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As a company grows, data sources multiply: production ERP, accounting software, e-commerce platform, CRM, IoT sensors and HR system. Each produces data in different formats and on different cycles. The question "what's the real number?" becomes impossible to answer.
At Digital Bridge we consolidate every source into a single, clean and reliable data warehouse. The dashboards, reports and AI models that draw from it all rely on consistent data.
Reliable, scheduled and replayable Extract-Transform-Load pipelines. Raw data is pulled from sources, transformed to business rules and loaded into the destination. Failed loads are logged and retried automatically.
PostgreSQL, MSSQL or cloud-based (BigQuery, Redshift) data warehouse architectures. Star-schema modelling for fast queries and flexible reporting. Historical retention and period-based versioning.
Data lake design for unstructured or high-volume raw data (sensor streams, log files, images). Raw layer → curated layer → service layer separation enforces data governance.
Gaps, duplicates, format inconsistencies and referential-integrity violations in source data are detected automatically. Quality scores are tracked; critical drops trigger manager alerts.
Depending on business criticality, data is moved live (streaming), every minute, hourly or daily (batch). Change Data Capture (CDC) moves only changed data, minimising load on source systems.
Business-aligned data marts on top of the warehouse: sales, production, finance, inventory. Each mart owns its KPI definitions and serves BI tools or custom APIs.
The data warehouse becomes the single source of truth; the BI dashboard built on top of it visualizes that data. When we deliver both layers together the whole team works from the same numbers, reports stop disagreeing, and managers reach meaningful insights faster.