Accelerated migration to Databricks

Accelerate your ETL, analytics, Hadoop, and data warehouse migration and transformation to Databricks with LeapLogic





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    Explore the transformation potential in your business with Databricks

    / Assessment
    • Say yes to key questions
    • 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, bloom filters, ZOrder indexing,, 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?
    • Analytics
    • Can I transform my analytics layer as well along with my data warehouse, ETL systems, and BI?
    • BI/Reporting
    • Can I use the processed data from my modern cloud-native data warehouse stack for my BI/reporting needs and leverage it with a modern BI stack?
    / transformation
    • Packaging and orchestration using Databricks-native wrappers
    • Intelligent transformation engine, delivering up to 95% automation for:
    • Data warehouse and ETL to Databricks migration – Databricks Lakehouse, Databricks Notebook, Databricks Jobs, Databricks Workflows, Delta Lake, Delta Live Tables
    • Analytics to Databricks migration – Databricks Lakehouse on AWS/Azure/GCP, PySpark
    • Hadoop to Databricks migration – 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
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    Automated workload transformation from Informatica to Databricks

    Automated Teradata data warehouse migration to Databricks

    Automated workload transformation from SAS to Databricks

    Automated workload transformation from Hadoop to Databricks

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    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

    Webinar

    Automated legacy ETL, Hadoop, analytics, and data warehouse platform migration to Databricks

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

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