A STUDY ON CORPORATE’S BIG DATA ANALYTICS SANNIDHANAMANURAG B.COM (COMPUTERS) STUDENT AT ST.JOSEPHSDEGREE AND PG COLLEGE ABSTRACTBig data analytics hascome in to use by the corporate sector due to the failure of the process-basedapplications system to scrutinize numerous volumes of data (Eg-: Aadhar card).Big data deals with scrutinizing huge volume data sections in order to ascertain the information theycontain.The main objective of this study is to know the importance of big data inpost-modernistic technological advancement and how we can make more changes inthe corporate sector by implementing big data techniques. The scope of study isrestricted to the use of big data techniques in corporate sectors to know all the differentsolutions to more quickly resolve or enhance a particular situation.
Theoutcomes I determined from this study is that big data is highly instrumentalto corporate sector (especially to the customers of the health sector) if therules and regulations are implied as per the need and wants of big dataanalytics, big data would be the most pleasing technology to scan numerous datain single goKey words-: process-basedapplication system, examining, technological advancement, solutions,specialized, cost effective INTRODUCTIONBIG DATABig data theword ‘Big’ here states huge/numerousdata, hence Big data deals with scrutinizing largevolume data sectionsin order to ascertain the information they contain within them. In simple wordsit is the extremely huge data sets that may be scrutinized using artificial intelligence toprovide the organization with patterns, trends, and associations, especiallyrelating to human behavior and interactions. It is the most trending techniqueused in the 21st Anno Domini era by almost all the big corporatesectors out there, as the techniques of big data are accepted throughout the globe this paved a huge platformfor big data technique users.
BIG DATA ANALYTICSWhereascoming to big data analytics, big dataanalytics is the technique of scrutinizing of huge and different data segments which helps tosimplify present trends of the market, preferences and other valuableinformation that can help the corporate world take more-knowledgeabledecisions. METHODOLOGY OF THE STUDY Data collection instrument: The data that isused in this research is mainly of secondary nature. The data is collected fromsecondary sources such as various websites, journals, newspapers, books, etc.the analysis used in this project has been done using selective technical tools.Review of literatureThe big data isnow one of the most trending tools used by large scale corporate sectorsglobally to know patterns, trends,and associations, especially relating to human behavior and interactions, Bigdate is more beneficial to the corporate sectors to ascertain the needs andwants of their customers and also helps in giving solutions to the companies sothat their customers get satisfied. Apart from all this big data is a tool usedby the corporate sector to maintain full-fledged support for their productsfrom the customers as the motive of every corporate is to earn profits with atmost consumer satisfaction and gain full-fledged trust from the customers.
TECHNIQUES OF BIG DATAANALYTICS1. Prescriptivemethod2. Predictivemethod3. Diagnosticmethod4. Descriptivemethod 1.
Prescriptive analytics-: This type of analysis reveals what actions should be taken.This is the most valuable kind of analysis and usually results in rules andrecommendations for next steps, but this approach is rarely used. Where bigdata analytics in general puts light on a subject, prescriptive analytics givesyou the perfect ability to answer the pros and cons, for example if you choosehealth sector. You can better manage thepatients frequency by using prescriptive analytics to measure the number ofpatients who are clinically obese 2.
Predictive analytics-: An analysis of likely situations of what might happen. Thedeliverables are usually a predictive forecast use bigdata to identify past patterns to predict the future. For example, companiesare using predictive analytics for the entire sales process, etc. Properlytuned predictive analytics can be used to support sales, marketing, or forother types of complex forecasts.3. Diagnostic analytics-: This technique is nothing but pooling back at past deeds of thebusiness to know what and why it happened. Diagnostic analytics is nothing butchecking the mistakes committed in the past and finding the cause of themistake4.
Descriptive analytics-: What is presentlyhappening in the organization based on the data ascertained data. A simpleexample of descriptive analytics would be ascertaining how much credit limitcan be given to a customer this would be possible only when the precedingprevious years financial performance is known by the bank to predict their customer’slikely financial performance From the following techniquesused I can conclude that there is deduction in the amount of huge dataavailable in the organization is and the data which is worthy is grasped by bigdata analytics to provide the organization with more effective results duringthe decision making LIMITATIONS OF BIG DATA ANALYTICS1. The implementation of bigdata techniques in an organization is very expensive2. Thereis lack of awareness of big data in the present global market3. Big data techniques canonly be implemented by the large scale organizations as the small scale cannotafford specialized labor and the installation costs4.
Itrequires knowledge in the techniques used only then an organization cansuccessfully adopt it.5. Thelack of stability of the employees who are knowledgeable of big data analyticsFINDINGSAND CONCLUSIONS AND SUGGESTIONS1. Big data is highly instrumental tocorporate sector to find effective results 2. The first time installation cost would be very high but oncethe tool is installed it would be cost effective3. The organization should increase the salaries of thespecialized people with big data analytics so that there would be employeesstability4. The tool need to be updated as per the requirements of thetool in order to get best results SOURCESSECONDARY DATA1.
https://www.coursera.org/learn/big-data-introduction/lecture/KSrx5/big-data-generated-by-people-the-unstructured-challenge3. http://opensourceforu.com/2017/09/open-source-tools-you-can-use-to-handle-big-data/4. Big Data and Learning Analytics in Higher Education (By Ben Kei Daniel)