Intelligence Layer
Most data projects fail at transformation—18 months building pipelines that break when source formats change. We've built a four-stage architecture (FEED → UNIFY → ENRICH → LAUNCH) that turns raw data into analysis-ready datasets automatically. The transformation logic is maintained centrally, so your pipelines stay current without engineering effort.
The FUEL data pipeline
FEED
Data stored exactly as received—no cleaning, no reformatting. Every source system gets its own tables. Complete audit trail from original file to final output. When something looks wrong downstream, you can trace it back to the source.
UNIFY
Multiple systems with different formats mapped to unified business concepts—Receipts, Products, Stores, Staff. POS, GrabFood, and Foodpanda transactions all become one Receipts table. Fragmented data consolidated into a single source of truth.
ENRICH
Where business logic lives. Calculate KPIs, apply tax rules, derive metrics. Raw transactions become daily summaries, performance rankings, location comparisons. The calculations that used to live in scattered spreadsheets, now centralized and consistent.
LAUNCH
Analysis-ready data with formatting applied—currency symbols, percentages, color-coded performance indicators. Optimized for dashboards, reports, and AI queries. The final stage before insights reach your team.
Build pipelines with Query Studio
Write SQL transformations, test with live data, deploy to production. SQL Agent assists with optimization and suggests fixes. A proper development environment for your data pipeline.
What you get
- Write SQL transformations in Query Studio—full IDE with syntax highlighting, autocomplete, and inline schema documentation for all FUEL stage tables
- SQL Agent assists development—suggests optimal joins, identifies schema issues, recommends indexes, and explains query execution plans in plain English
- Test with live data previews—run queries against actual data, see results instantly, validate transformations before deploying to production pipeline
- Schedule and orchestrate with VAL Workflow—run transformations on a schedule, trigger when new data arrives, or chain through FUEL stages sequentially
Data transformations through FUEL stages
FEED: Raw data preserved as received
Data stored exactly as received—no reformatting, no cleaning. Complete audit trail shows original file, ingestion timestamp, and source system metadata.
UNIFY: Multiple sources mapped to Domain Model
Multiple systems with different schemas mapped to standardized entities. POS, GrabFood, and Foodpanda all become unified Receipts with consistent fields. One table consolidates three source systems.
ENRICH: Business logic applied to unified data
SQL transformations calculate KPIs, apply tax adjustments, and categorize transactions. Raw receipts become daily summaries with revenue by location, transaction averages, and hourly trends.
LAUNCH: Action-ready datasets for consumption
Enriched data with comparisons, rankings, and display formatting. Optimized for dashboards and automated reports with currency symbols, percentages, and performance indicators.
Ready to transform your data?
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