Manufacturing Case Study: Transforming Data Pipelines with Databricks

 Second Largest Appliances Manufacturer Globally​

Use Case

Streamlining Data Pipelines​

Geography

Nordic Region

Problem

Large-Scale Legacy Data Migration

Industry

Information Technology

Pipeline Puzzle

Migrating 500+ Legacy pipelines under a Tight Deadline

Our impactful transformations—like 500+ pipeline migrations and creating Single Views of Customers—demonstrate our
ability to solve complex challenges effectively.

30%
More transparency in the sites’ risks
25%
Time was reduced to search for data within a single factory
50%
More safety measure against high-risks situations
1 - Manufacturer Case Study

Technology

Before Diggibyte:
Our customer’s business-critical data was hosted on an older version of Data lake Storage (ADLS Gen 1), which will become obsolete in February 2024.
After Diggibyte:
To safeguard against data loss, our crossfunctional team, alongside our experts, successfully completed the migration of over 500 terabytes of data with minimal disruption to the business

Business Challenge

The client’s critical data resided on an outdated version of Azure Data Lake Storage (ADLS Gen 1), scheduled for deprecation in February 2024. This impending obsolescence necessitated the migration of over 500 legacy data pipelines, each developed in various programming languages and lacking clear data ownership. The complexity of this task was heightened by a stringent timeline and the need to ensure business continuity.​

The Solution

Leveraging Databricks’ Lakehouse Platform, our cross-functional team executed a comprehensive migration strategy:​

  • Data Consolidation:Unified disparate data sources into a centralized repository using Databricks’ Delta Lake, enhancing data consistency and reliability.​
  • Pipeline Refactoring:Re-engineered over 500 data pipelines to align with Databricks’ scalable architecture, facilitating efficient data processing and integration.​
  • Optimization and Governance: Implemented Databricks’ Unity Catalog to establish robust data governance, ensuring secure and streamlined data access across the organization.​

The Impact

The migration to Databricks yielded significant benefits:​

  • Data Efficiency:Eliminated over 300 redundant pipelines, resulting in a data reduction of nearly 100 terabytes.​
  • Enhanced Transparency:Achieved a 30% increase in visibility into site-specific risks, enabling proactive risk management.​
  • Operational Efficiency:Reduced data search times within a single factory by 25%, streamlining operations and decision-making processes.​
  • Improved Safety Measures:Enhanced safety protocols led to a 50% increase in measures against high-risk situations, promoting a safer working environment.​