Improving data management with ThingWorx: a Cloud-based solution in the Industrial IoT landscape

The Internet of Things (IoT) has revolutionized the way data is collected, making it possible to create networks of connected devices and sensors to gather data from both objects and the environment. This work aims to study the impact of this technology in an industrial context, analyzing not only the role of data processing in supporting strategic decisions to improve the competitiveness of companies and optimize their processes, but also the architectural aspects involved in effective data management. In particular, the thesis discusses the topic by addressing three main aspects: market trends, enabling tools and architectures, and the relevance of IoT platforms to streamline an effective data management, allowing the integration with those tools that support the different activities involved in managing data, from its collection to its processing and visualization. It provides a comprehensive overview of two implementation approaches, using edge and cloud computing paradigms respectively, discussing their characteristics and the challenges that may arise when dealing with large and distributed IoT solutions, especially in mission-critical systems. To support the discussion on the most effective architectural approach for IIoT data management, the paper presents a business case that leverages ThingWorx, a centralized, cloud-based IoT platform for ingesting, integrating and analyzing Accenture clients' operational data. By discussing the potential of IoT platforms, this thesis explores some strategies for managing IoT data, highlighting its potential to enhance competitiveness in the ever-changing technological environment.