simple DFD.
Defining a desired data mart structure prior to beginning development is key to success. Data models are the blueprint of data mart development. This course demonstrates the creation of a simple data model while describing the role it serves.
New to LeapFrogBI? This is a great place to start. This course provides a high level development workflow overview. The concepts covered provide a foundation for all development tasks.