BIG DATA ANALYSIS AND ITS NEED FOR EFFECTIVE E-GOVERNANCE

BIG DATA ANALYSIS AND ITS NEED FOR EFFECTIVE E-GOVERNANCE Nishant Agnihotri 1 Dr. Aman Kumar Sharma 2 Research Scholar, Ph.D. Associate Professor, Computer Science Himachal Pradesh University, Shimla Himachal Pradesh University, Shimla Abstract Big Data [9] refers to data sets that are so large and complex that traditional data processing tools and technologies cannot cope with. The process of examining such data to uncover hidden patterns in them is referred to as Big Data Analytics. Data is growing at a high speed and its analysis with various mining techniques giving rise to the valuable results in term of best perception for the future. This paper focuses on the impact of big data analysis for the E-governance. Getting insight to the results of the predictive analysis can give huge benefits to the E-governance. Apart from this, analysis of the data and its predictive nature results into the better perception of the Plans to be implemented in the future. Key words: Big data, Data Mining, E- governance, Data Analytics, Data Analysis Techniques. 1. INTRODUCTION The amount of data is increasing at a doubling rate every two years[12]. The growing rate of multimedia contents and applications contributed a lot into the growth in the quantity of data. This huge data when crosses the limit of GB s it falls into the category of Big Data. This data is generated by cell phones, GPS systems, Social Networking Websites, Online Payroll Systems and many other applications. Users generate near about 2.5 quintillion [3] data per day and it is huge data in itself from the management point of view. Analyzing large databases like this gives result to the Data Analytics and results into future prediction for some better plans for future. Figure 1 shows the typical scheme of analysis of the big data. The concept of the Smart Cities [3] is already implemented and is an example of huge growth in data. Such cities are providing a good lifestyle and huge data to the customers and to the servers respectively. Platforms are designed in such cities for mobiles and tablets where people can collect and share the data to support the understanding their surroundings. Figure1: Typical Procedure of Big Data Analysis. On the other hand E-governance is the collection of various services of the government provided to the people of a country. In India national e-governance plan[11] (NeGP) has been formulated by the Department of Electronics and Information Technology (DeitY) and Department of Administrative Reforms and Public Grievances (DARPG). Apart from the assurance of the services to the People lot of other issues are also considered as the part of the E-governance and its Planning. The vision of E- governance[11] is to Make all Public Services 219 Nishant Agnihotri, Dr. Aman Kumar Sharma

accessible to the common man in his locality, through common service delivery outlets and ensure efficiency, transparency and reliability of such services at affordable costs to realize the basic needs of the common man. E-governance uses the applications of information and communication technologies (ICTs) to support and provide public services. It also supports government administration, relationships among citizens, civil society, the private sector, and the state. After two decades of the development E-governance is examined in terms of five objectives: a policy framework, enhanced public services, high-quality and cost-effective government operations, citizen engagement in democratic processes, and administrative and institutional reform. A typical structure of communication among government and citizens is explained in Figure 2. In this paper the big data analytics and its benefits are discussed along with the Impact on the Effective E-governance. Analytics with the help of mining the data on the latest servers and architectures which are indispensible for Big data takes place. The analytics provides with the report of the mining and the report is analyzed for the actions to be taken in future. More details about the analytics and its impact are discussed in the next sections of this paper. to the consumers with best of services and to bridge the gap between regulations and practices to provide safeguard to the users. a. Scale and Scope of big data analytics: In few of the recent conservative studies it has been estimated that in the year 2008 enterprise servers had processed near about to 9.57 * 1021 bytes of data and this number is doubled every two years. The growth of this record can be imagined on the basis of the organizations which are saving records of all the activities they perform. Wall mart saves near about to 2.5 petabyte of data every hour [8] of its customers purchase history so as to do further analysis for future. b. Great Analysis of data: Data which is collected from the servers of the big companies is used for the mining activities and are therefore reports are analyzed to find the specific behavior, answer specific question and for the future action to be taken. By such analysis sometimes a person s specific behavior is analyzed to reveal the facts about his life. c. Big data Analytics for Drug discovery: In order to analyze diversity of data types in large volumes for the purpose of drug discovery. For the above purpose algorithms that are simple are required, which should be effective, efficient and scalable. In this Talk [9]discussed about how to take advantage of the recent development in big data analytics to improve the drug discovery process. He also described what have recently been done and what remains to be done to develop big data algorithms for drug discovery. He also discussed how big data analytics may contribute to better drug efficiency safety for pharmaceutical companies and regulators. Figure2: Communication between Government and Citizens for Services 2. BIG DATA ANALYTICS Growth in data comes with lot of challenges and opportunities with it. The major issue is to improving the quality of the services provided 220 Nishant Agnihotri, Dr. Aman Kumar Sharma d. Big data analytics in healthcare By digitizing, combining and effectively using Big data, healthcare organizations ranging from single-physician offices and multi-provider groups to large hospital networks and accountable care organizations stand to realize

significant benefits [2]. Detecting diseases covered under the potential benefits at the beginning stages of the implementation. As per [13] when patients can be treated with great effectiveness then management of individuals and health of population then any kind of fraud or any kind of other illegal activity can be found very easily and quickly. Lot of other questions can be addressed with big data analytics. With the help of analytics of data certain outcomes or developments could be found or estimated based on the amount of historical data analyzed. Amount of data can be length of stay (LOS, Patients who may or may not get benefit from surgery, what kind of complications could take place to patients. e. Big data analytics in Public Sector Manyika, [6] discussed asserts that the public sector doesn t getting that much information from big data as compared to other sectors as public sector doesn t keep track of the analytics of big data compared to others. Irrespective from the amount of data available government can provide better services with the analytics of the data to the citizens this is the thinking of everyone. Chen, Chiang, and Storey, [5] discussed the following areas where web analysis has started and their causes for future and further references are discussed. These areas are campaign advertising, votermobilization, policy discussion, donations, and many more other areas. Interesting fact is that most of the work in such fields are done by the government itself and remaining contribution is given by the academicians. Big data is in fact playing a major role for the future actions and for providing best of the services. 3. BIG DATA ANALYTICS FOR E- GOVERNANCE E-Governance Plan (Figure 3)[11] in India has the statement and a vision of Make all Public Services accessible to the common man in his locality, through common service delivery outlets and ensure efficiency, transparency and reliability of such services at affordable costs to realize the basic needs of the common man [11]. Figure3: E-governance Plan of India Along with this many other fields are covered under this plan of GOI (Government of India) also use Information Technology for the delivery of quality information in the field of health care in the rural areas along with many other fields also. In India this project was begun with an idea and objective of reducing and eliminating the duplicate entries from the registers and to provide an unambiguous database, generation of the reports automatically, use of the data electronically for the future cause of action. PDAs (Personal Digital assistance) were given to the health workers for providing the quality of services with the help of assessment of the data. Matthias Finger proposed a model (Figure 4) [10] for E-Governance with the emergence of NICT(New Information and Communication Technology) and compared it with the traditional model on following factors E-Governance as Customers Satisfaction E-Governance as Process of Interaction E-Governance as Tool for Government Figure4: E-Governance model with NICT 221 Nishant Agnihotri, Dr. Aman Kumar Sharma

In the proposed model of E-Governance based on NICT there is a need of Policy making, regulations and operations. These all operations infact need a big decision making behind them. Big data analytics is the field which results into the better understanding the behavior of the data. Decision making, if done with the help of big data analytics will definitely results into the better decision making and for better results. In (Figure5) an action model has been discussed which gives a view of how to perform an action on the basis of analytic reports got from data analysis. Some benefits which can be given by the analytics are Predictive policing Increasing operational efficiency Better consumer services Identification of new market Figure 5: Process of Planning Action Predictive Policing: Data when analyzed and processed for future cause of action helps in giving a view of future. It helps in finding the areas for future where problems can take palace. By such policing we can make efforts for the improvement of the future. Increasing Operational Efficiency: A clear understanding of the analysis report provides a specific area to wok upon as per the specific requirement. Working on an defined field increase the operational efficiency and gives rise to an accurate result. Better Consumer Services: As operational efficiency is increased, on the same way analysis gives a clear insight to what customer needs. Providing consumer with what he/she wants is itself a quality service. By keeping a track of consumers behavior on different services and later on analyzing it gives rise to better service. Identification of new market: Big data analysis gives rise to new area to work upon. As it has a clear insight of the behavior of the current market or the area which is under analysis. Factors which cause failure are identified easily and in results it gives rise to finding new market to work upon. Apart from these benefits there are other benefits too which are not discussed in brief here like Compliance with regulations, informing strategic directions, identifying new product service. 4. TECHNIQUES FOR BIG DATA ANALYSIS This section of the paper discuss about the various techniques available for analysis of the data. Data mining: Data mining[6] Manyika discussed it as a technique of management of data with the help of some principles of statistics and machine learning. It helps in drilling the data to get a valuable insight of it. Text Analysis: analyzing specific strings of the text or some specific pattern of text for finding information. Text analysis can be made on data generated from web, social networks and many other sources deal with the rich text. Machine learning: Technique allows the machine to learn on the bases on algorithms. This technique helps in performing the analysis by learning various methods of data analysis. Mostly machines perform what we teach them but in case of machine learning machines learn from experiences. Miller [7] discussed an example of U.S. Department of Homeland security which use machine learning to identify patterns in cell phone and email traffic [7]. 222 Nishant Agnihotri, Dr. Aman Kumar Sharma

There are many other techniques which are used for the analysis of the data but are not discussed here. Some of them are predictive Modeling, cluster analysis, classification and many other techniques helps in data analysis. 5. CHALLENGES This section of paper refers to the challenges related to the analysis of Big data. As analysis of data deals with the data ranging from general to personal data of a person. Analysis of personal data is a typical job as lot of ethics and regulations have to be taken into account during analysis process. Some of the challenges are discussed below Privacy: Big data is combination of lot of data from various customers sale purchase history, clients to a company or it can be a record of a patient of hospital. Analysis of personal information may attract the attention of the people. A reason for this is people are concerned about what is going on with their personal information. There may be chances that some people are uncomfortable with the use of their personal information. They may not want to reveal about their status behavior or may be there health conditions. Picciano[1] discussed an example of a Arizona school where school predicts the behavior and performance in advance. And further when it came on storing the behavior data it is felts that some of them may find direct interaction with the data. So it has to make sure that this data must be preserved well so that it could remain safe and beneficial. Security: Security of the data which will be saved on the servers for the analysis and the reports after analytics of the data is a big issue. We need a good infrastructure for providing security to the data. Otherwise personal data of the peoples can be stolen by any intruder and can be misused. This is a big challenge for big data safety. Data Capture and storage: Data has been captured at a high speed from various sources [4]. It is becoming difficult to handle the data on the traditional systems. So capturing data from social media, cell phones, web sites and later on storing it is a big challenge itself. 6. CONCLUSION AND FUTURE WORK Big data if analyzed with good techniques and technologies can give rise to numerous ideas and areas to upon for getting effective results. In the same way if it is been analyzed for some services provided by the government to the citizens for better implementation for E- governance plan, will give rise to more effective services. Implementing data analysis with fuzzy sets and statistical method can provide more effective ideas. References [1]. A. G. Picciano, The Evolution of Big Data and Learning Analytics in American Higher Education, Journal of Asynchronous Learning Networks, (2012)., pp 9 20. [2] Burghard C, Big Data and Analytics Key to Accountable Care Success, IDC Health Insights, 2012. [3] C.Dobre, F.Xhafa, Intelligent services for big data Science, future generation computer systems, 2013, Elsevier, pp 267-281. [4] C.L. Philip Chen, Chun-Yang Zhang, Dataintensive applications, challenges, techniques and technologies: A survey on big data, informatics Sciences, published in Elsevier 2014, pp 314-347. [5] H. Chen, R. H. L. Chiang, V. C. Storey, Business Intelligence and Analytics: From Big Data to Big Impact MIS Quarterly, (2012), pp 1165 1188. [6] J.Manyika, M.Chui, B.Brown, J.Bughin, R. Dobbs, C. Roxburgh, A. H. Byers, Big data: 223 Nishant Agnihotri, Dr. Aman Kumar Sharma

The next frontier for innovation, competition, and productivity, 2011, pp. 1 143. [7] K. Miller, Big Data Analytics in Biomedical Research, Biomedical Computation Review, 2011/2012, pp 14 21. [8] Karthik Kambatta, Gioygos Kollias, vipin Kumar, Ananth Grama, Trends in big data Analysis, j. Parallel distributed computer,2014, pp 2561-2573. [9] Keith C.C. Chan, Big Data Analytics for Drug Discovery, IEEE International Conference on Bioinformatics and Biomedicine, 2013. [10] Matthias Finger, Gaelle Pecoud, From e- Government to e-governance? Towards a Model of e-governance,3rd European Conference on e-government Switzerland. [11] NeGP Website. "about NeGP". NeGP Website. Retrieved 17 July 2014. [12] Richard cumbley, Peter church, Is Big data Creepy?, Computer laws & Security Reviews, 2013, Elsevier ltd. pp 601-609. [13] W. Raghupathi, V. Raghupathi, Big data analytics in healthcare: promise and Potential, Raghupathi and Raghupathi Health Information Science and Systems 2014. 224 Nishant Agnihotri, Dr. Aman Kumar Sharma