Modeling Data Analytics Architecture for Smart Cities Data-Driven Applications using DAT

TL;DR

This paper discusses developing a Data Analytics Architecture for smart city applications using model-driven engineering and DAT to transform raw data into meaningful insights.

Contribution

It introduces a novel Data Analytics Architecture framework tailored for smart cities, leveraging model-driven engineering and DAT for efficient data processing.

Findings

Successful implementation of DAA in smart city scenarios

Enhanced data management and analysis capabilities

Improved visualization of city data insights

Abstract

Extracting valuable insights from vast amounts of information is a critical process that involves acquiring, storing, managing, analyzing, and visualizing data. Providing an abstract overview of data analytics applications is crucial to ensure that collected data is transformed into meaningful information. One effective way of achieving this objective is through Data Architecture. This article shares our experiences in developing a Data Analytics Architecture (DAA) using model-driven engineering for Data-Driven Smart Cities applications utilizing DAT.