Data Sources & Storage Assessment
Performed a full assessment of enterprise data sources, ingestion pipelines, storage systems, data quality, and reporting landscape, including recommendations and tooling strategy.
Problem
Data was collected from many systems (ERP, CRM, OT, web apps, databases) with no unified ingestion method, inconsistent storage patterns, and weak reporting foundations. Analytics teams struggled with data trust and availability.
Approach
Mapped all enterprise data sources including SAP, manufacturing systems, IoT/OT devices, cloud apps, and databases. Analyzed storage layers across on-prem databases, cloud buckets, warehouses, and shared repositories. Assessed pipelines (ETL/ELT), data refresh rates, API availability, and integration methods. Evaluated BI/reporting tools and data quality dimensions. Built a unified architecture view and performed gap analysis.
Solution
Delivered a structured assessment that included: Data Source Inventory (systems, owners, formats, refresh frequency) Storage Portfolio Assessment (cost, performance, scalability, security) Pipeline & Orchestration Review Data Quality Dashboard (metrics, scoring, exceptions) BI/Reporting Standardization Plan Recommended Tooling: Data Lake / Warehouse / Catalog / ETL tools Unified Data Model Blueprint Automated Reporting Layer Proposal
Impact
Improved clarity on all organization-wide data flows and dependencies. Reduced storage costs by identifying redundant or over-provisioned environments. Improved data quality and confidence for analytics teams. Enabled the decision to adopt a unified data lake architecture. Provided a clear roadmap for modernizing data pipelines and storage systems.