Applied PostgreSQL is a structured, practical course covering PostgreSQL, JSONB, Triggers, Performance. It emphasizes explainable methods, checked work and a final outcome that can be reviewed.
DatabasesTool stack
PostgreSQL
Technology marks for Applied PostgreSQL, sourced from the CC0-licensed Simple Icons project.
Use PostgreSQL appropriately in a realistic, bounded task.
Use JSONB appropriately in a realistic, bounded task.
Use Triggers appropriately in a realistic, bounded task.
Use Performance appropriately in a realistic, bounded task.
Course outline and revision prompts
Module 1
PostgreSQL: Data modelling
Apply PostgreSQL through entities, relationships, constraints.
Lesson
Key terms
Revision question
Entities with PostgreSQL
entities, PostgreSQL, databases
In Applied PostgreSQL, which evidence best supports a entities result produced with PostgreSQL?
Relationships with JSONB
relationships, JSONB, databases
In Applied PostgreSQL, which evidence best supports a relationships result produced with JSONB?
Constraints with Triggers
constraints, Triggers, databases
In Applied PostgreSQL, which evidence best supports a constraints result produced with Triggers?
Instructional figureNested structure
Entities: from context to evidence
Entities connects business rule and records to a valid data state in Applied PostgreSQL.
1Business rule and records
Define the purpose, intended user and PostgreSQL constraints.
frames
2Entities
Derive entities from business rules and define stable identifiers.
produces evidence for
3Valid data state
Compare the observed result with a normal case, boundary case and stated limitation.
Takeaway: Entities is credible only when the result can be traced back to its purpose, inputs and constraints. Entities is the decision layer between the starting context and evidence that the result is fit for purpose.
Module 2
JSONB: Querying
Apply JSONB through selection, joins, aggregation.
Lesson
Key terms
Revision question
Selection with Performance
selection, Performance, databases
In Applied PostgreSQL, which evidence best supports a selection result produced with Performance?
Joins with PostgreSQL
joins, PostgreSQL, databases
In Applied PostgreSQL, which evidence best supports a joins result produced with PostgreSQL?
Aggregation with JSONB
aggregation, JSONB, databases
In Applied PostgreSQL, which evidence best supports a aggregation result produced with JSONB?
Instructional figureContinuous cycle
Selection: from context to evidence
Selection connects business rule and records to a valid data state in Applied PostgreSQL.
1Business rule and records
Define the purpose, intended user and Performance constraints.
frames
2Selection
Translate conditions into predicates and test boundaries.
produces evidence for
3Valid data state
Compare the observed result with a normal case, boundary case and stated limitation.
Review the evidence, adjust the method, and repeat.
Takeaway: Selection is credible only when the result can be traced back to its purpose, inputs and constraints. Selection is the decision layer between the starting context and evidence that the result is fit for purpose.
Module 3
Triggers: Reliability
Apply Triggers through transactions, indexes, backups.
Lesson
Key terms
Revision question
Transactions with Triggers
transactions, Triggers, databases
In Applied PostgreSQL, which evidence best supports a transactions result produced with Triggers?
Indexes with Performance
indexes, Performance, databases
In Applied PostgreSQL, which evidence best supports a indexes result produced with Performance?
Backups with PostgreSQL
backups, PostgreSQL, databases
In Applied PostgreSQL, which evidence best supports a backups result produced with PostgreSQL?
Instructional figureProcess flow
Transactions: from context to evidence
Transactions connects business rule and records to a valid data state in Applied PostgreSQL.
1Business rule and records
Define the purpose, intended user and Triggers constraints.
frames
2Transactions
Choose boundaries that preserve invariants under failure.
produces evidence for
3Valid data state
Compare the observed result with a normal case, boundary case and stated limitation.
Takeaway: Transactions is credible only when the result can be traced back to its purpose, inputs and constraints. Transactions is the decision layer between the starting context and evidence that the result is fit for purpose.
Module 4
Performance: Production design
Apply Performance through security, performance, operations.
Lesson
Key terms
Revision question
Security with JSONB
security, JSONB, databases
In Applied PostgreSQL, which evidence best supports a security result produced with JSONB?
Performance with Triggers
performance, Triggers, databases
In Applied PostgreSQL, which evidence best supports a performance result produced with Triggers?
Operations with Performance
operations, Performance, databases
In Applied PostgreSQL, which evidence best supports a operations result produced with Performance?
Instructional figureContinuous cycle
Security: from context to evidence
Security connects business rule and records to a valid data state in Applied PostgreSQL.
1Business rule and records
Define the purpose, intended user and JSONB constraints.
frames
2Security
Grant roles by task and test prohibited operations.
produces evidence for
3Valid data state
Compare the observed result with a normal case, boundary case and stated limitation.
Review the evidence, adjust the method, and repeat.
Takeaway: Security is credible only when the result can be traced back to its purpose, inputs and constraints. Security is the decision layer between the starting context and evidence that the result is fit for purpose.
Course practical outcome
Produce a reviewable Applied PostgreSQL project using PostgreSQL, JSONB, Triggers.
Expected output: A working Applied PostgreSQL artefact plus an evidence-based self-review.
Tools: A suitable PostgreSQL environment, A plain-text decision log, Test data or realistic sample material
Production steps
Define the intended user, outcome and constraints.
Create the smallest complete result using PostgreSQL.
Test one normal case, one boundary case and one failure response.
Revise the work from the evidence and preserve before-and-after results.
Prepare a concise handover containing method, limitations and next step.
Success criteria
The output matches the stated outcome.
Inputs and decisions are reproducible.
Boundary and failure evidence is included.
Limitations and responsibility considerations are explicit.
Self-review
Can another learner repeat the method?
Did I test a difficult case?
Did I avoid unsupported claims?
Is the next action proportionate to the remaining risk?
Next step: Choose one weakness found during review and improve it before extending the PostgreSQL scope.
Glossary
PostgreSQL
A core concept or tool used in Applied PostgreSQL; its exact meaning is established in the relevant lesson.
JSONB
A core concept or tool used in Applied PostgreSQL; its exact meaning is established in the relevant lesson.
Triggers
A core concept or tool used in Applied PostgreSQL; its exact meaning is established in the relevant lesson.
Performance
A core concept or tool used in Applied PostgreSQL; its exact meaning is established in the relevant lesson.
References
PostgreSQL Tutorial - PostgreSQL Global Development Group (accessed 2026-08-21)
SQL Language - PostgreSQL Global Development Group (accessed 2026-08-21)
This guide is generated from DigiLearn course material. Product versions, regulations and professional standards can change; consult the linked authoritative source before applying version-sensitive guidance.