Data Engineering
Representative SolutionAutomated Data Platform
Created scheduled ETL pipelines and a centralized warehouse connecting operational systems to executive reporting.
1 source
Of analytical truth
This is a representative solution describing the type of system LT Lab delivers. It does not describe a specific named client engagement.
The challenge
What wasn't working
An organization with operations in several locations produced executive reports from exports of its ERP, CRM and field systems. Each report took days and definitions differed between teams.
Historical analysis was nearly impossible because source systems overwrote past values.
Approach
How the solution was built
Step 01
Define the metrics
Agreed definitions for core KPIs with finance and operations leaders before building anything.
Step 02
Automate ingestion
Scheduled extraction from each source system and API into a raw layer, with freshness and volume checks.
Step 03
Model the warehouse
Tested transformations into dimensional models with historical tracking for key entities.
Step 04
Deliver reporting
Executive and operational dashboards connected to governed datasets, with documentation for analysts.
Architecture
System overview
- ERP / CRM / APIs
- Airflow ingestion
- Raw layer
- dbt models
- Warehouse
- BI dashboards
Outcomes
What changed
- A single, documented set of KPI definitions
- Daily refreshed reporting without manual preparation
- Historical trend analysis now possible
- A clean foundation ready for forecasting and AI
Technologies
Python / Airflow / dbt / PostgreSQL / Cloud storage / Power BI
Services involved