Big Data is the major input for Data Analytics which has tremendous influence in carrying out socio-economic governance in efficient manner. The objective of this write up is to draw a sketch of the discipline of Big Data and Data Analytics so that anybody equipped with literacy on Data Science can understand the role of Big Data and Data Analytics in governance of economic, commercial as well as social institutions.
Data is input and processed data is information without which decision making in any sphere of 21st Century civilization is perhaps impossible. It is an imperative to use three connotations in the write up viz. ‘Data’,’ Big Data ‘and ‘Data Analytics’ in order to understand overall perspective of Big Data.
Data in simplicity is any alpha-numeric character and Big Data stands for volume of information both structured and unstructured data processed with the help of modern data processing techniques. It may be mentioned that floppy disk, CDs, and USBs were used to store data earlier and their storage capacity is restricted to Gigabyte (1 Gigabyte is equal to 1024 Megabyte). Today, Hard disk capacity has reached to Petabyte, Exabyte etc. Internet of Things (IOT) is also acting as a generator of huge data.
Big Data helps the socio-economic institutions in predicting behavior of economic and business variables in terms of demand, supply, pattern of GDP(Gross Domestic Product), customers’ behavior, tastes and preferences, etc which are considered to be necessary inputs for decision making in the commercial and social institutions. 21st Century organizations come across a different flow of data while remaining engaged in day to day operations and most of the data are left untapped since traditional data management techniques are devoid of required capacity to handle volume including high volume sensor data, server, mobile devices and information obtained from social networking sites which include Facebook, Twitter, LinkedIn etc and it is quite difficult to ignore information obtained from these sources. It is , therefore , a necessity to create data platform in terms of Exabyte (EB and one EB is equal to 1024 Petabyte (PB)) and it is attributed with significantly increasing trend in term of volume and that is why it is known as ‘Big Data’. Let us offer a bird’s eye view of statistics of the constituents of Big Data.
Walmart processes more than 10,00,000 transactions per hour, Amazon processes 600 items per second and more than 200 millions e-mails per day, commercial airlines process 5,800 flights take off per day, 3.7 billion humans remain on internet through mobile phone and other electronics devices, Master Card processes 74 billion transactions per year, Google Search Engine makes 40,000 searches per second, 300 million photos are uploaded on Facebook per day, Snapchat users share 5,50,000 photo uploads every minute, more than 4 million people access to You Tube every minute, more than 4,50,000 tweets are sent every minute, 1.5 billion users connect to facebook every day, 400 million Instagram users are found to be active per day, more than 16 million messages are transmitted per minute and so on.
The statistics furnished here are at global level , of course , and they may suffer from insignificant inaccuracy. Online mode of commercial, economic and social transactions make our lives hassle free and smooth. It is worth mentioning that we have hardly any idea how to manage the day to day data on the basis of individual requirement but Big Data is equipped well to handle this huge data and the same can be available for various purposes. Big Data is based on the categories in terms of Volume, Velocity and Variety. Now volume of data is measured in terms of PetaByte(PB). QR Code, Sensor Devices, and Smart Meters deal with real time data and theses schemes help in processing data with high speed and finally to talk about Variety of Big Data. Big Data come in different formats such as image, video, textual document, e-mail, barcode tagging, RFID (Radio Frequency Identification) and structured and unstructured data.
Big Data has occupied an important room in corporate and social sectors. It helps to understand customers’ psychological behaviour pattern, priorities, predicting and forecasting sales, factory set up and organization, income pattern of the customers and their purchasing power .
Since product pricing decision and its success act as the prime determinants of products’ profitability, customers’ profitability and of course, return on investment. Big Data helps in increasing sales revenue and efficient and effective cost management. Efficient cost management is of the Himalayan importance for sustainable profitability and growth of business organizations. It helps in optimum allocation of resources and spending, waste minimization, diagnosing the proximate and other causes of failure, improving sales forecasting, understanding the pulse of market competition etc. In a nut shell, Big Data has influential role in facilitating marketing and sales, purchase and procurement , finance and accounting, research and development, human resource and manpower planning functions and their effectiveness are determinants of success and they act as the critical success factors for the corporate sector by and large under the canvas buyers” market conditions.
Let us understand the significance of Data Analytics which in simplicity stands for a strategy of analyzing large volume of data i.e. Big Data.
Data Analytics aims at examining large quantum of data in order to unearth or uncover unexplored patterns, correlations and other relevant insights. It is a tool that enables economic, social and governmental institutions to analyze all relevant data for framing the appropriate strategies to meet the challenges likely to come into being in unforeseen future besides managing efficiently present socio-economic and bureaucratic as well as judiciary institutions . Here, anybody may raise a thought provocative question how Data Analytics makes Big Data work by making traditional data management techniques almost redundant and at the same time it is going to make revolutionary mark in the data management science. In this context, it may be asserted that Data Analytics make Big Data work on the principle that more somebody knows about anything , any time and any situation, the more it offers insights on forecasting and predictions about what is likely to happen in future. This is achieved through the processes involving developing models on the basis of collected data and running simulations until it makes out an insight in order to work out a solution to the problems the organizations faced or likely to face. In this context, it may be customary to take the instance of a techno-commercial firm where finance professionals are the most important data driven agents who bridge the gap between strategic, tactical and operational decision making managers and executives. The Chief Financial Officer(CFO) enjoys the prerogative of having access to diverse chunk of data of the an organization and it can take the help of Data Analytic to strengthen decision support system. The Cost & Management Accountants (CMAs) or simply Management Accountants (MAs) can convert data into business strategic management insights with their management accounting expertise in conjunction with use of modern management accounting tools and techniques in order to influence the direction of the business to navigate strategically at forecasted destination. The strategic level management needs information for visualization and decision making whereas the tactical management needs information for the purpose making analysis, forecasting and reporting thereof and finally operational management needs information for task planning and execution and Big Data is the source of all information and the same is disseminated with accuracy, speed, validity and authenticity by the MA to the users of information at different levels of management.
MA is well conversant to understand the needs of information of the managers and executives at different levels of management and Big Data is the source of such information. Data Analytic Approach is embodiment of ” asking interesting questions out of the box thinking, getting data, , data recovery, data preparation followed by modeling, then comes evaluation and finally it ends on deployment” and the step with respect of ” getting data” needs the help of information technology and rest of the process gets completed by the MAs. Big Data’s application is not restricted only to the league of technology driven economic entities but it is extended to almost all spheres of society. In other words, it has occupied a prominent room in space research organizations’ as well as in small and medium sized industries. including healthcare industry, weather forecasting, insurance, banks, manufacturing companies, service and utilities. To be specific, UPS (United Parcel Services), IRS(Inland Revenue Services), Alibaba, Netflix etc are the examples of prominent users of Big Data and practitioners of Data Analytics in order to make optimum utilization of the scarce economic resources . Big Data and Data Analytics need a new kind of expertise in leading any socio-economic and governmental including institutions of higher education in the country. To become an expert in Big Data and Data Analytics, it needs to have strong foundational combination of higher Mathematics, Statistics, Computer Science, Economics and Business Management domain knowledge. Big Data is a growing field and data scientists are in short supply. Data Analytics is by and large of three types and they are Descriptive Analytics, Predictive Analytics and Prescriptive Analytics.
Data Aggregation and Data Mining tools are used when it is to summarize results of the whole or any specific segments of a business. Secondly, Statistical Models and Simulation Techniques are widely used when it is to make an estimated result of an operation and finally Optimization Tools and Heuristics are used when it is to make a complex and time-sensitive decisions. Among the many available techniques in the field of Data Analytics, Apache, Apache Sqoop, Apache Hive, Big Table, Handoop, MongoDB, MapReduce, R and Oracle R Enterprise are found widely to be in use and preferred by the users of the Big Data. Survival, sustainable growth and time-honoued development of an organization invariably depend on adoption of strategies in order to accrue maximum competitive advantage which is possible to achieve when an organization is able to produce differentiated product and generate distinctive service under the supervision of cost leadership and focusing on the comparatively unexplored markets as far as business is concerned and other organizations can functions with efficiency when they have robust system of decision making . In all the situations, Big Data and Data Analytics can act as a boon of modern technology and we should empower ourselves with the tools and techniques of Big Data without wasting time anymore. The survival of an organization shall depend on how Big Data savvy it is.