IDEA by Capgemini

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INDUSTRIALIZE YOUR DATA & AI ESTATE MODERNIZATION JOURNEY

Through a modular design and platform-as-code, IDEA by Capgemini provides organizations with a flexible and customizable approach to data estate modernization. IDEA by Capgemini delivers a clear, fast, and scalable path from innovation to industrialization, shrinking the data estate modernization timeline while enabling enterprise-wide AI & analytics adoption to accelerate business value.

Idea on Snowflake (AWS)

Idea on Snowflake (Azure)

Services

Industrialized Data & AI Engineering Acceleration is a suite of accelerators, frameworks, methodologies, best practices, and implementation guidance for Data Estate Modernization projects.

Discovery & Complexity Analysis Service

Teradata and Snowflake landscape is discovered with the use of metadata information and presented with user friendly dashboards at overview and granular levels.

Schema, User & Role Migration

Teradata warehouse objects like Tables, Views, User and Roles are migrated to Snowflake compatible objects.

Data Migration

Data Migration support from various sources to Snowflake through various options(Batch/Incremental/Adhoc) are supported with ABCR services for data validation and reconciliation.

ETL Code Migration

AI powered semantic parsing engine to convert BTEQs, Stored procedures to compatible Snowflake SQL and python executables.

Data Ingestion

Support ingestion of data from various sources and modes primarily batch/streaming/CDC/Snowpipe/Kafka-Connect/Glue etc

Data Processing

Data processing is supported with the usage of DBT/Snowflake Copy/Snowpipe/Stream/Tasks

Data masking and Data Sharing

Supports Data Masking with rules and policies implementation and with support of UDFs. Direct and Indirect Data Sharing is supported as well.

Snowflake AI/ML

Model, Build, Train and Deploy of AI/ML are supported with Snowpark and AWS/Azure Notebook Integration.

IDEA Offerings

Design for Industrialization

Service Benefits

Quick turnaround.

New connectors can be built as per the need to cover more sources due to a very scalable and agile architecture

Use of Cloud specific native services for the job

Quick notification on the success and failure of data migration service.

Code analyzer to provide the current landscape of code in the source side

Code analyzer to provide the current landscape of code in the source side.

Low Code No Code Data Pipeline creation.

With LCNC orchestration modules developers can drag and drop components on the canvas and easily build the data flows in the pipeline and generate DAGs with a click of a button.

Rich analytics powered by AI

Rich analytics powered by artificial intelligence (AI) and machine learning (ML) to amplify business intelligence.

Microservices Governance

Leverage microservices to benefit from flexibility, scalability, and bring new apps and services to market faster.

Minimize cost, risk, and disruption

Lower total cost of ownership (TCO) with consumption-based pricing and improved resource management with reduced risk, robust data protection, digital security, and compliance. .

Data-driven decision

Agile scalability and flexibility to respond to changing demands and avoid disruptions with greater access and democratization of data to enable data-driven decision making across the enterprise.

Idea on Snowflake