Guide To Migrate Data Warehouse To Snowflake

Modernizing your data infrastructure is no longer a choice but a necessity. If you still run on-premise or hybrid data warehouses, it’s time to switch to the Snowflake AI DATA Platform. It is the ultimate solution modern businesses require to combine workloads and unify data on the cloud. Not only does it simplify the scaling efforts to support legacy databases, but it also makes data pipeline troubleshooting much more manageable and smoother. Whether you’re battling the complexity of data management or require the flexibility to scale your data processing operations, it’s time to migrate your data warehouse to Snowflake. Here is a complete data migration to Snowflake blueprint that will help you to get started!

Why Migrate Data Warehouse To Snowflake?

Migrating your data warehouse to Snowflake unlocks a wealth of advantages that traditional on-premises or hybrid systems simply can’t match! 

• Single Platform Accessibility: The Snowflake platform allows you to unify your data workloads and receive support for business intelligence and advanced analytics.
• Consumption-Based Pricing: Pay only for what you use with per-second billing without wasting your resources.
• Broad Language Support: No need to switch between platforms as you can work with SQL, Python, Java, and Scala on the unified platform altogether.
• Supports All Data Formats: Snowflake integrates seamlessly with varied architecture patterns, such as data lakes, data warehouses, and hybrid models.
• Fully-Managed Operations: Snowflake handles cloud provisioning with high availability without your intervention.
• Elastic Scalability: Instantly scale compute and storage independently to handle any workload, whether for a single user or a massive job.
• Migration Support: Snowflake offers tailored solutions for migrating data from legacy systems and platforms. It supports migration from on-premises systems like Teradata, Oracle, and Hadoop. You can migrate to cloud platforms like AWS Redshift, BigQuery, and Spark.

Organizations migrating their Data Warehouse to Snowflake can leverage the platform’s incredible capabilities to simplify cloud-native data management and operations.

When To Consider A Migration To Snowflake? Pre-Migration Assessment

The first step in migrating to Snowflake is to thoroughly assess the existing data warehouse and its architecture. Conduct a thorough review of your current data warehouse by finding answers to these questions:

• Is my current warehouse delivering speedy analytical performance?
• Am I struggling to manage workloads efficiently?
• Can my current platform scale seamlessly with demand?
• How easily can I share data across teams and systems?
• Am I paying for unused capacity, or are there any hidden costs?

Answering these questions will help you pinpoint gaps in your existing ETL processes and data warehouse setup. It’s time to initiate data migration to Snowflake and align your migration strategy with the Snowflake platform. 

Read: Data Warehouse Design Guide

Define The Migration Scope & Align With A Suitable Migration Strategy

A successful migration to Snowflake begins with understanding the data volume involved, whether terabytes or petabytes. This helps estimate the storage and computing requirements needed for seamless operations on Snowflake. You must set realistic timelines for the migration and allocate capable resources for execution. Always prioritize business continuity by minimizing disruptions and maintaining operations throughout migration. 

Snowflake supports different data migration strategies depending on the complexity and timeline. You must finalize a data migration strategy that suits your database architecture. To prioritize critical data, choose the “lift-and-shift” method or an “incremental migration” approach. Another option is to re-engineer or redesign the data architecture using Snowflake platform features like micro-partitioning and zero-copy cloning.

Steps To Initiate Data Migration To Snowflake

Now you have a data migration strategy with a team ready for execution; you must encourage them to follow a step-wise approach to keep it clean and error-free!

Set Up Snowflake Account

Before migration, you need a Snowflake account and an appropriate configuration. Sign up for Snowflake and choose your cloud provider from the available options. You can create Snowflake warehouses with computing resources and databases to house the migrated data. It will allow you to configure Snowflake roles and permissions to secure data access.

Perform Data Extraction From Legacy Warehouse

Next, you must extract old data from legacy on-premises warehouses and data lakes. You can use database export tools or data extraction scripts to maintain data quality. Always monitor whether the data exportation is clean and consistent. You can capture the schema definitions and table structures beforehand to maintain consistency in Snowflake after migration.

Schema Conversion and Data Loading

Snowflake supports several methods for loading data and securing schema conversion. The Snowflake Schema Conversion Tool can convert the legacy schema to a suitable format. You can map legacy data types and foreign keys with those compatible with Snowflake. Next, you can load data using Snowpipe, which automatically shifts your data from cloud storage (AWS S3, Azure Blob Storage, or GCP Cloud Storage) into Snowflake tables. If you have large data sets, you can do bulk loading.

Complete Data Transformation

In Snowflake, transformation is handled using SQL-based transformations. You can recreate any views or stored procedures from the legacy warehouse and adjust them per Snowflake’s syntax. You can optimize data modeling and re-engineer your ETL pipelines by rewriting SQL scripts. For detailed information, get in touch with our data warehouse consultants.

Data Validation To Cutover And Go-Live

After loading the data, you must perform rigorous validation and testing to ensure data integrity. Keep comparing record counts and data samples between both systems and execute different business queries to verify that performance matches expectations. Once you validate the data, you can perform the final sync to migrate the data warehouse to Snowflake.

Migrate Your Legacy Systems To Snowflake With Ksolves

Break free from the limitations of legacy systems with Ksolves Snowflake migration solutions. Snowflake is the ultimate cloud-native platform to unify workloads for modern data management. Ksolves data migration solutions enable you to stay stress-free as the migration experts plan the entire execution roadmap on your behalf!

Our Snowflake Consulting services include comprehensive data assessments and migration strategy planning. With expertise in zero-copy cloning and multi-cloud support, Our team of 500+ experts helps you optimize costs and drive actionable insights. So, what are you waiting for? Shake hands with us for an amazing migration journey that eliminates data silos and transforms your operations. Let us guide you in migrating to Snowflake, a platform designed to grow your business!