The Problem: Data You Have But Cannot Use
Most businesses in the GCC are not short on data. They have ERP systems generating transaction records, CRMs tracking sales pipelines, operational databases logging events, and spreadsheets capturing everything that fell between the cracks. The problem is not quantity — it is access, consistency, and trust.
When leadership asks "How did we perform last month?", the answer takes days. Someone pulls an Odoo report, someone else exports a spreadsheet, a third person reconciles the numbers manually. By the time the answer arrives, the data is stale and confidence in it is low. Strategic decisions get made on gut feel — not because leadership wants it that way, but because the data infrastructure was never designed to answer that question in real time.
The Solution: A Unified Data Platform on Google Cloud
We design and build data platforms on Google BigQuery that pull from every system your business runs — Odoo ERP, operational databases, third-party APIs, flat files — and consolidate everything into a single, governed data warehouse. From there, Looker dashboards give your business teams live, accurate visibility into the metrics that matter, without needing a data analyst in the room every time a question comes up.
This is not a reporting tool bolted onto an existing system. It is a proper data architecture — designed to grow with your business, add new data sources without rebuilding from scratch, and maintain data quality as a core constraint rather than an afterthought.
What We Build
Unified Data Warehouse on Google BigQuery
BigQuery is Google Cloud's serverless, fully managed analytics database. We design your warehouse schema using a layered data modelling approach — raw staging, transformation, and curated analytical layers — so your data is organised for fast querying, governed access, and long-term maintainability. There is no infrastructure to provision and no capacity to manage. BigQuery scales to petabytes automatically, and you pay only for what you query.
Automated ETL Pipelines
We build extraction, transformation, and load pipelines that move data from your source systems into BigQuery on a defined schedule — hourly, daily, or near real-time. Pipelines are built using Google Cloud's native toolset, including Dataflow, Cloud Composer, and Application Integration, depending on your architecture and latency requirements. Every pipeline is version-controlled, monitored, and alertable. If a pipeline fails or produces unexpected data volumes, your team knows immediately.
Data Quality & Governance Layer
A dashboard built on bad data is worse than no dashboard — it creates false confidence in decisions that are actually wrong. We implement data quality checks at the pipeline level: completeness validation, referential integrity, range checks, null rate monitoring, and data freshness alerts. Data that fails quality gates is quarantined for review and investigation, not silently overwritten. Your teams can trust what they see on every report.