WHAT IS BIG DATA?
‘Big Data’ is acknowledged as the application of specialized techniques and technologies in order to process very large sets of data. These data sets are often very large as well as complex that it indeed becomes difficult to process making use of on-hand database management tools such as weblogs, call records, medical records, military surveillance, photography archives, video archives and large-scale e-commerce.
IMPLEMENTING BIG DATA: 7 TECHNIQUES
1. Association rule learning
2. Classification tree analysis
3. Genetic algorithms
4. Machine learning
5. Regression analysis
6. Sentiment analysis
7. Social network analysis
1. ASSOCIATION RULE LEARNING
Association rule learning is an accepted as a method for discovering interesting correlations between the variables in large databases. It was indeed first made use of by major supermarket chains in order to discover interesting relations between products, making use of data from supermarket point-of-sale (POS) systems.
Association rules are helping in the learning processes that are being used to help:
• place several products in better proximity to each other to increase sales
• extract information about the visitors to websites from web server logs
• analyzing of biological data to uncover new relationships
• monitoring system logs to detect intruders and malicious activity
• identifying if people who buy milk and butter are indeed more likely to buy diapers
2. CLASSIFICATION TREE ANALYSIS
Statistical classification happens to be a method of identifying categories that a new observation does belong to. It does require a training set of rather correctly identified observations – historical data in other words.
Statistical classification is being made use of in order to:
• automatically assign documents to various categories
• categorize organisms into several groupings
• develop profiles of students who do take online courses
3. GENETIC ALGORITHMS
Genetic algorithms are rather inspired by the way evolution works – that is, through mechanisms such as inheritance, mutation and natural selection. These mechanisms are made use of to “evolve” useful solutions to problems that do require optimization.
Genetic algorithms are being made use of used to:
• schedule doctors for various hospital emergency rooms
• return combinations of the optimal materials as well as engineering practices that are required to develop fuel-efficient cars
• generate “artificially creative” content such as puns as well as jokes
4. MACHINE LEARNING
Machine learning includes several software that helps to learn from data. It allows computers the ability to learn without being explicitly programmed, and is rather focused on making predictions based on known properties learned from sets of “training data.”
Machine learning is being made use of to help:
• distinguish between spam and non-spam email messages
• learn user preferences to make recommendations based on this information
• determine the best content in order to engage prospective customers
• determine the probability of winning a case, and also setting the legal billing rates
5. REGRESSION ANALYSIS
At a basic level, regression analysis does involve the manipulation of some independent variable (i.e. background music) to see how it influences a dependent variable (i.e. time spent in store). It also describes how the value of a dependent variable does change when the independent variable is varied. It also works best with continuous quantitative data like weight, speed or age.
Regression analysis is being made use of to determine how:
• levels of customer satisfaction do affect customer loyalty
• the number of supports calls that are received which may be influenced by the weather forecast given the previous day
• neighborhood and size do affect the listing price of houses
• to find the love of one’s life via online dating sites
6. SENTIMENT ANALYSIS
Sentiment analysis does help researchers to determine the sentiments of speakers or writers with respect to a particular topic.
Sentiment analysis is being made use of to help:
• improve service at a hotel chain via analysis of guest comments
• customize incentives and services to address what customers are really asking for
• determining what consumers do really think based upon opinions from social media
7. SOCIAL NETWORK ANALYSIS
Social network analysis is no doubt a technique that was first made use of in the telecommunications industry, and then rather quickly adopted by sociologists in order to study interpersonal relationships. It is now, of course, is applied to analyze the relationships between people in several fields and commercial activities.
Social network analysis is being used to:
• see how the people from different sorts of populations form ties with outsiders
• find the importance or even influence of a particular individual within a group
• find the minimum number of direct ties that are required to connect two individuals
• understand the social structure of a customer base
