LTI Canvas PolarSled
Every few decades, a disruptive technology shakes up the fundamentals of its market. Snowflake is one of such a game-changer that irrevocably altered the landscape of Data Management solutions for analytics. We followed an amplified services approach by augmenting Snowflake practitioners at LTI with tools, utilities and frameworks. This has been driven by our flagship portfolio, branded LTI Canvas PolarSled.
LTI Canvas PolarSled platform addresses the core challenges of designing, accelerating, and governing a data transformation journey to cloud. It provides a complete playbook encompassing migration strategy, automated migration and post migration governance to enable the Snowflake’s cloud data platform adoption.
LTI Canvas PolarSled
LTI Canvas PolarSled platform enables simplified & mindful migration to Snowflake’s cloud data platform, which helps in addressing the key challenges of being on-time & in-budget. It helps to steer through the complexity during the transition to Snowflake’s cloud data platform and eliminate embedded legacy platform’s technical debt.
Speed Expediting cloud journey from years to months, with automation-first approach
Performance Future-ready Snowflake’s cloud data platform with reduced technical-debt.
Reduced Risk De-risk migration with key guiding principles, proven best practices, and automation.
Technology strategy & consulting to help define the Snowflake migration & data strategy to cloud
- Platform Fitment Evaluation
- Assessment and Roadmap Definition
- Architecture definition
End to-end implementation/migration toolkit to Snowflake’s cloud data platform, for wing-to-wing, automation-led implementation/migration powered by ML-based automation tools
- Data Architecture Implementation
- Data Migration and Code Migration
- Data Validation and Tuning
Governance toolkit to help sustain and optimize the new Snowflake’s cloud data platform along with operations management
- DataOps on Snowflake
- Platform & Application Optimization
Solutions & Accelerators
Analysis of the data table and views to get a view of the existing data landscape and the technical debt associated with it
Migrates source database schema into Snowflake schema in an automated process. Additional feature inclusion/ exclusion of table
View migration from on-premise DB into Snowflake view in an automated process along with naming the data elements
Migrate incumbent database SQL queries to corresponding snowflake queries
Analyze data stored in Snowflake to identify cold/warm data which can be moved to external tables for cost optimization
Spark-based ingestion framework for migrating and processing data from on-premise DB to Snowflake
Automation tool to validate data between source and target post-migration
Identify potential security gaps in snowflake implementation like nonsecure views, objects created by account admin, etc.
Analyze and report potential inefficient cost consumption patterns e.g. long-running queries, high-cost virtual warehouses, idle resources, etc.
Knowledge Bot for sharing and amplifying Snowflake knowledge within an organization
Ensure a certified level of data quality with the help of pre-built business rules
Sustain and optimize overall Snowflake DW performance based on the queries run to achieve high performance and better cost saving