Integrate and Manage Databases in Full Stack Applications
Overview
This standard defines the competencies required to design, implement and manage data storage solutions that support full stack applications. It covers data modelling, schema management, query optimisation, security and compliance, resilience, and operational monitoring to ensure databases remain reliable, performant and compliant throughout the application lifecycle.
Data is a core asset for organisations, and effective database management ensures that applications can deliver consistent, reliable, and accurate services. Secure and well-managed databases support compliance with regulatory requirements, protect sensitive information, and enable scalability as applications grow in complexity and demand.
This standard is intended for professionals responsible for managing data systems within full stack environments, including developers, database administrators, and data engineers.
Performance criteria
You must be able to:
- Model data and select appropriate data stores based on access patterns, consistency requirements and scalability needs, in line with organisational architecture and data standards.
- Implement schema migration and versioning processes safely, managing schema evolution across environments in line with organisational change and release management procedures.
- Write and optimise queries using indexing and query plan analysis, in line with organisational performance and efficiency standards.
- Configure database connection management and concurrency controls, including pooling, timeouts and isolation levels, in line with workload requirements and organisational standards.
- Implement database security controls, including access control, encryption and auditing, in line with organisational security policies and data-protection requirements.
- Define and implement data retention, archival and deletion policies, including lawful handling of personal data, in line with legal, regulatory and organisational requirements.
- Configure high availability, backup and recovery processes, and test recovery procedures, in line with organisational resilience standards and defined recovery objectives.
- Monitor database capacity, performance and cost, and identify optimisation opportunities, in line with organisational monitoring and financial management practices.
- Maintain data quality and integrity across integrations and updates, in line with organisational data governance and assurance standards.
- Document database architecture, configurations and changes, in line with organisational documentation and change control standards.
Knowledge and Understanding
You need to know and understand:
- Data modelling techniques and schema design approaches for relational and non-relational databases, and how these align with different access patterns and consistency models.
- Principles and practices of schema migration, versioning and safe schema evolution across development, test and production environments.
- Query optimisation techniques, including indexing strategies, execution plans and performance tuning methods.
- Transaction management concepts, including concurrency control, isolation levels and consistency trade-offs.
- Database security controls and compliance requirements, including role-based access control, encryption, auditing and lawful handling of personal data.
- Backup, recovery and high-availability strategies, including replication, failover and recovery point and recovery time objectives.
- Database monitoring, capacity planning and cost optimisation practices, and how these support reliable and sustainable operation.
- Data retention, archival, and deletion policies, including Right to Be Forgotten (RTBF), and associated legal and regulatory obligations.
- Data quality management practices, including reconciliation and approaches to handling eventual consistency.
- Documentation practices for database design, architecture, and operational procedures, including change control processes.
Scope/range
Scope Performance
Scope Knowledge
Values
Behaviours
Skills
Glossary
Relational database
A database that stores data in structured tables with defined relationships, typically using schemas and transactions to support consistency and integrity.
NoSQL database
A non-relational database designed to handle large volumes of data with flexible schemas, often optimised for scalability, availability or specific access patterns.
Data modelling
The process of defining data structures, relationships and constraints to support application and business requirements.
Schema migration
The controlled process of modifying a database schema over time while preserving data integrity and availability.
Schema versioning
The practice of tracking and managing changes to database schemas across different environments.
Query optimisation
The process of improving query performance through indexing, execution plan analysis and efficient query design.
Query plan analysis
The examination of how a database executes a query in order to identify performance bottlenecks and optimisation opportunities.
Transaction management
The control of database operations to ensure data consistency and integrity when multiple operations are performed concurrently.
Concurrency control
Mechanisms that manage simultaneous access to data to prevent conflicts and maintain consistency.
Connection management
The configuration and control of database connections, including pooling, timeouts and resource limits.
Database security controls
Technical and procedural measures used to protect databases, including access control, encryption, auditing and monitoring.
Data retention
Policies and practices that define how long data is stored before being archived or deleted.
High availability
The design of database systems to minimise downtime through redundancy, replication or failover mechanisms.