Various techniques have been employed to help big data analysis since the usual database, and spreadsheet tools are overwhelmed by the processing and querying that is needed. Mostly, the data to be processed is normally in the region of terabytes and petabytes. With the involvement of experts, any big data analytics platform they use will bring solutions to your organization. There are several big data techniques that organizations should at least have. These include:
Association Rule Learning
This method is used to find if there is any correlation between some variables. Majorly used by the supermarkets to study the relationships between POS and products. It is an excellent way of busting fraud.
This technique is also helpful in the monitoring the logs in a system to see if there are any intruders, analysis of data to discover any relationships, checking the traffic flow on a website and finding ways of placing products next to each other in a supermarket among many others.
This technique is useful in the scheduling of advertisements and TV programs, arranging emergency surgeries in a hospital, generating contents such as pranks and jokes and developing the right combination of materials for various tasks in an engineering set-up.
Classification Tree Analysis
Historical data is analyzed, and the information used to identify categories that new observations that have been made belong to. It is ideal when new documents have to be continuously added to existing categories, organisms have to be grouped and profiles of students have to be developed for those taking online courses.
Regression analysis is normally used to see the movement of a variable that is dependent as a result of independent variable being manipulated. For example, if there is background music being played in a store, how many hours will people spend shopping?
Regression analysis is used to analyze how customer satisfaction affects customer loyalty, the relationship between the price drops of products and human traffic in departmental stores.
Computers are fitted with software that enables them to learn the trend from data. Computers make predictions as a result of previous actions. Machine learning is essential when trying to differentiate between email messages that are non-spam and spam emails, develop preferences for users, coming up with web content for customers and in a law firm, to evaluate the possibility of a case being won or lost.
Social Network Analysis
This big data technique is majorly used when studying the interpersonal relationships. Used to analyze how certain people influence decisions in a group and know how customers are socially structured.
Regardless of the big data technique used, organizations will be interested in knowing correlations between different groups, how to use resources optimally and have a reliable system of billing.