A data bridge is a process that connects two or more stable, predefined data stores for a limited time or on an ongoing basis. Data bridges are used in a variety of applications such as:
- Converting data from an old system to a new system
- Interfacing data from one system to another
- Sourcing a data warehouse, etc.
This course explains the foundational concepts underlying a successful bridging project, describes the activities required for a successful data bridge, and covers the methodology needed to build a data bridge.
Course Outcomes:
Students of Advanced Strategies’ Data Bridging Course returning to work will be able to:
- Explain the concept of data bridging and the different classes of data bridges.
- Explain the different activities that are needed to bridge data.
- Apply a methodology to define, analyze, and design a data bridge in any application.
- Select an appropriate bridging paradigm for various source/target scenarios.
- Identify the appropriate use of utility software, custom software, and manual processes in building bridges.
Note: This course will not eliminate the hard, dirty work of bridging data, but it will provide a methodology to make it a manageable, predictable, and repeatable process.
Course Outline:
Introduction to Data Bridging
- What is Data Bridging?
- When is Data Bridging Used?
- Classes of Data Bridges
- How is Data Bridging Done?
- Who Does Data Bridging?
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Data Bridging Activities
- Sourcing
- Auditing
- Unloading
- Scrubbing
- Transforming
- Loading
- Logging and Validating
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Fundamental Methodology Concepts
- A Path to a Solution
- When are Data Bridges Built When Developing Systems
- The Data Bridging Methodology Framework
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Defining a Data Bridge
- Stakeholders
- Intentions
- Values
- Focus
- Context
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Data Bridging Paradigms
- Where to Start: Source or Target?
- Target Backward
- Source Forward
- Hybrids
- Cost/Benefits of Various Paradigms
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Analyzing a Data Bridge
- Discovering Candidate Target and Source Data
- Assessing Needs of Target and Source Data
- Assessing Data Bridging Options
- Specifying Data to Be Bridged and Bridging Rules
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Designing a Data Bridge
- Designing the Data Bridging Architecture
- Engineering the Data Bridge
- Completing the Design
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Realization Strategies
- Acquired Packages
- Custom Code
- Utilities / Tools
- Manual Processes
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Beyond Realization
- Implementation
- Support
- Maintenance
- Final Case Study
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Who Should Attend:
This course is targeted for Data Modelers, Database Administrators, Systems and Business Analysts, and other individuals involved in data bridging projects.
Non-Course Prerequisites:
Prior to the course, students should be able to read and be familiar with logical and physical data models.
Course Duration:
Three Days
Class Availability:
Request It Now!
Materials Provided:
Student Workbook, Case Study, and Bridging Checklists
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