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Virtusa is the first system integrator (SI) partner to finish DB Freedom Program with AWS. With two decades of data management expertise, we help build cloud-native data store for organizations leveraging services such as Amazon S3, Amazon RDS, Amazon Aurora, Amazon Redshift, and Amazon EMR. We use a holistic approach to migrate legacy data store to AWS. Our proprietary data migration accelerators combined with native AWS migration utilities offers a differentiated approach to cloud enable your data systems.
We leverage native AWS utilities such as Schema Conversion Tool (SCT) and DMS (Data Migration Services) for one-time schema migration and initial data load.
Learn more about Virtusa’s Amazon Redshift Experience
Amazon Elastic MapReduce (EMR) is an Apache Hadoop and Spark distribution built for the cloud that combines the integration and testing rigor of commercial Hadoop distributions with the scale, simplicity, and cost effectiveness of the cloud.
Combining our proprietary tools and AWS services, we analyze you current IT landscape and help rapidly and successfully migrate data assets from Oracle, SQL Server, Teradata, Netezza to Amazon Redshift.
Data Asset Rationalization Framework enables rationalization of on-premise data assets prior to cloud migration and facilitates identification of the right set of data to be migrated. It classifies enterprise data assets and provides rationalization recommendations in line with the future state data strategy.
Database Objects Analyzer aids in quick analysis of database objects (tables, views, stored procedures, functions, scripts/codes) and helps in sizing the project and complexity of migration. It offers reports containing list of objects such as transformations and functions, complexity information, and source/target dependency information.
Code Converter converts procedural logic/SQL code into SQL scripts/PySpark data frames, preserving business logic and general flow. It groups patterns and migrates code segments (70-95%), reducing total project cost by up to 80%. It also refactors the code so that native cloud elasticity can be leveraged.
PySpark-based Data Transformation Framework helps in processing incremental data load. It was developed using Sqoop, PySpark, AWS Glue, AWS Glue catalogue and AWS S3. It reduces the effort to build new ETL job by 50% and delivers 40% improved performance over several leading COTS ETL platforms.
We offer end-to-end services right from helping you jumpstart your AWS journey, to migrating and managing solutions from the AWS suite.
Contact us to speak to an expert, request an assessment, or demo our solutions.