Big Data Technologies and Applications
33 papers on this topic
Social Network Mining (SNM): A Definition of Relation between the Resources and SNA
Social Network Mining (SNM) has become one of the main themes in big data agenda. As a resultant network, we can extract social network from different sources of information, but the information...
SQL and NoSQL Databases Software architectures performance analysis and assessments -- A Systematic Literature review
Context: The efficient processing of Big Data is a challenging task for SQL and NoSQL Databases, where competent software architecture plays a vital role. The SQL Databases are designed for...
A compendium of data sources for data science, machine learning, and artificial intelligence
Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed...
Big Data Testing Techniques: Taxonomy, Challenges and Future Trends
Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free...
Towards a Generic Multimodal Architecture for Batch and Streaming Big Data Integration
Big Data are rapidly produced from various heterogeneous data sources. They are of different types (text, image, video or audio) and have different levels of reliability and completeness. One of...
Towards Interactive, Adaptive and Result-aware Big Data Analytics
As data volumes grow across applications, analytics of large amounts of data is becoming increasingly important. Big data processing frameworks such as Apache Hadoop, Apache AsterixDB, and Apache...
BigDL: A Distributed Deep Learning Framework for Big Data
This paper presents BigDL (a distributed deep learning framework for Apache Spark), which has been used by a variety of users in the industry for building deep learning applications on production...
Geospatial Big Data Handling with High Performance Computing: Current Approaches and Future Directions
Geospatial big data plays a major role in the era of big data, as most data today are inherently spatial, collected with ubiquitous location-aware sensors. Efficiently collecting, managing,...
Designing and Implementing Data Warehouse for Agricultural Big Data
In recent years, precision agriculture that uses modern information and communication technologies is becoming very popular. Raw and semi-processed agricultural data are usually collected through...
Graceful Forgetting II. Data as a Process
Data are rapidly growing in size and importance for society, a trend motivated by their enabling power. The accumulation of new data, sustained by progress in technology, leads to a boundless...
Caveat emptor: the risks of using big data for human development
Big data revolution promises to be instrumental in facilitating sustainable development in many sectors of life such as education, health, agriculture, and in combating humanitarian crises and...
Big Data application in congestion detection and classification using Apache spark
With the era of big data, an explosive amount of information is now available. This enormous increase of Big Data in both academia and industry requires large-scale data processing systems. A...
A Big Data Analysis Framework Using Apache Spark and Deep Learning
With the spreading prevalence of Big Data, many advances have recently been made in this field. Frameworks such as Apache Hadoop and Apache Spark have gained a lot of traction over the past...
Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud
Clustering big data often requires tremendous computational resources where cloud computing is undoubtedly one of the promising solutions. However, the computation cost in the cloud can be...
Video Big Data Analytics in the Cloud: Research Issues and Challenges
On the rise of distributed computing technologies, video big data analytics in the cloud have attracted researchers and practitioners' attention. The current technology and market trends demand an...
Strategies and Principles of Distributed Machine Learning on Big Data
The rise of Big Data has led to new demands for Machine Learning (ML) systems to learn complex models with millions to billions of parameters, that promise adequate capacity to digest massive...
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved...
Generalized formal model of big data
This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the "big data" term. The article proposes and describes the...