KPMG’s Data & AI practice works with enterprises in all sectors to optimize and monetize data. On-premises, in private clouds, or hosted in cloud-provider centers, our solutions and services range from end-to-end infrastructures, through data strategy and migration, to data research. 

Design & Architecture

We help you process vast amounts of data so that you can best navigate your business – if it's on Cloud or on-premise. We build the architecture to process real time, data, structured & unstructured data from social media, IoT devices, and other channels. We setup data lakes ready for consumption by different systems. Working with innovative tools like Elasticsearch, Confluent, Databricks/Spark on top of on-premise servers or on leading cloud vendors platforms. 

Model Development

Predictive models, NLP, machine learning, artificial intelligence, behavior, analytics, and sentiment analysis are not buzzwords for KPMG’s experts. We put emerging technologies to work building real-life models that detect fraud, analyze relationship patterns, measure customer lifetime value, or pinpoint cross-sell incentives. We help you monetize your data and grow your business.

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Data Strategy and Assessment

KPMG provides a wide range of data-strategy and assessment services to organizations that do not have a clear picture of how to utilize and leverage their data or want to obtain more valuable and actionable insights. Our professionals analyze your organization’s current state, needs, and objectives, and plan the optimum data-transformation journey. 

Data Migration

Whether you are planning a full/partial migration of some applications’ data, a large IT estate, or from paper to data with computer vision models - our migration services enable you to achieve agility and integrate more easily with your ecosystem.

Why KPMG’s Data and IA?

  • Business-first approach backed by expert knowledge of data technologies
  • Global network of experts and alliances across a rich technology landscape
  • Intelligent models, new technologies, in-depth knowledge of data issues
  • Technological and strategic knowhow to optimize data pipelines & ML models