HP Indigo Boosts Manufacturing Yield and Traceability with Databricks and Unity Catalog
HP Indigo migrated more than 3,500 data volumes (~10 terabytes) of disparate ERP, manufacturing and field data, previously tracked manually across spreadsheets and legacy systems, onto Databricks and Unity Catalog. Unity Catalog's built-in data lineage reduced consumable traceability time from two to three days down to about one hour. HP Indigo also built a prediction model on Databricks to optimize manufacturing parameters for one of its parts, increasing yield from 60% to 92%. Databricks AI/BI Genie provides natural-language, self-service data access for business users, replacing ad hoc requests to technical teams.
Overview
HP Indigo migrated more than 3,500 data volumes (~10 terabytes) of disparate ERP, manufacturing and field data, previously tracked manually across spreadsheets and legacy systems, onto Databricks and Unity Catalog. Unity Catalog's built-in data lineage reduced consumable traceability time from two to three days down to about one hour. HP Indigo also built a prediction model on Databricks to optimize manufacturing parameters for one of its parts, increasing yield from 60% to 92%. Databricks AI/BI Genie provides natural-language, self-service data access for business users, replacing ad hoc requests to technical teams.
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Inspect the highlighted sourceThe challenge
HP Indigo faced challenges with disparate legacy systems and manual data tracking that slowed decision-making and limited operational visibility. Some critical data was tracked manually in spreadsheets across different parts of the company, making it nearly impossible to maintain a single source of truth.
The solution
To unify its data and empower employees with reliable, trusted insights, HP Indigo turned to Databricks and Unity Catalog, migrating legacy data warehouses and manual data files onto a single platform with built-in data lineage. HP Indigo implemented Databricks AI/BI Genie to let business users ask questions in natural language and get answers directly from Unity Catalog-governed data, and developed a prediction model on Databricks to optimize manufacturing parameters for one of its parts.
Reported business value
Tracing manufactured consumables through HP Indigo's legacy systems took two to three days; with Unity Catalog, that process now takes just 60 minutes. Using a prediction model in Databricks, HP Indigo increased yield on one manufactured part from 60% to 92%.
Sources
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