# The Role of Big Data Analytics in Industrial Internet of Things

## TL;DR

This paper reviews how big data analytics enhances industrial IoT systems by classifying existing research, presenting frameworks and case studies, and discussing future challenges and opportunities.

## Contribution

It provides a comprehensive taxonomy of BDA technologies in IIoT and highlights recent developments, frameworks, and case studies in the field.

## Key findings

- BDA enables operational and customer insights in IIoT.
- Frameworks and case studies demonstrate BDA benefits in enterprises.
- Identifies key challenges and future research directions in BDA for IIoT.

## Abstract

Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage resources at IoT device-end. Big data analytics (BDA) is expected to provide operational- and customer-level intelligence in IIoT systems. Although numerous studies on IIoT and BDA exist, only a few studies have explored the convergence of the two paradigms. In this study, we investigate the recent BDA technologies, algorithms and techniques that can lead to the development of intelligent IIoT systems. We devise a taxonomy by classifying and categorising the literature on the basis of important parameters (e.g. data sources, analytics tools, analytics techniques, requirements, industrial analytics applications and analytics types). We present the frameworks and case studies of the various enterprises that have benefited from BDA. We also enumerate the considerable opportunities introduced by BDA in IIoT.We identify and discuss the indispensable challenges that remain to be addressed as future research directions as well.