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The area of Learning Analytics has developed enormously since the first International Conference on Learning Analytics and Knowledge (LAK) in 2011. It is a field that combines different disciplines such as computer science, statistics,…

Learning analytics is a research topic that is gaining increasing popularity in recent time. It analyzes the learning data available in order to make aware or improvise the process itself and/or the outcome such as student performance. In…

The landscape of analytics is changing rapidly. Much of online user analytics, however, is based on collection of various user analytics numbers. Understanding these numbers, and then relating them to higher numerical analysis for the…

This paper gives a systematic research review at the boundary of the information systems (IS) and marketing disciplines. First, a historical overview of these disciplines is given to put the review into context. This is followed by a…

Urban analytics combines spatial analysis, statistics, computer science, and urban planning to understand and shape city futures. While it promises better policymaking insights, concerns exist around its epistemological scope and impacts on…

Data analytics and data science play a significant role in nowadays society. In the context of Smart Grids (SG), the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this paper, we…

Software Analytics (SA) is a new branch of big data analytics that has recently emerged (2011). What distinguishes SA from direct software analysis is that it links data mined from many different software artifacts to obtain valuable…

The main aim of this paper is to provide a deep analysis on the research field of healthcare data analytics. This paper is analyzing the previous studies and works in this research area, as well as highlighting some of guidelines and gaps.…

The application of Data Science and Analytics to optimize or predict outcomes is Ubiquitous in the Modern World. Data Science and Analytics have optimized almost every domain that exists in the market. In our survey, we focus on how the…

There has been a significant increase in the development of data-driven safety analytics approaches in recent years. In light of these advances it has become imperative to evaluate such approaches in a principled way to determine their…

Gaining profound insights from collected data of today's application domains like IoT, cyber-physical systems, health care, or the financial sector is business-critical and can create the next multi-billion dollar market. However, analyzing…

Research in operations management has traditionally focused on models for understanding, mostly at a strategic level, how firms should operate. Spurred by the growing availability of data and recent advances in machine learning and…

Sports analytics -- broadly defined as the pursuit of improvement in athletic performance through the analysis of data -- has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this…

Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization. To better identify which research topics are promising and to learn how to apply relevant techniques in visual…

Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for research and application. This work explores the theoretical…

While manufacturers have been generating highly distributed data from various systems, devices and applications, a number of challenges in both data management and data analysis require new approaches to support the big data era. These…

The literature on fraud analytics and fraud detection has seen a substantial increase in output in the past decade. This has led to a wide range of research topics and overall little organization of the many aspects of fraud analytical…

The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. However, humans do not possess the cognitive capabilities to…

Informatics and technological advancements have triggered generation of huge volume of data with varied complexity in its management and analysis. Big Data analytics is the practice of revealing hidden aspects of such data and making…

Open datasets play a crucial role in three research domains that intersect data science and education: learning analytics, educational data mining, and artificial intelligence in education. Researchers in these domains apply computational…