Database Design & Operations

Use Cases

• High-Volume Transactional Database Design

  Schema design, partitioning, and indexing strategies for OLTP systems that stay responsive under millions of daily transactions — order processing, telemetry ingestion, and audit logging.

• Reporting Warehouses & Analytics Models

  Star-schema warehouses and read-optimized replicas that take analytical load off production systems, feeding dashboards and BI tools without slowing the business down.

• Zero-Loss Database Migrations

  Move between engines, versions, or hosts — SQL Server upgrades, on-premise to cloud, monolith to service-per-database — with rehearsed cutover plans and row-count reconciliation.

• Performance Tuning & Query Optimization

  Execution-plan analysis, index consolidation, and query rewrites that turn minute-long reports into sub-second responses — measured before and after, not guessed.

• High Availability & Disaster Recovery

  Failover clustering, log shipping, and tested restore procedures with recovery-time and recovery-point objectives your business actually signs off on.

• GDPR Data Lifecycle & Retention

  Data classification, anonymisation pipelines, retention schedules, and subject-access tooling built into the database layer, where compliance can be proven rather than promised.

Key Benefits

• Queries tuned against measured execution plans, not folklore
• Backup and restore procedures that are actually rehearsed
• Schemas designed for the data volume you will have, not just today's
• GDPR retention and anonymisation enforced at the data layer
• Monitoring that flags degradation before users feel it

Technologies We Use

Our Approach

1. 1

   Workload & Schema Assessment

   Profile real query patterns, data growth, and pain points before touching anything — the baseline every improvement is measured against.

2. 2

   Design & Remediation Plan

   Prioritised plan covering schema changes, indexing, partitioning, and hardware or tier decisions, with expected impact per item.

3. 3

   Staged Implementation

   Changes applied in reviewed, reversible batches — index by index, table by table — with performance measured at every step.

4. 4

   Migration & Validation

   Where data moves, automated reconciliation verifies every row arrived intact before the old system is switched off.

5. 5

   Monitoring & Handover

   Alerting on the metrics that matter, documented runbooks, and knowledge transfer so your team owns the result.

What You Get

Related Projects