Analytics over large-scale multidimensional data: the big data revolution!
Alfredo Cuzzocrea,Il-Yeol Song,Karen C. Davis +2 more
- pp 101-104
TLDR
This paper provides an overview of state-of-the-art research issues and achievements in the field of analytics over big data, and extends the discussion to Analytics over big multidimensional data as well, by highlighting open problems and actual research trends.Abstract:
In this paper, we provide an overview of state-of-the-art research issues and achievements in the field of analytics over big data, and we extend the discussion to analytics over big multidimensional data as well, by highlighting open problems and actual research trends. Our analytical contribution is finally completed by several novel research directions arising in this field, which plays a leading role in next-generation Data Warehousing and OLAP research.read more
Citations
More filters
Journal ArticleDOI
Big Data computing and clouds
Marcos Dias De Assuncao,Rodrigo N. Calheiros,Silvia Cristina Sardela Bianchi,Marco A. S. Netto,Rajkumar Buyya +4 more
TL;DR: This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications, and identifies possible gaps in technology and provides recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions.
Journal ArticleDOI
Social big data
TL;DR: This paper presents a revision of the new methodologies that are designed to allow for efficient data mining and information fusion from social media and of thenew applications and frameworks that are currently appearing under the “umbrella” of the social networks, socialMedia and big data paradigms.
Journal ArticleDOI
Big data analytics: a survey
Chun-Wei Tsai,Chin-Feng Lai,Han-Chieh Chao,Han-Chieh Chao,Han-Chieh Chao,Athanasios V. Vasilakos +5 more
TL;DR: The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data.
Book ChapterDOI
Big Data Analytics: A Literature Review Paper
Nada Elgendy,Ahmed Elragal +1 more
TL;DR: This paper aims to analyze some of the different analytics methods and tools which can be applied to big data, as well as the opportunities provided by the application of big data analytics in various decision domains.
Journal ArticleDOI
Understandable Big Data
TL;DR: This survey tackles semantics (reasoning, coreference resolution, entity linking, information extraction, consolidation, paraphrase resolution, ontology alignment) in the Big Data context.
References
More filters
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This paper presents the implementation of MapReduce, a programming model and an associated implementation for processing and generating large data sets that runs on a large cluster of commodity machines and is highly scalable.
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This presentation explains how the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
Journal ArticleDOI
Scalable SQL and NoSQL data stores
TL;DR: This paper examines a number of SQL and socalled "NoSQL" data stores designed to scale simple OLTP-style application loads over many servers, and contrasts the new systems on their data model, consistency mechanisms, storage mechanisms, durability guarantees, availability, query support, and other dimensions.
Proceedings ArticleDOI
Hive - a petabyte scale data warehouse using Hadoop
Ashish Thusoo,Joydeep Sen Sarma,Namit Jain,Zheng Shao,Prasad Chakka,Ning Zhang,Suresh Antony,Hao Liu,Raghotham Murthy +8 more
TL;DR: Hive is presented, an open-source data warehousing solution built on top of Hadoop that supports queries expressed in a SQL-like declarative language - HiveQL, which are compiled into map-reduce jobs that are executed using Hadoops.
Journal ArticleDOI
HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads
TL;DR: This paper explores the feasibility of building a hybrid system that takes the best features from both technologies; the prototype built approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce-based systems.