The Power of Time Series Data in IoT | InfluxData's Evan Kaplan | Internet of Things Podcast

IoT For All Podcast · 28 Jan 2025 · 16m · Episode 368

What this episode covers

Evan Kaplan, CEO of InfluxData, explains that time series data is the foundational language of IoT, representing timestamped telemetry from sensors that enables the transition from monitoring to autonomous systems. He details the specific engineering challenges of managing this data, including high ingestion rates, cardinality explosion, and the need for immediate read/write capabilities in operational contexts. Kaplan highlights InfluxData's architecture, which optimizes for these three pillars, and discusses the emerging trend of integrating time series data with machine learning to build self-perfecting, intelligent physical systems like self-driving cars and smart grids.

Mentioned

Companies
InfluxData, Tesla, iPass, SonicWall, Dell
Products
InfluxDB, Powerwall
Also
Oracle, Informix, MySQL, Cassandra, Apache Data Fusion, Fluentd, Telegraf

Other shows on the same ground, closest first.

  • The Robot Report Podcast · 1h 06m

    Unlocking the Power of Time Series Databases for Industrial and Robotic Systems

    Doug Pagnutti, Developer Advocate at Tiger Data, explains how TimescaleDB, a PostgreSQL extension for time series data, helps robotics developers manage high-volume telemetry, spatial, and multimodal data. He details strategies for edge-to-cloud data synchronization, the use of continuous aggregates and compression to handle fleet-scale data, and integrating with industrial tools like Ignition and MQTT. The conversation also covers the emerging need for hybrid search stacks to combine temporal data with vector embeddings for AI-driven maintenance and fleet optimization.

  • Over the Air · 20m

    The Future of IoT Revealed: Inside Samsara's Data Revolution with Evan Welbourne

    Evan Welbourne, Head of AI and Data at Samsara, discusses the evolution of IoT from a distinct technology to an invisible infrastructure, emphasizing that the real value lies in data analytics and edge computing. He details Samsara's pivot from a temperature sensor to a vehicle gateway, highlighting how thermal constraints in AI dash cams drive hardware design decisions. The conversation explores the future of neuromorphic computing, data ownership in connected devices, and the rise of edge AI for real-time safety insights.

  • Over the Air · 30m

    Implementing a Winning IoT Strategy at the Enterprise Level with Josh Becker of SAS

    Josh Becker, Senior Global Director and Head of IoT Commercial at SAS, discusses the evolution of analytics from batch processing to real-time AI-driven insights. He shares his background in reliability engineering at Sub-Zero Wolf, where he built one of the earliest IoT devices to monitor refrigerators remotely. Becker explains how SAS leverages event stream processing and computer vision to solve enterprise problems, from defect detection in manufacturing to predicting utility asset failures through partnerships like the one with Exactor.

  • Over the Air · 48m

    IoT Data: Using Smart Tech to Outsmart Analog Competitors

    Sean Grundy, Co-Founder & CEO of Bevi, explains how the company uses IoT data to manage field operations, predict maintenance, and drive product improvements, setting it apart from analog competitors. He details the mechanical engineering challenges of inline carbonation and shares lessons learned from early hardware failures, such as the lack of systematic breakdown tracking. Grundy also discusses strategic decisions regarding core competencies, outsourcing non-core functions like firmware and door manufacturing, and the importance of choosing the right contract manufacturer partners for startups.

  • Moore's Lobby · 56m

    Sensors Insights: Bridging Hardware Collection and Software Analysis

    Nils Beckmann, Director of Engineering for Intelligent Automation at Emerson, discusses the convergence of hardware and software in industrial IoT. He explains that while sensors are the critical data source, the primary challenge is bridging the skill gap between hardware engineers who lack software knowledge and software engineers who misunderstand physical constraints. Beckmann advises starting with simple monitoring of existing sensors to establish baselines before attempting complex predictive maintenance, emphasizing that repeatability is often more valuable than high accuracy for analytics.

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by IoT For All Podcast. The episode itself belongs to its publisher.