IoT Analytics

Unlock the true potential of your IoT data with our IoT analytics services. We employ advanced analytics techniques, including machine learning and artificial intelligence, to extract valuable insights from vast amounts of IoT-generated data. Our team of data scientists and analysts helps you discover patterns, trends, and correlations, enabling you to make informed business decisions, optimize operations, and drive innovation. From predictive maintenance and demand forecasting to customer behavior analysis, our IoT analytics solutions empower you to stay ahead of the competition in today's data-driven world.

We provide full-cycle implementation services, which comprise:

• Business analysis

Our BA team will analyze your analytics needs, translate them into a feature set, carry out a feasibility study taking into account the capabilities of the existing data analytics solution, if you have one implemented, as well as consider legal, regulatory, and security requirements to create a detailed requirements specification.

• Dashboard design

Our UI/UX designers will create an optimal dashboard layout that clearly reflects trends, patterns, and dependencies derived from the IoT data, adapting the displayed content to relevant use roles.

• Architecture design and development

Designing and developing IoT analytics solutions we focus on consistency, reliability and flexibility. At this stage, our database team will:

• Design and implement a data lake for storing sensor data.
• Design and implement a big data warehouse for a well-tuned management of sensor data and metadata (e.g., the data about sensor locations, calibrations and maintenance). Also, our data engineers will implement ETL processes for a range of data sources, such as ERP, MES, WMS, and others, to create a consolidated data management and analytics solution.
• Implement BI, reporting and visualization tools for deriving insights from the historical and real-time sensor data and conveying the insights in the form of predefined and ad-hoc reports.
• Implement a machine learning component to power the solution with predictive analytics capabilities.