Modern Data Management for Manufacturers
Data is not just a byproduct; it is a strategic asset for all manufacturers. From optimizing production schedules to forecasting demand, the ability to manage and interpret data effectively can make or break operational success.
Modern data management revolves around four key technologies: Data Lakes, Data Factories, Databricks, and Data Warehouses. Together, they form a powerful ecosystem that transforms raw inputs into refined insights.
It starts with the Data Lake, a flexible repository that captures unstructured and semi-structured data from sources like IoT sensors, machine logs, and raw material tracking. This foundational layer supports exploratory analysis and long-term retention, making it ideal for predictive maintenance and AI experimentation.
Once data is captured, it must be shaped and moved. That is where Data Factories and Databricks come into play. Data Factory automates ETL workflows, seamlessly integrating with ERP systems like Epicor to ensure real-time data movement. Meanwhile, Databricks empowers teams to perform advanced analytics and machine learning, enabling deeper insights into historical trends and operational performance.
The final destination is the Data Warehouse, a structured, centralized hub optimized for reporting and strategic planning. Cleaned and organized data from ERP outputs, BOMs, and financial metrics flows here, ready to be visualized through tools like Power BI. This is where manufacturers gain clarity on production costs, delivery performance, and quality metrics.
At 2WTech, we specialize in building this data pipeline for manufacturing and distribution organizations. From Epicor integrations to Azure-powered analytics, we help clients turn complexity into clarity, unlocking real-time insights and driving smarter decisions across the enterprise. Your business generates data every day. The real question is: are you just storing it, or using it to drive innovation?
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