Review on Big Data & Analytics – Concepts, Philosophy, Process and Applications

Abstract Big Data analytics has been the main focus in all the industries today. It is not overstating that if an enterprise is not using Big Data analytics, it will be a stray and incompetent in their businesses against their Big Data enabled competitors. Big Data analytics enables business to take proactive measure and create a competitive edge in their industry by highlighting the business insights from the past data and trends. The main aim of this review article is to quickly view the cutting-edge and state of art work being done in Big Data analytics area by different industries. Since there is an overwhelming interest from many of the academicians, researchers and practitioners, this review would quickly refresh and emphasize on how Big Data analytics can be adopted with available technologies, frameworks, methods and models to exploit the value of Big Data analytics.

[1]  Gonzalo Mateos,et al.  Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge , 2014, IEEE Signal Processing Magazine.

[2]  Ian T. Foster,et al.  An in-memory based framework for scientific data analytics , 2016, Conf. Computing Frontiers.

[3]  Le Minh Nguyen,et al.  Text analytics in industry: Challenges, desiderata and trends , 2016, Comput. Ind..

[4]  Melanie Swan,et al.  Philosophy of Big Data: Expanding the Human-Data Relation with Big Data Science Services , 2015, 2015 IEEE First International Conference on Big Data Computing Service and Applications.

[5]  C. K. Jha,et al.  MapReduce: Simplified Data Analysis of Big Data , 2015 .

[6]  Cees T. A. M. de Laat,et al.  Defining architecture components of the Big Data Ecosystem , 2014, 2014 International Conference on Collaboration Technologies and Systems (CTS).

[7]  Alexandra Roatis,et al.  CLAMS: Bringing Quality to Data Lakes , 2016, SIGMOD Conference.

[8]  Lars Rönnbäck,et al.  Big Data normalization for massively parallel processing databases , 2017, Comput. Stand. Interfaces.

[9]  Manuele Kirsch-Pinheiro,et al.  The 6th International Conference on Ambient Systems, Networks and Technologies (ANT 2015) Context-Aware Scheduling for Apache Hadoop over Pervasive Environments , 2015 .

[10]  Klaus Meyer-Wegener,et al.  Speaking in tongues: SQL access to NoSQL systems , 2014, SAC.

[11]  Sugam Sharma,et al.  Expanded cloud plumes hiding Big Data ecosystem , 2016, Future Gener. Comput. Syst..

[12]  Der-Jiunn Deng,et al.  Real-time big data analytics for multimedia transmission and storage , 2016, 2016 IEEE/CIC International Conference on Communications in China (ICCC).

[13]  Ravikiran Vatrapu,et al.  Social Set Analysis: A Set Theoretical Approach to Big Data Analytics , 2016, IEEE Access.

[14]  Songlin Hu,et al.  QMapper: a tool for SQL optimization on hive using query rewriting , 2013, WWW '13 Companion.

[15]  Joseph M. Hellerstein,et al.  MAD Skills: New Analysis Practices for Big Data , 2009, Proc. VLDB Endow..

[16]  Fred Popowich,et al.  Mixed-Initiative for Big Data: The Intersection of Human + Visual Analytics + Prediction , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[17]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[18]  Ishwarappa,et al.  A Brief Introduction on Big Data 5Vs Characteristics and Hadoop Technology , 2015 .

[19]  Feras Batarseh,et al.  Assessing the Quality of Service Using Big Data Analytics: With Application to Healthcare , 2016, Big Data Res..

[20]  Daniel Pakkala,et al.  Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems , 2015, Big Data Res..

[21]  Sai Peck Lee,et al.  Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: A review, classifications, and open issues , 2016, J. Syst. Softw..

[22]  J. Manyika.  Big data: The next frontier for innovation, competition, and productivity , 2011 .

[23]  Reinhard Klein,et al.  A visual analytics perspective on shape analysis: State of the art and future prospects , 2015, Comput. Graph..

[24]  X. Zhu,et al.  iCARE: A framework for big data-based banking customer analytics , 2014, IBM J. Res. Dev..

[25]  E. A. Mary Anita,et al.  A Survey of Big Data Analytics in Healthcare and Government , 2015 .

[26]  K. P. Soman,et al.  Apache Spark a Big Data Analytics Platform for Smart Grid , 2015 .

[27]  Chun-I Chen,et al.  A Hyperconnected Manufacturing Collaboration System Using the Semantic Web and Hadoop Ecosystem System , 2016 .

[28]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[29]  Davide Anguita,et al.  Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf , 2015, INNS Conference on Big Data.

[30]  Laila Niedrite,et al.  Accelerating data queries on Hadoop framework by using compact data formats , 2016, 2016 IEEE 4th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE).

[31]  Andrew Schwarz,et al.  Examining the Impact of Multicollinearity in Discovering Higher-Order Factor Models , 2014, Commun. Assoc. Inf. Syst..

[32]  Rajeshwari M. Goudar,et al.  Notice of Violation of IEEE Publication PrinciplesA Speedy Data Uploading Approach for Twitter Trend and Sentiment Analysis Using HADOOP , 2015, 2015 International Conference on Computing Communication Control and Automation.

[33]  Hugh J. Watson,et al.  Tutorial: Big Data Analytics: Concepts, Technologies, and Applications , 2014, Commun. Assoc. Inf. Syst..

[34]  David Loshin.  Chapter 7 – Big Data Tools and Techniques , 2013 .

[35]  Gabriel Antoniu,et al.  Enabling fast failure recovery in shared Hadoop clusters: Towards failure-aware scheduling , 2017, Future Gener. Comput. Syst..

[36]  Shicong Meng,et al.  Bigprovision: a provisioning framework for big data analytics , 2015, IEEE Network.

[37]  Francisco J. García-Peñalvo,et al.  Knowledge discovery in software teams by means of evolutionary visual software analytics , 2016, Sci. Comput. Program..

[38]  Suresh Chalasani,et al.  Predictive analytics on Electronic Health Records (EHRs) using Hadoop and Hive , 2015, 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT).

[39]  Yusuf Kavurucu,et al.  Hadoop Ecosystem and Its Analysis on Tweets , 2015 .

[40]  Yu Zhou,et al.  A Novel Approach for Improving Security and Storage Efficiency on HDFS , 2015, ANT/SEIT.