Accelerated migration to Databricks

With LeapLogic, your transformation to Databricks will happen faster, with more accuracy, thanks to superior analysis, automation, and validation

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Explore the transformation potential in your business
with Databricks

/ Assessment
  • Get answers to key questions
  • Can I identify anti-patterns in my existing code and resolve them as per Databricks Lakehouse coding techniques and standards?
  • Will it make sense to design my future-state architecture using all cloud-native services (for orchestrating, monitoring, etc.)?
  • Will I know if I can meet my SLAs through Databricks Lakehouse or if I need cloud-native warehouses?
  • Data warehouse
  • Can I get schema optimization recommendations for partitioning, bucketing, clustering, etc.?
  • ETL
  • Will my ETL processing SLAs impact my choice for an optimum Databricks cluster size?
  • Can I save provisioning and maintenance costs for rarely used workloads on Databricks?
  • Hadoop
  • Is my optimization strategy for Update/Merge on Databricks apt?
/ transformation
  • Packaging and orchestration using Databricks-native wrappers
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse and ETL – Databricks Lakehouse on AWS/Azure/GCP
  • Analytics – Databricks Lakehouse on AWS/Azure/GCP, PySpark/Scala + Spark
  • Hadoop – Databricks Lakehouse on AWS/Azure/GCP, Presto query engine
/ validation
  • All transformed data warehouse, ETL, analytics, and/or Hadoop workloads
  • Business logic (with a high degree of automation)
  • Cell-by-cell validation
  • Integration testing on enterprise datasets
/ operationalization
  • Capacity planning for optimal cost-performance ratio
  • Performance optimization
  • Robust cutover planning
  • Infrastructure as code
  • CI/CD
  • Provisioning of Databricks Lakehouse and other required services

Automated workload transformation from Informatica to Databricks

Automated workload transformation from Teradata to Databricks

Automated workload transformation from SAS to Databricks

Automated workload transformation from Hadoop to Databricks


Explore resources to support your transformation initiatives

Case Study

30% performance improvement by converting Netezza and Informatica to Azure-Databricks stack

Case Study

20% SLA improvement by modernizing Teradata workloads on Azure


Automated modernization of legacy EDW, ETL, Hadoop, and analytics platform to Databricks


Learn more about these benefits and best practices for cloud-native transformation