We migrate your data from legacy systems, on-premise servers and obsolete data warehouses to modern cloud platforms like Snowflake and Databricks, with detailed migration plans, exhaustive integrity validation and zero data loss. We reduce infrastructure costs, improve analytical performance and leave your data platform ready to scale with artificial intelligence.
Cloud Data Migration with Snowflake and Databricks
At MiT Software we specialize in migrating data infrastructures to Snowflake and Databricks, the two most widely adopted cloud data platforms by leading companies worldwide. Our migration methodology guarantees complete data integrity, business continuity throughout the process and a controlled transition that minimizes operational risk. We migrate from any source: Oracle, SQL Server, Teradata, on-premise Hadoop, Amazon Redshift, Google BigQuery, SAP BW or any existing data warehouse or data lake. The result is a modern, scalable data platform with significantly superior analytical performance and optimized infrastructure costs compared to the previous system.
We start with a detailed inventory of the source system: tables, volumes, dependencies, existing pipelines, connected applications and business criticality of each component. This inventory is the basis of the migration plan, which defines the order, phases, timelines and success criteria for each migrated component.
We define the complete architecture in the target platform: database organization, role and permissions model, warehouse or cluster configuration, network security, connectivity with existing systems and integration with the BI and ML tools that will consume the migrated data.
We develop the complete migration tooling: ETL/ELT scripts for data extraction and loading, SQL conversion tools for dialect adaptation, validation scripts for integrity testing and orchestration pipelines that automate and monitor the entire migration process.
We execute the migration in controlled phases, starting with the least critical components and progressively moving to the most important ones. Each phase includes an exhaustive validation before moving on to the next, ensuring that no phase advances until the quality and integrity of the previously migrated data are confirmed.
We execute the final cutover with minimum maintenance window, redirecting all applications and users to the new platform in a coordinated and controlled manner. During the first days after cutover, we provide intensive monitoring support to quickly detect and resolve any incident that may arise.
Once the new platform is stable and validated, we coordinate the controlled decommissioning of the legacy system and perform a post-migration optimization review that identifies additional opportunities to reduce costs and improve query performance in the new environment.
On-premise data warehouses require significant investments in hardware, licenses and specialized personnel for maintenance and updates. Moving to Snowflake or Databricks eliminates those fixed costs, replaces them with a pay-per-use model and provides virtually unlimited scalability without capacity planning.
Snowflake and Databricks are designed from scratch for cloud-scale analytical workloads. Their distributed architectures, automatic caching and query optimization allow running complex analytical queries over billions of records in seconds, compared to the minutes or hours that legacy systems require for equivalent queries.
Snowflake is the leading cloud data platform for organizations that need a highly performant, secure and easy-to-operate data warehouse. We manage the complete migration: schema conversion, data migration, pipeline adaptation, security configuration and team training for autonomous platform management.
Databricks is the ideal platform for organizations that need to combine large-scale data analytics with machine learning and AI. We manage the migration of data warehouses, data lakes and ML pipelines to Databricks, implementing the Lakehouse architecture that unifies analytics and AI on a single platform.
We have specialized experience in migrating from the most common enterprise data warehouse systems to Snowflake or Databricks: SQL dialect conversion, stored procedure migration, view and function adaptation, and performance optimization of the migrated queries to take advantage of the cloud architecture.
We migrate Hadoop ecosystems — HDFS, Hive, Spark, HBase, Impala — to cloud equivalents in Snowflake or Databricks, preserving the existing data processing logic and eliminating the complexity and cost of operating a Hadoop cluster on-premise.
Every migration we perform includes an exhaustive data integrity validation process: record counting at each stage, checksum comparison, statistical validations of key metrics and functional testing of the main queries and reports that depend on the migrated data.
Migration is the ideal opportunity to optimize the data model: normalize or denormalize schemas according to the access patterns of the new platform, eliminate redundancies, improve partitioning strategies and adapt the physical design to maximize analytical performance in Snowflake or Databricks.
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