Data Lake Overview

Break down silos and enhance fleet operations with a unified scalable data platform

The Data Lake is the backbone of IrisX. Build specifically for construction and machine data. Trackunit uses this data architecture to power our applications and now we enable customers to leverage the functionality. The power of Data lake is integrating and normalizing telematics data to be used in the other capabilities in IrisX, such as Apps, Analytics, AI and Automation.

IrisX Data Lake is the perfect solution for organizations aiming to build a secure, scalable, and flexible data infrastructure that supports a wide range of analytics and machine learning applications.

IrisX Data Lake

Use Cases

  • Integrate and normalize telematics data for comprehensive performance monitoring and advanced analytics.
  • Transform data into actionable insights with encrypted transmission, ensuring reliability.
  • Handle large data volumes and support advanced analytics and machine learning.

Features & Capabilities

  • Prepopulated with your Trackunit operating data: All your telematics data with full resolution and the entire time series history. All data continuously updated, cleaned, harmonized, and aligned – and ready for use in AI, LLMs, and ML models.
  • Broad Data Ecosystem Support: Seamlessly integrates with IrisX Analytics, leveraging its powerful processing capabilities. The Data Lake offers integration options with high volume data access APIs and SQL querying. It can be integrated with other data warehousing and data lake technogies as part of a federated data architecture.
  • Scalable Data Handling and Efficient Data Storage: Designed to be robust and scalable, capable of handling diverse environments and scaling as per business needs. Manage metadata efficiently, allowing for rapid reads and writes without performance degradation, suitable for large datasets.

The Data Lake's secure architecture ensures storing of large quantities of reliable and encrypted data. Customers can build their own data lake on IrisX or integrate it with existing infrastructure.