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Data, Analytics & AI CoE

Create the enterprise data and AI engine for your GCC across data engineering, BI, advanced analytics, ML, GenAI, MLOps and governance.

6 Core data, analytics & ai capability areas

3 Integrated delivery layers

4 Knowledge-to-value levers

1 Connected data, analytics & ai knowledge platform

OUR CUSTOMERS

GoodWorks Group, trusted by everyone — Fortune 500 to startups.

OUR TRACK RECORD

GCC Success Stories

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Cyber Security · Singapore Saptharushi Saptharushi India Global Capability Centre (GCC) Read case study →

Automotive · Germany Mercedes-Benz Mercedes-Benz Research & Development India Read case study →

Retail · UK Tesco Tesco Bengaluru Global Capability Centre Read case study →

Automotive · Germany BMW BMW Motorrad India Read case study →

EXPERT COMMITTEE

Data, Analytics & AI CoE Expert Committee

A 6–8 member committee brings together GCC leadership, functional specialists, technology experts and ecosystem perspectives. It provides strategic guidance, validates knowledge outputs and helps keep priority themes current.

Data Leader

Chief Data / Analytics GCC Leader

Brings enterprise data strategy, platform and global capability perspective.

Data Platform

Data Engineering / Platform Head

Validates architecture, data products, quality, observability and platform operations.

Analytics & BI

Analytics / Decision Intelligence Leader

Connects semantic models, BI, advanced analytics and business adoption.

AI & MLOps

ML / GenAI / MLOps Specialist

Brings production models, evaluation, lifecycle governance and responsible AI.

Technology Specialist

Data, Analytics & AI Platform / Architecture Specialist

Brings platform architecture, integration, workflow and automation expertise into the functional operating model.

Controls & Governance

Data, Analytics & AI Governance / Controls Lead

Validates controls, risk, service management and governance themes for scalable global operations.

Academia & Skills

Data, Analytics & AI Skills / Research Representative

Connects role architecture, future skills and capability-development pathways to the CoE.

International SME

Global Data, Analytics & AI Shared Services SME

Provides global benchmark, service-model and transformation perspective across mature GCC and GBS environments.

FUNCTION OVERVIEW

Data, Analytics & AI Capability for Global GCCs in India

Data GCCs are becoming enterprise platforms for trusted data products, analytics, ML and GenAI rather than isolated reporting factories.

The Data, Analytics & AI CoE structures data ownership, platform architecture, analytics product management, model lifecycle and responsible-AI governance into one operating model.

6 Core data, analytics & ai capability areas

3 Integrated delivery layers

4 Knowledge-to-value levers

1 Connected data, analytics & ai knowledge platform

FUNCTION OPERATING LANDSCAPE

Data Product Operating Model

Domain ownership, data contracts, quality and product accountability are central to reusable enterprise data.

Tracked monthly

Lakehouse / Cloud Data Platforms

Architecture, cost, security, observability and integration choices shape scalable data engineering.

Tracked quarterly

BI & Semantic Layer

Metrics, dimensions and semantic consistency determine whether self-service analytics produces trusted decisions.

Tracked monthly

MLOps & Model Governance

Model registry, evaluation, release, monitoring and lineage are required for production ML.

Tracked continuously

GenAI / RAG Governance

Retrieval, embeddings, prompt/version control, evaluation and access to enterprise knowledge need explicit controls.

Tracked monthly

HOW THIS GCC COE DELIVERS VALUE

Knowledge

Data, Analytics & AI research, operating benchmarks, talent themes and priority standards are converted into decision-ready knowledge.

Advisory

Expert Committee guidance validates the capability model, operating choices and priority transformation themes for data, analytics & ai.

Ecosystem

Talent, technology, academic and specialist partner connections help accelerate data, analytics & ai capability building in India.

Accelerator Kit

Reusable blueprints, role maps, governance patterns and implementation playbooks reduce time spent designing the data, analytics & ai model from scratch.

FUNCTION SNAPSHOT

Data, Analytics & AI GCC Capability Snapshot

Core Capability Areas

Data / AI capability domains

Governance / lifecycle levers

Integrated Delivery Layers

Capability-structure indicators for the CoE model. Enterprise-specific market and workforce metrics are validated during the engagement.

THE CHALLENGE WE SOLVE

What modern Data, Analytics & AI teams need to solve

Data, Analytics & AI teams need a coherent global operating model, trusted data, clear controls and the right automation choices before scale creates complexity.

Data Ownership Is Unclear

Pipelines fail to create value when domains, quality accountability and product ownership are missing.

Metric Inconsistency

Teams cannot trust analytics when KPI definitions differ across dashboards and business units.

Platform Cost & Complexity

Multiple data tools, clouds and duplicate pipelines can increase cost faster than data value.

Models Stall Before Production

ML and GenAI pilots fail without deployment, monitoring, evaluation, ownership and support.

Responsible AI & Access Risk

Enterprise data and model outputs need access, privacy, safety and human-use controls.

OUR SERVICES — END-TO-END OR MODULAR

Build the right Data, Analytics & AI capability

Use the complete GCC lifecycle or select the strategy, setup, talent, technology, governance and transformation modules required for this mandate.

Data & AI Strategy

Use-case portfolio, data domains, platform and operating model.

Data Platform Engineering

Lakehouse/warehouse, ingestion, transformation and observability.

Data Product Model

Ownership, contracts, quality, metadata and domain interfaces.

BI & Analytics

Semantic layer, dashboards, self-service and advanced analytics.

ML / GenAI Engineering

Models, RAG, agentic workflows and applied AI.

MLOps & Governance

Evaluation, registry, release, monitoring, lineage and risk controls.

Talent & Leadership

Data engineering, analytics, ML, platform and AI product roles.

Capability Development

Data, GenAI, cloud, analytics and responsible-AI upskilling.

HOW WE DELIVER

Three integrated layers

A common delivery model connects validated knowledge to setup, capability building, scale and ongoing optimisation.

01 / KNOWLEDGE

Knowledge & Expert Committee

Sector or functional research, operating intelligence, talent context, technology benchmarks, regulatory updates and reusable reference material.

02 / SETUP & BUILD

Setup & Build

Entity, workspace, talent, technology, compliance and operating-model setup aligned to the CoE mandate.

03 / GROWTH

Growth & Optimisation

Mandate expansion, capability upgrades, leadership development, health diagnostics and ongoing transformation advisory.

DOMAIN COVERAGE

What the Data, Analytics & AI CoE Covers

The CoE structures six core data, analytics & ai capability areas into a reusable GCC operating and transformation model.

Data Engineering

Data platforms pipelines lakehouse enterprise data products

Business Intelligence

Semantic models dashboards self-service analytics reporting

Advanced Analytics

Forecasting optimization experimentation decision science

Machine Learning

Applied ML predictive models production AI use cases

Generative AI

RAG copilots LLM applications enterprise AI assistants

MLOps & Governance

Deployment observability evaluation security responsible AI

ENGAGEMENT CADENCE

A repeatable rhythm of knowledge exchange

The model combines focused CoE activity with cross-ecosystem forums so knowledge stays current and actionable.

Per CoE — Semi-Annual Activity

Focused roundtables, working sessions and knowledge exchanges around the most material capability topics.

Annual Flagship Forum

A cross-CoE forum connecting enterprise leaders, experts, ecosystem partners and emerging capability themes.

KNOWLEDGE REPOSITORY

What the Aerospace GCC CoE Publishes

A structured repository of reports, benchmarks, trackers, public snapshots and expert-led publications keeps the CoE knowledge layer current and practical.

QUARTERLY INTELLIGENCE

Data, Analytics & AI GCC Landscape Brief

Quarterly view of capability signals, operating trends, talent demand and material developments affecting data, analytics & ai GCC leaders.

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BENCHMARK

Data, Analytics & AI Capability & Talent Benchmark

Role families, skill priorities, maturity indicators and operating benchmarks for planning and scale decisions.

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PLAYBOOK

Data, Analytics & AI CoE Operating Playbook

Reusable governance, process, service-model and implementation patterns for enterprise teams.

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FUNCTION OVERVIEW

Data, Analytics & AI GCC Snapshot

Public high-level overview of the data, analytics & ai capability landscape, priority themes and India operating considerations.

View freely - no registration

WHITEPAPER

Data, Analytics & AI Strategy for India GCCs — 2026

Research-led perspective on building, scaling and transforming data, analytics & ai capability in India.

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EXPERT BRIEFING

Data, Analytics & AI Expert Committee Briefing

Periodic expert-led briefing on material capability, talent, technology, governance and transformation themes.

View briefing details

ECOSYSTEM

Enterprise, academic and technology connections

The CoE connects capability leaders to the broader network required to establish, operate, scale and transform in India.

Enterprise & Industry

GCC and GBS leadership
Domain and functional specialists
Industry associations and peer networks

Academia & Research

Universities and research institutions
Specialist talent pipelines
Applied research and knowledge partnerships

Technology & Innovation

Technology platform specialists
Start-up and innovation ecosystem
International SMEs and benchmark networks

TECHNOLOGY PLATFORM

Data, Analytics & AI CoE AI Knowledge Assistant

Developed and maintained by Sansovi GCC, the assistant gives enterprises instant access to current, India-specific information sourced from the GCC CoE knowledge repository.

Sector-specific opportunities in India

Talent availability by vertical and role

Universities and research institutions

Government initiatives and infrastructure

Policy FAQs and investment environment

Events and ecosystem activities

GCC landscape and benchmarks

India's GCC ecosystem overview

Functions solely as an informational resource, never as legal, financial or regulatory advice.

Data, Analytics & AI CoE AI Knowledge Assistant interface

FREQUENTLY ASKED QUESTIONS

Common questions about Data, Analytics & AI CoE

Quick answers to the questions GCC leaders typically ask when evaluating this capability in India.

How is a Data & AI CoE different from a BI team?+

It owns more of the data lifecycle: platforms, data products, quality, semantic models, analytics, ML/GenAI, MLOps and governance.

What should be centralised vs federated?+

Platform engineering, standards and governance often centralise well; domain data-product ownership may remain federated with common contracts and controls.

What causes analytics distrust?+

Inconsistent metrics, weak master data, missing lineage and unclear ownership are common causes.

What should be in an MLOps baseline?+

Versioned data/code/model artefacts, evaluation, registry, controlled deployment, monitoring, rollback, lineage and support ownership.

How can Sansovi support Data & AI CoE setup?+

Support can cover operating model, specialist talent, platform setup, governance, AI assurance and capability development.

Ready to build your Centre of Excellence?

Whether you're establishing a new GCC capability, expanding an existing shared-services function, or moving toward AI-led intelligent operations — Sansovi GCC can help you assess, build and scale the right model.

Talk to a Sansovi GCC Specialist Explore all 26 CoEs