Your Migration Solution
The time to experience the benefits of the cloud is now—and LeapLogic makes migration possible, no matter your business workflows or needs
Select any source and target below
Explore the transformation potential
Discover the power of smarter, faster transformation from Teradata
LeapLogic assesses and transforms diverse Teradata scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption
/ Source scripts
- DML and DDL scripts
- Stored procedures
- Shell scripts and macros
- BTEQ, TPT, MultiLoad, FastLoad, FastExport, etc.
/ ETL scripts
- Informatica, DataStage, Ab Initio, ODI, SSIS, Talend, Matillion, Pentaho, SnapLogic, etc.
/ Analytics scripts
- SAS, Alteryx, etc.
/ BI scripts
- Tableau, Cognos, OBIEE, etc.
/ Orchestration
- Control-M, AutoSys, EPS, Cron Shell, etc.
Discover the power of smarter, faster transformation from Netezza
LeapLogic assesses and transforms diverse Netezza scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption
/ Source scripts
- DML and DDL scripts
- NZPLSQLs
- Shell scripts
- NZ SQL, Export/Load, etc.
/ ETL scripts
- Informatica, DataStage, Ab Initio, ODI, SSIS, Talend, Matillion, Pentaho, SnapLogic, etc.
/ Analytics scripts
- SAS, Alteryx, etc.
/ BI scripts
- Tableau, Cognos, OBIEE, etc.
/ Orchestration
- Control-M, AutoSys, EPS, Cron Shell, Airflow, etc.
Discover the power of smarter, faster transformation from Oracle
LeapLogic assesses and transforms diverse Oracle scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption
/ Source scripts
- DML and DDL scripts
- PL/SQLs
- Shell scripts
- SQL Loader/Spool, etc.
/ ETL scripts
- Informatica, DataStage, Ab Initio, ODI, SSIS, Talend, Matillion, Pentaho, SnapLogic, etc.
/ Analytics scripts
- SAS, Alteryx, etc.
/ BI scripts
- Tableau, Cognos, OBIEE, etc.
/ Orchestration
- Control-M, AutoSys, EPS, Cron Shell, Airflow, etc.
Discover the power of smarter, faster transformation from SQL Server
LeapLogic assesses and transforms diverse SQL Server scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption
/ Source scripts
- DML and DDL scripts
- Stored procedures
- Shell scripts with embedded SQL Server blocks
- TSQL, etc.
/ ETL scripts
- Informatica, DataStage, Ab Initio, ODI, SSIS, Talend, Matillion, Pentaho, SnapLogic, etc.
/ Analytics scripts
- SAS, Alteryx, etc.
/ BI scripts
- Tableau, Cognos, OBIEE, etc.
/ Orchestration
- Control-M, AutoSys, EPS, Cron Shell, etc.
Discover the power of smarter, faster transformation from Vertica
LeapLogic assesses and transforms diverse Vertica scripts and ETL, so you can feel the freedom of the cloud quickly, with lower risk of disruption
/ Source scripts
- DML and DDL scripts
- Shell scripts
- VSQL, Load, Export, etc.
/ ETL scripts
- Informatica, DataStage, Ab Initio, ODI, SSIS, Talend, Matillion, Pentaho, SnapLogic, etc.
/ Analytics scripts
- SAS, Alteryx, etc.
/ BI scripts
- Tableau, Cognos, OBIEE, etc.
/ Orchestration
- Control-M, AutoSys, EPS, Cron Shell, Airflow, etc.
Discover the power of smarter, faster transformation from Informatica
LeapLogic assesses and transforms diverse Informatica code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses Informatica XML files, Informatica BDM scripts, IICS (Informatica Cloud) scripts
- Converts workflows and mappings to:
- Cloud-native ETL: AWS Glue Studio, AWS Glue Jobs, AWS Glue Notebook, Matillion ETL, Snowflake/Snowflake Scripting, Redshift ELT, Databricks Lakehouse/Notebook, Databricks Delta Live Tables, Databricks Unity Catalog, DBT + Snowflake, Azure Data Factory, etc.
- Cloud-native warehouses: Amazon Redshift, Databricks Lakehouse/Notebook, Snowflake, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts Informatica scheduler scripts
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from Datastage
LeapLogic assesses and transforms diverse Datastage code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses XML, DSX scripts
- Converts jobs and stages to:
- Cloud-native ETL: AWS Glue Studio, AWS Glue Jobs, AWS Glue Notebook, DBT, Matillion ETL, Snowflake, Databricks Lakehouse/Notebook, Databricks Delta Live Tables, Databricks Workflows, Databricks Unity Catalog, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Snowflake, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from Talend
LeapLogic assesses and transforms diverse Talend code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses ITEM scripts
- Converts jobs and subjobs to:
- Cloud-native ETL: AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from ODI
LeapLogic assesses and transforms diverse ODI code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses XML scripts
- Converts packages and mappings to:
- Cloud-native ETL: AWS Glue Notebook, Databricks Lakehouse/Notebook, Databricks Delta Live Tables, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from SSIS
LeapLogic assesses and transforms diverse SSIS code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses DTSX scripts
- Converts control flows and data flows to:
- Cloud-native ETL: AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from Matillion
LeapLogic assesses and transforms diverse Matillion code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses JSON scripts
- Converts orchestration and transformation jobs to:
- Cloud-native ETL: Amazon Redshift, AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from Pentaho
LeapLogic assesses and transforms diverse Pentaho code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses KJB, KTR scripts
- Converts jobs and transformations to:
- Cloud-native ETL: AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from SnapLogic
LeapLogic assesses and transforms diverse SnapLogic code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses SLP scripts
- Converts pipelines and tasks to:
- Cloud-native ETL: AWS Glue Jobs, AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from
Ab Initio
LeapLogic assesses and transforms diverse Ab Initio code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses KSH, XFR, PLAN, scripts
- Converts ETL graphs to:
- Cloud-native ETL: AWS Glue Studio, AWS Glue Notebook, Databricks Lakehouse/Notebook, etc.
- Cloud-native warehouses: Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
- Converts orchestration scripts and logic from AutoSys, EPS, Cron Shell, Airflow, etc. to target-native equivalent format
- Converts warehouse schema and maps data types for migration to the target platform
Discover the power of smarter, faster transformation from SAS
LeapLogic assesses and transforms diverse SAS analytics scripts, so you can feel the freedom of the cloud quickly, with lower risk of disruption.
- Assesses SAS, EGP scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as base procs, advanced procs, macros, data steps, proc SQLs, etc. and produces actionable insights
- Converts SAS scripts:
- Scripts and procedures
- Macros, scheduler jobs, ad hoc queries
- Data steps, tasks, functions, etc.
- SAS-purposed ETL/statistical/advanced algorithmic logic
- Converts SAS, EGP scripts to:
- Cloud-native stack: AWS Glue Notebook, Databricks Lakehouse/Notebook, Snowflake/Snowpark, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
Discover the power of smarter, faster transformation from Alteryx
LeapLogic assesses and transforms diverse Alteryx code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses YXMC, YXMD, YXWZ scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as Alteryx documents, nodes, macros, queries, entities, functions, expressions, etc. and produces actionable insights
- Converts Alteryx scripts:
- Alteryx scripts
- Macros and tasks
- Alteryx workflows and operations
- Analytics workflows
- Converts Alteryx scripts to:
- Cloud-native stack: AWS Glue Jobs, AWS Glue Notebook, Databricks Lakehouse/Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
Discover the power of smarter, faster transformation from Mainframe
LeapLogic assesses and transforms diverse Mainframe code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses Cobol, JCL scripts
- Converts Cobol and JCL scripts to:
- Cloud-native stack: Databricks Lakehouse/Notebook, AWS Glue Notebook, Amazon EMR, Azure HDInsight, Google Dataproc, etc.
- Open collaboration–based languages: PySpark, etc.
Discover the power of smarter, faster transformation from Sqoop
LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assessment of jobs running on the Hadoop platform - Hive, Impala, Presto, Spark, MapReduce, Oozie, and Sqoop
- Report resource utilization, duration, and frequency of occurrences
- Identify unique workloads and queries
- Classify workloads into processing, ingestion, and orchestration workloads
- Storage analysis of the source Hadoop platform
- Data temperature analysis by classifying data into hot, warm, cold, and frozen categories based on access
- Hive table detailed analysis
- Migration inventory creation for all unique workloads
- Complexity classification of workloads
- Classification of workloads to rehost, refactor and rebuild categories based on target technology mapping
- Actionable recommendations for target technology – Amazon EMR, Redshift, Databricks, Azure Synapse, GCP Dataproc, BigQuery, Snowflake, etc.
- Assessment of SQL artefacts – Scripts and queries for Hive SQL, Impala, Presto, and Spark SQL
- Assessment of Code artefacts - MapReduce, Spark, Oozie, and Sqoop
- Workload auto conversion and migration to target native equivalent using intelligent and pattern-based transformation
- Automated data-based validation of transformed code
- Validation support for a limited sample as well as full historic volumes
- Row and cell-level query validation
- Detailed validation report with success and failure counts and failure details
- Operationalizes workloads
- End-to-end target-specific executable package
- Optimal price-performance ratio
- Parallel run execution enablement, production deployment, and support
Discover the power of smarter, faster transformation from Spark
LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assessment of jobs running on the Hadoop platform - Hive, Impala, Presto, Spark, MapReduce, Oozie, and Sqoop
- Report resource utilization, duration, and frequency of occurrences
- Identify unique workloads and queries
- Classify workloads into processing, ingestion, and orchestration workloads
- Storage analysis of the source Hadoop platform
- Data temperature analysis by classifying data into hot, warm, cold, and frozen categories based on access
- Hive table detailed analysis
- Migration inventory creation for all unique workloads
- Complexity classification of workloads
- Classification of workloads to rehost, refactor and rebuild categories based on target technology mapping
- Actionable recommendations for target technology – Amazon EMR, Redshift, Databricks, Azure Synapse, GCP Dataproc, BigQuery, Snowflake, etc.
- Assessment of SQL artefacts – Scripts and queries for Hive SQL, Impala, Presto, and Spark SQL
- Assessment of Code artefacts - MapReduce, Spark, Oozie, and Sqoop
- Workload auto conversion and migration to target native equivalent using intelligent and pattern-based transformation
- Automated data-based validation of transformed code
- Validation support for a limited sample as well as full historic volumes
- Row and cell-level query validation
- Detailed validation report with success and failure counts and failure details
- Operationalizes workloads
- End-to-end target-specific executable package
- Optimal price-performance ratio
- Parallel run execution enablement, production deployment, and support
Discover the power of smarter, faster transformation from Impala
LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assessment of jobs running on the Hadoop platform - Hive, Impala, Presto, Spark, MapReduce, Oozie, and Sqoop
- Report resource utilization, duration, and frequency of occurrences
- Identify unique workloads and queries
- Classify workloads into processing, ingestion, and orchestration workloads
- Storage analysis of the source Hadoop platform
- Data temperature analysis by classifying data into hot, warm, cold, and frozen categories based on access
- Hive table detailed analysis
- Migration inventory creation for all unique workloads
- Complexity classification of workloads
- Classification of workloads to rehost, refactor and rebuild categories based on target technology mapping
- Actionable recommendations for target technology – Amazon EMR, Redshift, Databricks, Azure Synapse, GCP Dataproc, BigQuery, Snowflake, etc.
- Assessment of SQL artefacts – Scripts and queries for Hive SQL, Impala, Presto, and Spark SQL
- Assessment of Code artefacts - MapReduce, Spark, Oozie, and Sqoop
- Workload auto conversion and migration to target native equivalent using intelligent and pattern-based transformation
- Automated data-based validation of transformed code
- Validation support for a limited sample as well as full historic volumes
- Row and cell-level query validation
- Detailed validation report with success and failure counts and failure details
- Operationalizes workloads
- End-to-end target-specific executable package
- Optimal price-performance ratio
- Parallel run execution enablement, production deployment, and support
Discover the power of smarter, faster transformation from Hive
LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assessment of jobs running on the Hadoop platform - Hive, Impala, Presto, Spark, MapReduce, Oozie, and Sqoop
- Report resource utilization, duration, and frequency of occurrences
- Identify unique workloads and queries
- Classify workloads into processing, ingestion, and orchestration workloads
- Storage analysis of the source Hadoop platform
- Data temperature analysis by classifying data into hot, warm, cold, and frozen categories based on access
- Hive table detailed analysis
- Migration inventory creation for all unique workloads
- Complexity classification of workloads
- Classification of workloads to rehost, refactor and rebuild categories based on target technology mapping
- Actionable recommendations for target technology – Amazon EMR, Redshift, Databricks, Azure Synapse, GCP Dataproc, BigQuery, Snowflake, etc.
- Assessment of SQL artefacts – Scripts and queries for Hive SQL, Impala, Presto, and Spark SQL
- Assessment of Code artefacts - MapReduce, Spark, Oozie, and Sqoop
- Workload auto conversion and migration to target native equivalent using intelligent and pattern-based transformation
- Automated data-based validation of transformed code
- Validation support for a limited sample as well as full historic volumes
- Row and cell-level query validation
- Detailed validation report with success and failure counts and failure details
- Operationalizes workloads
- End-to-end target-specific executable package
- Optimal price-performance ratio
- Parallel run execution enablement, production deployment, and support
Discover the power of smarter, faster transformation from Oozie
LeapLogic assesses and transforms diverse Hadoop workloads, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assessment of jobs running on the Hadoop platform - Hive, Impala, Presto, Spark, MapReduce, Oozie, and Sqoop
- Report resource utilization, duration, and frequency of occurrences
- Identify unique workloads and queries
- Classify workloads into processing, ingestion, and orchestration workloads
- Storage analysis of the source Hadoop platform
- Data temperature analysis by classifying data into hot, warm, cold, and frozen categories based on access
- Hive table detailed analysis
- Migration inventory creation for all unique workloads
- Complexity classification of workloads
- Classification of workloads to rehost, refactor and rebuild categories based on target technology mapping
- Actionable recommendations for target technology – Amazon EMR, Redshift, Databricks, Azure Synapse, GCP Dataproc, BigQuery, Snowflake, etc.
- Assessment of SQL artefacts – Scripts and queries for Hive SQL, Impala, Presto, and Spark SQL
- Assessment of Code artefacts - MapReduce, Spark, Oozie, and Sqoop
- Workload auto conversion and migration to target native equivalent using intelligent and pattern-based transformation
- Automated data-based validation of transformed code
- Validation support for a limited sample as well as full historic volumes
- Row and cell-level query validation
- Detailed validation report with success and failure counts and failure details
- Operationalizes workloads
- End-to-end target-specific executable package
- Optimal price-performance ratio
- Parallel run execution enablement, production deployment, and support
Discover the power of smarter, faster transformation from Tableau
Experience end-to-end transformation, operationalization, and transitioning of reporting workloads with zero business disruption.
- Assesses TDS, TWB scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as data sources, sets, dashboards, worksheets, visualizations, columns, actions, filters, entities, etc. and produces actionable insights
- Converts Tableau dashboards and worksheets to:
- Cloud-native stack: Amazon QuickSight
- Converts orchestration logic to the target-native equivalent
Discover the power of smarter, faster transformation from OBIEE
Experience end-to-end transformation, operationalization, and transitioning of reporting workloads with zero business disruption.
- Assesses XML and SQL scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as business models, subject areas, schemas, calculation measures, aggregations, dashboards, publisher models, presentation/logical/physical tables, filters, agents, etc. and produces actionable insights
- Converts subject areas, criteria, views, and dashboards to:
- Cloud-native stack: Power BI, Amazon QuickSight
- Converts orchestration logic to the target-native equivalent
Discover the power of smarter, faster transformation from Cognos
Experience end-to-end transformation, operationalization, and transitioning of reporting workloads with zero business disruption.
- Assesses XML files
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as reports, pages, visualizations, visualization objects, calculated columns, queries, columns, filters, entities, etc. and produces actionable insights
- Converts IBM Cognos reports and pages to:
- Cloud-native stack: Power BI
- Converts orchestration logic to the target-native equivalent
Discover the power of smarter, faster transformation from AutoSys
LeapLogic assesses and transforms diverse AutoSys code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses AutoSys orchestration scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as jobs, jobs types, conditions, commands, etc. and produces actionable insights
- Converts AutoSys orchestration scripts to Databricks Workflows, Airflow
Discover the power of smarter, faster transformation from Control-M
LeapLogic assesses and transforms diverse Control-M code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses Control-M orchestration scripts
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as jobs, associated application, conditions, job frequency, etc. and produces actionable insights
- Converts AutoSys orchestration scripts to Databricks Workflows, Airflow
Discover the power of smarter, faster transformation from Snowflake
LeapLogic assesses and transforms diverse Snowflake code formats, so you can feel the freedom of the cloud quickly, with lower risk of disruption
- Assesses Snowflake DML scripts, SnowSQLs, etc.
- Produces extensive interdependencies between the workloads
- Identifies extensive inventory such as jobs, views, queries, tables, procedures, etc. and produces actionable insights
- Converts SnowSQLs and procedures to:
- Cloud-native stack: Databricks Lakehouse/Notebook
- Converts orchestration scripts and logic to the target-native equivalent
Meet your accelerated migration to AWS
With LeapLogic, your transformation to AWS will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ 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?
- ETL
- Will the assessment help me choose AWS-native services for meeting ETL SLAs?
- Data warehouse
- Can I get schema optimization recommendations for distribution style and dist keys, sort keys, etc.?
- 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 Amazon 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:
- ETL to AWS stack migration – AWS Glue, Amazon Redshift, PySpark
- Data warehouse to AWS stack migration – Amazon EMR, Amazon Redshift, Snowflake on AWS, Databricks on AWS
- 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
- ETL – Provisioning of AWS Glue and other required services
- Data warehouse – Provisioning of Amazon EMR/Amazon EC2/Amazon Redshift/Snowflake, and other AWS services for orchestration, monitoring, security, etc.
- 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
Meet your accelerated migration to Azure
With LeapLogic, your transformation to Azure will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ Assessment
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Azure-native services (for data processing and storage, orchestrating, BI/reporting etc.)?
- Will I know which workloads can benefit from HDInsight vs. Synapse analytics platform?
- Can I save provisioning and maintenance costs for rarely used workloads on Azure?
- Data warehouse
- Can I get schema optimization recommendations for distribution style, indexing techniques, partitioning, etc.?
- ETL
- Will the assessment help me choose Azure services for meeting ETL SLAs?
- Analytics
- Will it be beneficial to convert my analytical functions to Spark libraries or some native Azure functions?
- Will my ETL processing SLAs impact my choice of an optimum Azure HDInsight cluster size?
- Hadoop
- Is my optimization strategy for Update/Merge on Azure Synapse apt?
- Can I get schema optimization recommendations for distribution style, indexing techniques, partitioning, etc.?
/ transformation
- Packaging and orchestration using Azure-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – Azure Databricks, Azure HDInsight, Azure Synapse, Snowflake on Azure
- ETL – Azure Data Factory, Azure Synapse, PySpark
- Analytics – Azure HDInsight, PySpark
- BI/Reporting – Azure Power BI
- Hadoop – Azure Synapse, 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 ADLS/HDInsight/Synapse, and other Azure services for orchestration, monitoring, security, etc.
- ETL – Provisioning of Azure Data Factory and other required services
- Analytics – Provisioning of Azure HDInsight and other required services
- BI/Reporting – Provisioning of Power BI
- Hadoop – Provisioning of Synapse and other required services
Meet your accelerated migration to Google Cloud
With LeapLogic, your transformation to Google Cloud will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ Assessment
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Google Cloud-native services (for data processing and storage, orchestrating, analytics, etc.)?
- Can I save provisioning and maintenance costs for rarely used workloads on Google Cloud?
- Data warehouse
- Can I get schema optimization recommendations for partitioning, clustering, etc.?
- ETL
- Will the assessment help me choose Google Cloud services for meeting ETL SLAs?
- Analytics
- Will it be beneficial to convert my analytical functions to Spark libraries or some native Google Cloud functions?
- Will my ETL processing SLAs impact my choice of an optimum Dataproc cluster size?
- Hadoop
- Is my optimization strategy for Update/Merge on BigQuery apt?
/ transformation
- Packaging and orchestration using Google Cloud-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – BigQuery, Dataproc, Snowflake on Google Cloud, Databricks on Google Cloud
- ETL – Cloud Data Fusion, Dataflow, Dataproc, PySpark
- Analytics – Google Cloud Dataproc, PySpark
- Hadoop – BigQuery, Snowflake on Google Cloud, 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
- 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 Dataproc/BigQuery/Snowflake, and other Google Cloud services for orchestration, monitoring, security, etc.
- ETL and analytics – Provisioning of Cloud Data Fusion, Dataflow, Dataproc and other required services
- Hadoop – Provisioning of BigQuery/Snowflake on Google Cloud and other required services
Meet your accelerated migration to Snowflake
With LeapLogic, your transformation to Snowflake will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ Assessment
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Snowflake-native services (for data processing and storage, orchestrating, analytics, BI/reporting, etc.)?
- What should be the optimum auto-scaling rule for my Snowflake cluster based on my reporting needs?
- Can I save provisioning and maintenance costs for rarely used workloads on Snowflake?
- Data warehouse
- Can I get schema optimization recommendations for partitioning, clustering, and more?
- ETL
- Will my ETL processing SLAs impact my choice for an optimum Snowflake cluster size?
- 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 apt for Snowflake?
- Can I get schema optimization recommendations for partitioning, clustering, and more?
/ transformation
- Packaging for and orchestration using Snowflake-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – Snowflake
- ETL – Snowflake
- Analytics – Snowpark on Snowflake
- Hadoop – Snowflake, 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
- 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 Snowflake and other AWS services for orchestration, monitoring, security, etc.
- ETL – Provisioning of Snowflake and other required services
- Analytics – Provisioning of Snowflake and other required services
- BI/Reporting – Provisioning of Snowflake
- Hadoop – Provisioning of Snowflake and other required services
Meet your accelerated migration to Databricks
With LeapLogic, your transformation to Databricks will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ Assessment
- Get answers 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/Google Cloud, PySpark
- Hadoop to Databricks migration – Databricks Lakehouse on AWS/Azure/Google Cloud, 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
Meet your accelerated migration to Spark
With LeapLogic, your transformation to Spark (Hadoop) will happen faster, with more accuracy, thanks to superior analysis, automation, and validation
/ Assessment
- Get answers to key questions
- Can I identify anti-patterns in my existing code and resolve as per Hadoop’s coding techniques and standards?
- Will I know if I can meet my SLAs through Spark 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 Hadoop cluster size?
- Analytics
- Will it be beneficial to convert my analytical functions to Spark ML-based libraries?
- How can I accurately transform my legacy analytical models?
- How can I effectively transform thousands of conditional statements, macros, complex statistical and algorithmic logic to the new target service maintaining/enhancing the precision of the model?
/ transformation
- Packaging and orchestration using Hadoop-native wrappers
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – Hadoop (Spark SQL and HQL), Python/Scala/Java
- ETL – Hadoop (Spark SQL and HQL), Python/Scala/Java, Amazon EMR/Azure HDInsight/Dataproc
- Analytics – Hadoop (Spark SQL and HQL)
/ validation
- Pipeline-based automated validation
- Auto-generation of reconciliation scripts
- Cell-to-cell validation reports
- Data type and entity-level matching
- File to file validation
- Assurance of data and logic consistency and parity in the new target environment
/ operationalization
- Optimal cost-performance ratio
- Productionization and go-live
- Infrastructure as code
- Execution using cloud-native orchestrators
- Automated DevOps including CI/CD, etc.
- Target environment stabilization
- Smooth cut-over
Please choose at least one specific source or destination
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Explore real results
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
CASE STUDY
50% cost and time savings when transforming Informatica workflows and Oracle EDW to AWS
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