IoT Analytics Architectures: Challenges, Solution Proposals and Future Research Directions

Architecting Data-Driven Applications: From Architectural Design to the Data Quality

“…Effective DA is essential for advanced data analytics, business intelligence, and arti-1.3. Need For Data Architecture ficial intelligence applications [124]. It allows organizations to extract valuable insights from their data, make data-intensive decisions, and stay ahead of the competition in today's data-intensive world [92] [14].…”

“…Analytics architectures are the systems and technologies used to collect, store, process, and analyze data to gain insights and make data-driven decisions [124]. These architectures typically involve using distributed computing systems, such as clusters of servers or cloud-based platforms, to handle the processing and storage of data.…”

“…Big Data analytics (BDA) is the process of analyzing the massive raw data by data scientists to uncover unidentified relationships and associations, market trends, and valuable information to make business decisions [92] [14] [124]. Business intelligence (BI) is more focused and refers to the technologies, applications, and practices used to gather, store, access, and analyze data to help them make more informed business decisions.…”

Tapis v3 Streams API: Time‐series and data‐driven event support in science gateway infrastructure

“…The rise of IoT devices, instruments, and sensors in recent years has lead to a demand for support of storing, processing, and analyzing time‐series data. Further, as more ML and AI systems are developed and come online, the need for re‐enforcement data and datasets that can be leveraged for training as well as input for driving events is increasing 1 …”