Journey to the Cloud

Transforming Data Warehouse and analytics to the cloud is a complex task and can go wrong without careful planning.

Key challenges faced by organizations in their Journey to the Cloud:

  • Establishing a fool-proof transformation roadmap and strategy
  • Following an incremental, step-wise approach for transformation
  • Controlling cost overruns
  • Ensuring business continuity and data integrity
  • Ensuring security and governance

Architectural blueprint is defined in  the Journey to the Cloud phase, we do this by selecting the right tools available in a cloud stack that optimize Total Cost of Ownership (TCO), enable real-time capabilities, bring in self-service and minimize efforts.

Once best fit cloud services are put together as a blueprint, then task of cloud transformation begins with a chosen use case.

An incremental approach vis-à-vis a big bang approach will help to feedback the environment specific learnings into the transformation program without any risks or disruption to the business.

Our incremental approach involves using a Minimum Viable Product (MVP) as an important cloud adoption strategy. This acts as the right starting point as it validates the transformation approach and ensures that all specific customizations for maximizing automation are identified and implemented. Post this validation, Amaze™ for Data & AI gets customized to the environment to accelerate the rest of the transformation efforts.

With the learnings and insights from the MVP, a full-fledged transformation of the Data Warehouse, BI and analytics systems will be setup to run in a factory model.

The entire ETL code conversion, database schema transformation, data and reports movement are automated, which reduces time, efforts and cost involved by over 60%.

Through Amaze™ you can automate the transformation from:

  1. On-premise ETLs like Informatica, SSIS, IBM Datastage, SAP BODS to cloud native ETLs like Talend, Azure Data Factory
  2. Legacy Data warehouses and Databases like Teradata, Exadata, Netezza, SQL Server and Oracle DB to cloud platforms like AWS, Azure, GCP, Databricks or Snowflake.
  3. Legacy BI tools like Microstrategy, Crystal reports to platforms like Power BI , Tableau on cloud.

High-impact benefits delivered by Amaze™ for Data and AI include:

  • Over 60% efforts reduction through automation
  • Robust suite of accelerators
  • Automated metadata analysis of ETL, database, and reporting environments
  • Automated conversion of legacy to modern analytics ecosystem
  • Metadata-based data ingestion framework for creating new pipelines for cloud

Reference Use Cases

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