“The global data migration market is projected to grow to $11.49 billion in 2022 with a compound annual growth rate (CAGR) of 17.5%.”- Datamation
Be it your organization is adapting to the new normal or starting up a new business, you need to deal with huge data regardless of your line of business. Legacy data platforms such as Oracle demands huge infrastructure maintenance, rigid licensing terms, upcharges for hardware & software counterparts, a highly skilled workforce, and much more. In addition, Oracle requires additional OLAP counterparts to harness the data for analytics.
To halt this chaos, organizations are now shifting to leading modern data landscapes like Snowflake to establish matured data models with streaming solutions. While migrating from Oracle to Snowflake, businesses choose to reengineer the entire data landscape or retain the legacy business logic in Snowflake based on their needs. On the whole, the goal is to win the competitive marketplace with a data-driven business model.
Evaluate the Oracle databases, schemas, objects, data sources, data pipelines, processes & toolsets and orchestrate them in an architecture diagram.
Document their job schedules, process dependencies, connection strings, and configuration guidelines.
Analyze their development and deployment process.
Explore roles, users, accessibility permissions, frequency of patches, and other maintenance operations in Oracle.
In this blog post, we showcase how our data engineers establish Oracle to Snowflake migration strategy!
Deciding on Key factors to establish a migration strategy
Depending on the existing data warehouse architecture and business needs, we connect Snowflake platform to the data sources in two different approaches.
In this approach, we create a replica of Oracle SQL packages in SnowSQL. Then, by utilizing the connectors and drivers, we establish data source integration to Snowflake platform.
If your enterprise already leverages third-party integration tools like Informatica, Talend, Azure Data Factory, and Databricks, we recommend retaining them to establish the connection to Snowflake platform.
Our data engineers rationalize the data models by considering the future architecture. We categorize the future data models as:
Refactoring data model
Requires reengineering to comply with Snowflake platform.
Retaining data model
Migrated as-is to the Snowflake platform.
With this rationalization, our team showcases the clear picture of efforts required to attain the future Snowflake architecture to the executive team of your enterprise.
Based on the size of existing data warehouse, we discuss with the executive team and define the historical data load approach. We are flexible with online and offline historical data loads.
Loading historical data by leveraging cloud data migration services and connecting periodically to synchronize source datasets till cutover.
Loading historical data by utilizing AWS Snowball/Azure Databox/Google Transfer Appliance and planning for incremental loads till cutover.
Our team brainstorms with the executive team and plans for Oracle cutover. We categorize the legacy data warehouse cutover as:
Big bang migration
Complete data migration with planned downtime for live systems.
Data migration in phases with parallel runtime of Oracle and Snowflake platform.
By considering all these factors, our data architects develop a custom migration strategy for your enterprise Snowflake migration.
With the existing architecture and inventory, our team prioritizes datasets and pipelines based on process dependencies. Further, we document these process dependencies to identify the ongoing changes throughout the migration. We capture these ongoing changes with automated job schedules to cut off rudimentary efforts.
Our team assesses the availability of resources and requirements of reengineering to attain the future data model in the Snowflake platform to set achievable deadlines. Your executive team can have business expectations and our team would figure out ways to establish realistic deadlines through consecutive brainstorming sessions.
Our team is ready with a Snowflake pricing estimator to assess the estimated annual cost based on the number of minutes a warehouse is expected to run each day and the number of days the warehouse is expected to run each week. Based on the data warehouse sizing and the number of compute clusters required during and post-migration, we can help you in concluding the budget planning for the Oracle to Snowflake migration.
Our team determines the success factors in the Snowflake migration by discussing with the executive team. In addition, we document these expected outcomes, and benefits of Snowflake migration to validate the future data architecture.
Some of the common success factors of our clients were
Upon concluding the desired outcomes in Snowflake migration, our team ideates the possible solutions to achieve the future architecture. As a proof-of-concept, we take primary data sources and create data pipelines to Snowflake platform. With this proof-of-concept, we identify the defined patterns that migrate the source data structures to Snowflake platform and design the migration framework.
By executing the migration framework, we iterate and load the historical data to Snowflake platform effortlessly with minimal sprints.
Our team steps forward to present the MVP for the primary source system of your enterprise. By leveraging the migration framework, we bring in the datasets from source touchpoints to Snowflake platform and BI tools. Further, we validate and present this MVP to the executive team to communicate the benefits of migrating to Snowflake platform.
Being a trusted Snowflake partner, with years of industry excellence and customer journey, we can architect a custom Snowflake migration strategy for your business needs. From unveiling your legacy data platform to migrating & optimizing your modern data landscape with matured data models, our team delivers an end-to-end cloud data strategy solution. We’re ready with migration accelerators across the data lifecycle from ingestion to analytics for seamless data platform modernization.
Let’s get over the call and build a personalized data migration strategy for your organization! Talk to us today!
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