Problem
A database is only useful when its structure reflects the business accurately. Poor entity boundaries, duplicated data or weak integrity rules create reporting and operational problems later.
Interactive visual stories
See the thinking behind the data
Visual concepts covering data modelling, business rules and checking relationships. Illustrative examples, not a reproduction of assessed work.
Concept visuals · no client screenshots
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My role
I worked through conceptual modelling, normalisation, relational design and SQL implementation with an emphasis on connecting database decisions to the business use case.
What I worked on
Model the domain
Identify entities, keys, relationships and cardinality from business requirements before writing queries.
Protect integrity
Use normalisation and relational constraints to reduce duplication and keep stored data consistent.
Make data usable
Write SQL that retrieves and combines data in forms that support operational questions and reporting.
Proof of work
ERD thinkingEntity relationships and identifiers are designed before implementation, rather than treating tables as isolated spreadsheets.
NormalisationStructures are reviewed for duplicated or dependent data and decomposed where needed.
SQL implementationOracle SQL is used to create, populate and query relational structures.
Business connectionSchema decisions are explained in terms of business rules, not only database syntax.
Tools & capabilities
Oracle SQLSQLERDRelational ModellingNormalisationPrimary / Foreign KeysData IntegrityQuery Design
What this demonstrates
This work supports my analyst profile because it helps me discuss data structures with technical teams while still reasoning from business entities, rules and reporting needs.
The ERD visual used on the portfolio is a representative visualisation of relational-design capability, not a copy of assessed university schema. I avoid publishing assessed material as if it were a public production project.
Next step