EDW to Snowflake: Know The Best Transformation Approach


The legacy data warehouses come with a host of limitations, propelling enterprises to look forward to advanced methodologies. With the advent of cloud-based data warehouses, scalability and performance issues  are  significantly resolved, leading to more fruitful outcomes.

One of the most sought-after cloud-based data warehouses, Snowflake, has been substantially contributing to the improved scenarios. With advantages like complete SQL support alongside serverless framework and strengthened connection with Business Intelligence and various ETL tools, Snowflake has been at the forefront of the business digital transformation.

No matter what the book says, the migration from a traditional data warehouse to a cloud-based warehouse, prominently Snowflake, poses a wide variety of challenges including progression of numerous ETL/ELT jobs, redundancy of the legacy environment, difficulty in the recognition of optimal components of the cloud architecture, data validation, etc. These challenges must be dealt with utmost diligence for a successful Snowflake migration.

This is where Impetus Snowflake Workload Transformation Solution comes into play. Developed by Impetus Technologies, this solution encapsulates everything needed to streamline your Snowflake transformation process and make it hassle-free.

Major advantages of leveraging Snowflake Workload Transformation Solution by Impetus:

·         Provides configuration-driven mapping from the legacy data warehouse to the cloud-based data warehouse

·         Facilitates effective DDL conversions from source database to Snowflake

·         Offers you the option to view DDL conversions

·         Helps source business logic as well as scripts

·         Enables automatic transference of an enormous amount of data in just 12-20 weeks' time

The Snowflake Workload Transformation Solution provides the much-needed automated approach besides effective decision support that is data-driven and the required cloud expertise to make your Snowflake migration journey smoother.

A three-step process to accelerate your Snowflake migration process using Snowflake Workload Transformation Solution:

Assessment

This step includes everything ranging from data profiling to recognition of various types of workloads that need to be migrated. It also includes an assemblage of the said workloads into various migration units.

Transformation

In the transformation stage, automated data migration happens. This encompasses varied procedures particular to data types, intervals, UDFs, etc. Moreover, formation of patterns, including security, data sync, and lineage, is also accomplished at the transformation stage.

Validation and Execution

In the final stage, the auto-generation of reconciliation scripts takes place. Moreover, it facilitates the execution process using the execution engine and furthers legacy data decommissioning.

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