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Get the data-powered advantage

Becoming a data-powered organization requires a strong data foundation – one that unites the enterprise and unlocks timely, accurate, and relevant insights – to drive real outcomes.

In the digital world, data makes the difference between success and stagnation. Data-powered organizations are 22% more profitable, and have twice the market capitalization rate, as their data-lagging counterparts. But becoming a data-powered organization is an enterprise-wide challenge that must be embraced by all parts of the business.

Capgemini helps organizations build their data foundation, enhancing, expanding, and advancing their existing data capabilities with powerful accelerators, frameworks, methodologies, and best practices gathered from decades of experience by our market-leading Insights & Data team.

Collaborative Data Ecosystems

The new tectonic shift in data is sharing.

Becoming a data-powered organization requires imagination. Our team of data engineers helps your organization envision and execute the data foundation that will help your business get the future you want.

    890 by Capgemini

    Data-powered decisions, delivered with confidence.

    IDEA by Capgemini

    The key to your data-powered organization.

      What we do

      Embrace the potential of artificial intelligence (AI) by transforming the way you are doing business, engaging with your clients and employees, and building a better society.

      Our data and AI strategy helps companies address the most critical requirements to fully utilize data, analytics, and AI for competitive advantage, market impact, and business results.

      Our offer focuses on four key areas to help clients craft a comprehensive, multifaceted data strategy, establish a scalable and sustainable data foundation, and ensure that their data, analytics, and AI fabric is agile, durable, and secure:

      1. Data and AI mobilization
      2. Data-powered innovation
      3. AI and analytics scaling
      4. Data and AI academy

      There’s no intelligence without data, at scale. These foundation services create modern data and AI platforms to deliver trusted AI solutions in production and at scale.

      Master Data Management (MDM)

      Our Master Data Management services provide the frameworks, accelerators and solutions you need to create a centralized information hub that avoids typical point-to-point integration of different applications. 

      MDM is a cloud-based solution powered by machine learning and AI. We help you harmonize the scattered and inconsistent master data gathered from all your internal data assets into a ‘single version of the truth – bringing a clear, consistent understanding of the data across your entire organization. 

      Data Estate & BI Modernization

      With the support of people, processes, and technology, our Data Estate and BI Modernization approach helps organizations transform their relationship with data.

      In a world where continuous, rapid change is the norm, where hybrid multi-cloud context is mainstream, we create with you an industrialized and secure data estate, and the data fabric, that supports the level of business innovation you need to remain a market leader.

      Industrialized Data & AI Engineering Acceleration (IDEA)

      Industrialized Data & AI Engineering Acceleration (IDEA) from Capgemini helps organizations turn their data sprawl into a valuable strategic asset.

      It’s time to rethink AI and analytics: from proof of concept to source of value. A functional asset to foundational capability. An experiment to an enabler.

      The true value of AI and Analytics cannot be realized from individual proofs of concept, but their at-scale deployment across business functions, units, and geographies.

      As an end-to-end transformation partner, we work with clients to develop the methodology, framework, and environment to enable large-scale, production-grade intervention and deploy AI and Analytics at scale.

      Our robust service offering and underlying business transformation capabilities address every aspect of the AI agenda – from laying a strong data foundation, to selecting the right tools, technology platforms, and agile practices, to establishing balanced operating models and ethical AI algorithms, to cultivating rich talent and partner pools.

      890 by Capgemini

      Data holds infinite possibilities – now is the time to activate its full potential. 890 by Capgemini is available on any cloud, and with a single interface, it puts you at the helm of your data. Data-powered decisions, delivered with confidence.

      The key is finding the data that’s right for you, easily and quickly. By combining an extensive ecosystem of industry-specific, open, and exclusive sources with your own data, we can help you create specific insights that allow you to make key decisions with confidence. Trusted, robust, and curated to your needs, 890 by Capgemini helps clients take their business forward with confidence.

      Machine Learning Operations (MLOps)
      Leverage MLOps to improve quality and robustness, shorten deployment times, and unlock the benefit of sustainable and scalable AI models.

      Organizations need strong support for scaling and industrializing AI/ML models. Capgemini provides a proven framework to stabilize, standardize, and optimize the entire AI/ML journey across popular cloud services, as well as on-premises setups.

      Our MLOps framework, built on the key principles of DataOps and DevOps, offers clients access to reusable templates and pipelines to enable a model ecosystem, a mix of cloud native services and third party/open-source stack for added flexibility, customized model approval workflows for enhanced governance, and extensive plugins to enhance model monitoring.

      Federated learning
      Federated learning provides organizations with a decentralized model training capability. With our cutting-edge approach, models are trained locally and securely, aggregated centrally, and deployed back on edge – all without moving data outside its boundary.

      AI and ML-driven business decisioning provides enormous value to the organization. However, challenges around data security and privacy, as well as the scalability of the platform, are major obstacles to widespread AI/ML adoption.

      Federated learning, along with EDGE AI enablement, helps organizations overcome these challenges. Capgemini’s state-of-the-art Simulation Lab for Federated Learning & Edge Intelligence allows customers to leverage best-in-class FL frameworks to validate thinking and identify optimal use cases as they begin or continue their FL journey.

      Intelligent process automation leverages a unique and differentiating approach that encompasses an end-to-end perspective from ideation to production.

      This enables you to seek guidance on starting an automation journey, scale up operations, enjoy sustainable automation benefits, and pursue capability growth and innovation that benefits from our world-class capability, and vertical and horizontal process experience.

      Client stories

      Expert perspectives

      Data and AI

      Ethical AI – Decoded in 7 Principles

      Zhiwei Jiang
      26 Apr 2021
      Data and AI

      What can AI strategists learn from software development history?

      Padmashree Shagrithaya
      15 Sep 2021

      Meet our experts

      Eric Reich

      Expert in Big Data, Cloud, Enterprise Content Management, IOT

      Dinand Tinholt

      Data & AI Strategy Offer Leader
      “Even while investment levels in data and AI initiatives are increasing, organizations continue to struggle to become data-powered. Many have yet to forge a supportive culture and a large number are not managing data as a business asset. For many firms, people and process challenges are the biggest barriers in activating data across the enterprise.”

      Neerav Vyas

      Head of Customer, Co-Chief Innovation Officer, Insights & Data, North America
      Neerav is an outstanding leader, helping organizations accelerate innovation, drive growth, and facilitate large-scale transformation. He is a two-time winner of the Ogilvy Award for Research in Advertising and an AIconics 2019 and 2020 finalist for Innovation in Artificial Intelligence for Sales and Marketing.

      Mark Oost

      Global Offer Leader – AI Analytics & Data Science
      Prior to joining Capgemini, Mark was the CTO of AI and Analytics at Sogeti Global, where he developed the AI portfolio and strategy. Before that, Mark worked as a Practice Lead for Data Science and AI at Sogeti NetherLands, where he started the Data Science team, and as a (Lead) Data Scientist at Teradata and Experian. Throughout his career, Mark had the opportunity to work with clients from various markets around the world and has used AI, deep learning, and machine learning technologies to solve complex problems.

      Sebastien Guibert

      VP Global Head of Intelligent Automation
      Intelligent Process Automation can help eliminate frictions impacting your data, people, processes, and technology, enabling you to implement data-driven & digitally augmented workforce at scale by combining process automation, AI and process analytics.

      Steve Jones

      Expert in Big Data and Analytics
      ‘Steve is the founder of Capgemini’s businesses in Cloud, SaaS, and Big Data, a published author in journals such as the Financial Times and IEEE Software. He is also the original creator of the first unified architecture for Big Fast Managed data, the Business Data Lake. He works with clients on delivering large-scale data solutions and the secure adoption of AI, he is the Capgemini lead for Collaborate Data Ecosystems and Trusted AI.

      Gianfranco Cecconi

      Director, Data Sharing Acceleration Lead, Capgemini Invent
      “The opportunities that emerge from open data and data sharing are compelling as best practices become mature and more accessible. They are available today in both private and public sectors. Capgemini wants to accelerate the digital transformation process that enables public administrations to play an active role in the data ecosystems they belong to, to become modern, financially sustainable, and socially responsible organizations.”