BIG DATA ANALYSIS

#Business Intelligence and data mining
#BIG DATA ANALYSIS
#Report and Presentation
#Critically evaluate available methods of big data analysis and review possible uses of these techniques for business intelligence
#Big data is the term for data sets so large and complex that they are difficult to process using traditional database management or data processing applications. Scientists regularly encounter limitations on the size of data sets that are feasible to process in a reasonable amount of time in many areas, including meteorology, genomics, complex physics simulations, and biological and environmental research. The limitations also affect Internet search, finance and business informatics.
#Healthcare: Screening and diagnostic tests, genomics, medical imaging data
Science: Sloan Digital Sky Survey, Square kilometre array, Large Hadron Collider, earthquake sensor data
Social Science: Social media data streams, Facebook etc.
Business and Finance: Stock exchange data streams, Point of Sale data, Amazon.com
Industrial: Sensor and monitoring equipment

Alternatively, you may select your own area of big data to investigate, but please inform me of you selected area before you commence your investigation.
Healthcare: Screening and diagnostic tests, genomics, medical imaging data
Science: Sloan Digital Sky Survey, Square kilometre array, Large Hadron Collider, earthquake sensor data
Social Science: Social media data streams, Facebook etc.
Business and Finance: Stock exchange data streams, Point of Sale data, Amazon.com
Industrial: Sensor and monitoring equipment

Alternatively, you may select your own area of big data to investigate, but please inform me of you selected area before you commence your investigation.

#Biologically Inspired Data Mining Techniques

For the last few years, biologically inspired data mining techniques have been intensively used indifferent data mining applications such as data clustering, classification, association rule mining, sequential pattern mining, outlier detection, feature selection and bioinformatics. The techniques include Neural Networks, Evolutionary Computation, Fuzzy Systems, Genetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, Artificial Immune Systems, Culture Algorithms, Social evolution, and Artificial Bee Colony Optimization. A huge increase in the number of papers published in the area has been observed in the last decade. Most of these techniques use optimization to speed up the data mining process and improve the quality of patterns mined from the data. The aim of the workshop is to highlight the current research related to biologically inspired techniques in different data mining domains and their implementation in real life data mining problems. The workshop will provide a platform to the researcher from computational intelligence and evolutionary computation and other biologically inspired techniques to get feedback on their work from other data mining perspective such as statistical data mining, AI and machine learning based data mining.

The special issue highlights a relatively new but fast growing area of data mining which is based on optimization techniques from biological behaviour of animals, insects, cultures, social behaviours and biological evolution. Techniques based on these models have been studied substantially, well optimized and tuned for different application areas in the previous decade. Knowledge Discovery and Data mining has been observed as one of the fastest growing application area of these nature inspired techniques.

Your task is to investigate an area of big data analysis using biologically inspired data mining methods, and produce a research report that documents the particular techniques and technologies employed and the specific challenges that face that application of big data analysis. Your report should also address criticisms of the big data paradigm that some authors have identified and suggest what implications such arguments have on the area of big data analysis that you have chosen to investigate. You are also required to present your findings in the final week of classes (week 11 in the form of Audio slides).

#Research Report