"Status quo. Latin for the mess we're in."
Jeve Moorman

Reverse Data Engineering is a common sense but disciplined approach to developing models of existing systems that have poor or no documentation. This approach includes both documenting what is seen and discovering (and documenting) what is unseen.

IT professionals often reverse engineer existing systems so they can understand, enhance, rebuild, reuse and/or salvage portions of these systems. In addition, vendor software is often reverse engineered to determine how well it aligns with a company's business practices.

Course Outcomes:
Students of Advanced Strategies’ Reverse Data Engineering Course will return to work and be able to:

  1. Explain the concept of reverse engineering and the common motivation for performing reverse engineering.
  2. Plan a reverse engineering project.
  3. Conduct reverse engineering sessions.

Course Outline:
Fundamentals of Reverse Engineering
  • Motivation for Reverse Engineering
  • How Far to Reverse Engineer
  • Managing the Effort
  • Instruments and Tools
Metadata in Reverse Engineering
  • Importance of Managing Metadata
  • Determining What Metadata to Maintain
  • Use of a Metadata Repository
Getting Started in Reverse Engineering
  • Defining and Planning a Reverse Engineering Project
  • Key Resource Requirements
  • Planning a Session
  • Conducting a Session
Creating a Physical Model
  • Reverse Engineering Steps
  • Developing an Architectural Model
  • Engineering Design
  • Developing Data Models
Creating a Logical Model
  • Examining Physical Models
  • Performance Indicators
  • Normalization
  • When to Use Canonical Synthesis
  • Benefits of Automated Tools
  • Definition
  • Focus and Planning
  • Examining Resources
  • Selecting Increments
  • Exercises on Key Techniques

Who Should Attend:
This course is targeted for Data Modelers, Database Administrators, Systems and Business Analysts, and other individuals involved in reverse engineering 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 and Case Study

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