Eliminated-Data-Latency-and-Optimized-Cost-by-migrating-Teradata-Hadoop-and-AbInitio-ETL-to-Databricks-on-Microsoft

Onix Eliminates Data Latency and Cuts Costs for Tech Company with Databricks on Azure Migration

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The Company:

The client is a major technology company with a vast data landscape. They are committed to leveraging data-driven insights for continuous innovation and business optimization.

Industry:

Technology

The Challenges: 

  • Legacy Infrastructure Constraints:The client’s on-premises Teradata and Hadoop systems posed limitations, including high costs, latency issues, and challenges with data availability and quality.
  • Need for Scalability and Cost Control:They sought a modern cloud-based solution to scale cost-effectively and handle growing data volumes.
  • Real-Time Analytics Imperative:Minimizing data latency was crucial for timely decision-making and driving responsive business operations.
  • Data Quality Assurance:Improving data accuracy and consistency across their platform was essential for reliable insights.

The Solution

Datametica (now an Onix company), orchestrated a seamless migration from Teradata and Hadoop to Databricks on Azure. Key components included:

  • In-depth Assessment with Eagle:We conducted a comprehensive analysis of the existing environment with Eagle, providing a roadmap for an efficient migration.
  • Raven-Powered Automation:Raven accelerated the conversion of database objects (tables, views, stored procedures), ETL code (Hive, Impala, Ab Initio), and job orchestration to Databricks/Azure native components.
  • Data Validation with Pelican:Meticulous cell-level validation with Pelican ensured absolute data integrity and accuracy between source and target environments.
  • Power BI Integration:We established connectivity with Power BI, ensuring continuity of the client’s preferred reporting and analytics workflows.

Outcomes

  • Zero Data Latency: Databricks on Azure resolved data latency issues, enabling real-time or near-real-time analytics for agile decision-making.
  • Enhanced Data Quality:The migration significantly improved data accuracy and consistency, leading to greater confidence in insights and decision-making.
  • Optimized Operational Costs:The cloud-based Databricks platform delivered substantial cost savings compared to legacy infrastructure.
  • Accelerated Time-to-Value:Datametica’s migration suite enabled a 40% faster migration timeline, minimizing disruption for the client.

Conclusion

Our expertise in migrating Teradata and Hadoop to Databricks on Azure not only resolved the client’s existing challenges but also set them up for a modern, scalable, and cost-effective data warehousing solution with improved data quality and availability. This transformation empowered the company with real-time analytics, scalable infrastructure, and greater cost-efficiency—positioning them to lead with data-driven innovation.

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