The amount of sensors has grown so much that 20 years ago, computer scientists had to design a new internet protocol foreseeing that the previous would exhaust the amount of connected devices. This is the Internet of Things or IoT world - with sensors connected within the enterprise and publicly creating a wave of noisy, loud, fast, and voluminous data requiring new architectures and patterns in edge computing, cleaning algorithms, storage, notification triggers, and integration solutions.  This is IoT & Sensor Data.

Beyond Big Data, sensor data – remote or IoT, big and/or fast, requires edge and centralized new data flow patterns to trigger the real-time monitoring to support operation and decision making at the data-driven organization.

 

Our clients in transportation and science are leading the way in sensor integration and knowledge products.

Top Solutions

  1. Agile Applicatoin Integration with IoT/Sensor Data and Enhancement (Development)
  2. Real-Time Data Hub Architecture and Development (Design and Dev)
  3. Remote Sensing Large Portfolio Rationalization Tools and Consulting (Strategy)
  4. Real-Time Data Lifecycle Governance Development and Architecture Advisory (Strategy)

Top 5 Challenges IoT Data Face

  1. IoT feeds require both high performance computing and storage solutions to avoid the data lakes turning into data marshes.
  2. Organizations have increasingly started looking at storing big data collected using IoT devices rather than rely on vendors.
  3. IoT devices may provide unstructured data formats, may be dirty, and require edge filtering, adaptive transformation, and other deferred load solution as area matures.
  4. Data hubs are needed to handle IoT, remote sensing, and other massive fast or big feeds.
  5. No current toolsets are available to easily assess the effectiveness of IoT sensor project installation projects.