The Infinitive Data Transformation Methodology (IDTM) is a step-by-step process for conducting a data transformation project. It was developed based on the many data transformation projects conducted by Infinitive over the years.
The benefits of using the proven Infinitive Data Transformation Methodology include:
- Structure and Organization: The ITDM project provides a structured framework for project execution, ensuring that tasks and activities are well-defined and organized.
- Risk Management: The ITDM emphasizes risk management throughout the project lifecycle. This encourages proactive identification, assessment, and mitigation of risks, enabling project teams to address potential issues early on.
- Quality Control: The Infinitive methodology emphasizes quality control by integrating quality management practices into the project workflow. It promotes the use of quality assurance techniques to ensure that project deliverables meet predefined standards and requirements.
- Collaboration and Communication: The ITDM emphasizes collaboration and effective communication among project stakeholders. It provides guidelines and tools for transparent and timely information sharing, enabling project teams to align their efforts, share progress updates, and resolve issues collaboratively.
The Infinitive Data Transformation Methodology is a detailed set of tasks that runs three layers deep. The highest level starts the work breakdown.
The top level, four pillars of the methodology are:
Strategic — Develops a data strategy that helps ensure the “to be” data architecture meets the strategic goals of the enterprise.
Foundational — Established the detailed data mapping and build the fundamental infrastructure needed for the “to be” data architecture.
Exploratory — Implements a series of high value use cases to prove the technical approach and business case ROI.
Advanced — Completes the data migration from the “as is” to the “to be” data architecture, establishes self-service analytics capabilities, finalizes governance, and creates a data-driven culture.
