Key Highlights: What This Case Study Covers
- Modern data engineering solutions with a three-year roadmap designed for scalability and flexibility.
- Unified data management layer creating a single source of truth for consistent enterprise-wide access.
- Batch and near real-time ingestion with Informatica, GSUTILS, Pub/Sub, and Dataflow.
- Multi-zone BigQuery data architecture supporting history preservation, trusted transformations, and advanced analytics.
- Enterprise-ready Power BI dashboards enabling ANZ-wide visibility for executives, sales leaders, and frontline teams.
- Improved data governance and literacy by treating data as a product, driving trust and adoption across the workforce.
Client Overview
A large automotive aftermarket parts supplier in Australia and New Zealand. With operations spanning both countries, they needed a modern analytics platform to unify data silos and empower decision makers with reliable insights at scale.
The Ask
The client sought a robust data and analytics platform that could:
- Consolidate fragmented systems into a single, reliable environment.
- Integrate both historical and real-time data pipelines.
- Deliver interactive Power BI dashboards for enterprise-wide sales analytics across ANZ.
Challenges
- Data Silos: Legacy on-premises Oracle systems created fragmented, hard-to-access data.
- Scalability Limitations: Processes lacked flexibility to handle new use cases and growing data volumes.
- Real-time Gaps: Reporting was limited to batch cycles without streaming ingestion.
- Governance Gaps: Inconsistent data management practices reduced trust and slowed adoption.
- Visibility Issues: Sales leaders lacked consolidated dashboards for performance monitoring.
Our Solution: Enterprise Data Platform on GCP
Data Ingestion & Storage
- Executed a one-time 2TB Oracle migration using GSUTILS (bulk) and Informatica (batch)
- Automated daily incremental loads into Google Cloud Storage.
- Enabled near real-time ingestion with Pub/Sub and advanced transformations via Dataflow.
Data Management Layer
- Raw Zone (GCS): Source replicas in native formats.
- Trusted Zone (BigQuery): SCD Type 2 for historical accuracy.
- Refined Zone (BigQuery): Cleansed, aggregated, and business-ready datasets.
Orchestration & Semantic Layer
- Informatica orchestrated end-to-end pipelines.
- BigQuery Views and BI Engine created a semantic layer for optimized, user-friendly reporting.
Dashboards & Consumption
- Power BI dashboards provided multi-level insights:
- Executive KPIs for Australia, New Zealand, and ANZ.
- Sales analysis across ACE and non-ACE segments.
- Enterprise views for variance, year-on-year, and margin trends.
- Power users accessed BigQuery directly for advanced self-service analytics.
Impact Delivered
- Established a single source of truth for reliable, trusted enterprise analytics.
- Scalable data ingestion and management framework supporting both historical and streaming use cases.
- Stronger data governance practices improved adoption and decision-making confidence.
- Executives and sales teams gained ANZ-wide visibility and faster insights through intuitive dashboards.
