Design data models that meet the business requirements and align to the agreed architecture framework.
Ensure data modelling deliverables are delivered according to project plan and budget to meet commitment to stakeholders.
Ensure all data modelling activities and deliverables are aligned to the development methodology and to the data modelling principles and standards
Apply the approved tooling to create the data modelling deliverables.
Adopt the Enterprise Data Model (which is based on the IFW) as a standard for data model designs to leverage best practice and fast track data modelling efforts.
Translate business requirements into data requirements.
Analyse and profile the source data to understand data quality issues, relationships patterns and rules in the data.
Structure data requirements into logical data constructs based on the Enterprise Data Model, including ERD models, dimensional models to ensure optimal implementation.
Compile Source to Target Mapping Specifications
Ensure complete and correct data by identifying definitive or authoritative source of data; analysing source data; and identifying gaps
Enable physical implementation of the data structure by generating the first cut physical data model from the logical data model.
Facilitate dataflow understanding by collating dataflow diagrams outlining the flow of data across systems and interfaces.
Reduce non-value adding work by identifying opportunity for re-use of the Enterprise Data Model
Maintain up to date knowledge of latest developments in the Data Modelling domain, including reading; continuous professional development courses; seminars and conferences.
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