Accelerated migration to AWS

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

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Explore the transformation potential in your business with AWS

 

/ Assessment
  • Get answers to key questions
  • Will it make sense to design my future-state architecture using all AWS-native services (for data processing and storage, orchestrating, analytics, BI/reporting, etc.)?
  • Will I know which workloads can benefit from EMR vs. Redshift cloud data warehouses or AWS Glue, Lambda, Step Functions, etc.?
  • Can I save provisioning and maintenance costs for rarely used workloads on AWS?
  • Data warehouse
  • Can I get schema optimization recommendations for distribution style and dist keys, sort keys, etc.?
  • ETL
  • Will the assessment help me choose AWS-native services for meeting ETL SLAs?
  • Analytics
  • Will it be beneficial to convert analytical functions to Spark libraries or some native AWS functions?
  • Will my ETL processing SLAs impact my choice of an optimum Amazon EMR cluster size?
  • Hadoop
  • Is my optimization strategy for Update/Merge on AWS Redshift apt?
  • Can I get schema optimization recommendations for distribution style and dist keys, sort keys, etc.?
  • 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 for and orchestration using AWS-native services
  • Intelligent transformation engine, delivering up to 95% automation for:
  • Data warehouse to AWS stack migration – Amazon EMR, Amazon Redshift, Snowflake on AWS, Databricks on AWS
  • ETL to AWS stack migration – AWS Glue, Amazon Redshift, PySpark
  • Analytics to AWS stack migration – Amazon EMR, PySpark
  • BI/Reporting to AWS stack migration – Amazon QuickSight
  • Hadoop to AWS migration – Amazon Redshift, Snowflake on AWS, Presto query engine
/ validation
  • All transformed data warehouse, ETL, analytics, BI/reporting, and/or Hadoop workloads
  • Business logic (with a high degree of automation)
  • Cell-by-cell validation
  • File to file validation
  • Integration testing on enterprise datasets
  • Assurance of data and logic consistency and parity in the new target environment
/ operationalization
  • Productionization and go-live
  • Capacity planning for optimal cost-performance ratio
  • Performance optimization
  • Robust cutover planning
  • Infrastructure as code
  • Automated CI/CD
  • Data warehouse – Provisioning of Amazon EMR/Amazon EC2/AWS Redshift/Snowflake, and other AWS services for orchestration, monitoring, security etc.
  • ETL – Provisioning of AWS Glue and other required services
  • Analytics – Provisioning of Amazon EMR and other required services
  • BI/Reporting – Provisioning of Amazon QuickSight
  • Hadoop – Provisioning of Redshift/Snowflake on AWS and other required services

Automated workload migration: Hadoop to Amazon EMR

Automated reporting migration to AWS: Tableau to Amazon QuickSight

Automated data warehouse migration to AWS: Oracle to Amazon Aurora

Automated reporting migration to AWS: OBIEE to Amazon QuickSight

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Explore resources to support your transformation initiatives

Case Study

Data platform migration and modernization on AWS significantly reduces passenger wait time for United Airlines

Case Study

A bank’s analytics transformation journey - Automated assessment and transformation of Informatica workflows and Oracle EDW to AWS

Case Study

Automated Netezza data warehouse to AWS migration for a Fortune 500 mortgage lender

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Learn more about the benefits and best practices for AWS-native transformation