Webinar

Harnessing AI for IoT: Strategies and Technologies for Data Empowerment

Discover how a modern and sustainable approach to AI and IoT, built on principles of context, unification, and flexibility, can empower your business. Learn how companies are leveraging cutting-edge technologies to manage and analyze massive IoT datasets in real time, unlocking intelligent decision-making and operational efficiencies.

Stefan Asanin from CrateDB talking about AI strategies and technologies for IoT

IoT projects remain on the rise as organizations strive to capitalize on the vast amounts of data generated by connected devices to increase operational efficiency, reduce costs, and improve decision-making. At the same time, the scalability and speed required to process and analyze all of that data streaming in from sensors and devices come with many challenges. The need to process data and make decisions in real-time is a major issue. Data quality, security, and privacy are also top concerns.

By providing greater automation, advanced analytics, and increased decision-making capabilities, AI can significantly enhance IoT initiatives in a large number of areas. 

Register now to watch  the recording of a special roundtable webinar and dive into the top trends in modern data architecture for 2025.

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What you will learn

  • How CrateDB serves as a powerful unified data layer specifically designed to manage, process, and analyze massive IoT datasets in real time, overcoming challenges related to data latency, volume, and silos.
  • The critical importance of enriching raw IoT data with contextual information from various sources (historical, structured, unstructured) to fuel meaningful AI-driven decisions, as highlighted by CrateDB.
  • How CrateDB provides a scalable and resilient platform with features like distributed processing, sharding, and standard SQL queries, simplifying data access and integration with existing tools and AI/BI platforms.
  • Real-world examples, such as TGW Logistics' success with CrateDB in accelerating access to large volumes of real-time warehouse data, improving predictive model accuracy, and enabling digital assistants.
  • Key characteristics to look for in a data platform for unifying IoT data for AI, with a focus on functionality, performance, scalability, flexibility, and how CrateDB excels in these areas.