Data Visualization for Business Intelligence on Mobile Phone and Tablets

Transcription

1 International Journal of Information Science and Intelligent System, 3(1): 41-46, 2014 Data Visualization for Business Intelligence on Mobile Phone and Tablets Prasad Kawade 1, Rohini Temkar 2 1 MCA Third Year, VESIT, Chembur, Mumbai, India. 2 Assistant Professor, Dept of MCA, VESIT, Chembur, Mumbai, India. Abstract Received: 10 October 2013; Accepted: 01 December 2013 Nowadays Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business and society as the Internet has become. This paper presents information about BIG DATA and an Android Application based on Big Data that can be used by the higher level management, staff, salesman etc. in their mobile phones and tablets. It gives the organization an analytical view in the form of Charts like Area Chart, Bar Chart, Pie Chart etc. This application helps various organizations like Insurance, Manufacturing Companies, Banking in Decision-making, Developing new strategies of their organization. Data Visualization for business intelligence displays a graphical view of all the data. Keywords: Data visualization; Big data; Business intelligence; Smart phone and tablet Martin Science Publishing. All Rights Reserved. 1. Introduction Mobile devices are rapidly gaining popularity due to their small size and their wide range of functionality. With the constant improvement in wireless network access, they are an attractive option not only for day to day use, but also for in-field analytics by first responders in wide spread areas. However, their limited processing, display, graphics and power resources pose a major challenge in developing effective applications. Nevertheless, they are vital for rapid decision making in emergencies when combined with appropriate analysis tools. Big Data is a term applied to data sets whose size is beyond the ability of traditional software technologies to capture, store, manage and process within a tolerable elapsed time[1-5]. The main goal of data visualization is to communicate information clearly and effectively through graphical means that allows the higher level management to insight the business and help them in decision making. Mobile Business Intelligence (Mobile BI or Mobile Intelligence) is defined as The capability that enables the mobile workforce to gain business insights through information analysis using applications optimized for mobile devices [6].

2 42 Prasad Kawade / International Journal of Information Science and Intelligent System (2014) Mobile business intelligence is soft- ware that extends desktop business intelligence applications so they can be used on a mobile device. In other words we can say that Mobile Business Intelligence is the ability to provide business and data analytic services to mobile device. The mobile applications have become more prevalent across a number of vertical markets. The drivers and patterns of mobile application adoption vary across industries, but a common framework has begun to take shape that explains these activities. Put simply, organizations have started to apply mobile technology to those processes where the integration of real-time information can drastically improve process quality. This Mobile Application can be used by the higher level management, staff, salesman etc in their mobile phones and tablets. It gives the organization an analytical view in the form of different Charts (D3 charts, Google maps or high charts) that is used for developing new strategies[7-10]. 2. Big Data Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. The target moves due to constant improvement in traditional DBMS technology as well as new databases like NoSQL and their ability to handle larger amounts of data. With this difficulty, new platforms of "big data" tools are being developed to handle various aspects of large quantities of data. Examples of Big Data include Big Science, sensor networks, social networks, big social data analysis, Internet documents, Internet search indexing, call detail records, astronomy, atmospheric science, bio geochemical, biological, and other complex and often interdisciplinary scientific research, military surveillance, forecasting drive times for new home buyers, medical records, photography archives, video archives, and large-scale e-commerce. 3. Characteristics of Big Data Volume. The size of available data has been growing at an increasing rate. This applies to companies and to individuals. A text file is a few kilo bytes; a sound file is a few mega bytes while a full length movie is a few giga bytes. More sources of data are added on continuous basis. For companies, in the old days, all data was generated internally by employees. Currently, the data is generated by employees, partners and customers. For a group of companies, the data is also generated by machines. For example, Hundreds of millions of smart phones send a variety of information to the network infrastructure. Variety. Initially, companies analyzed data using a batch process. One takes a chunk of data, submits a job to the server and waits for delivery of the result. That scheme works when the incoming data rate is slower than the batch processing rate and when the result is useful despite the delay. With the new sources of data such as social and mobile applications, the batch process breaks down. The data is now streaming into the server in real time, in a continuous fashion and the result is only useful if the delay is very short. e.g. 140 million tweets per day on average. Velocity. From excel tables and databases, data structure has changed to lose its structure and to add hundreds of formats. Pure text, photo, audio, video, web, GPS data, sensor data, relational data bases, documents, SMS, pdf, flash, etc. One no longer has control over the

3 Prasad Kawade / International Journal of Information Science and Intelligent System (2014) 43 input data format. Structure can no longer be imposed like in the past in order to keep control over the analysis. As new applications are introduced new data formats come to life. 4. Data Visualization Figure 1. Characteristics of big data Data visualization, the use of images to represent information, is only now becoming properly appreciated for the benefits it can bring to business. It provides a powerful means both to make sense of data and to then communicate what we ve discovered to others. Many of the current trends in data visualization are actually producing the opposite of the intended effect, confusion rather than understanding. Nothing going on in the field of business intelligence today can bring us closer to fulfilling its promise of intelligence in the workplace than data visualization. But this will happen only if we understand it and use it properly. Typically the quantity of information is dense and substantial or the nature of the data is complex. Data visualization uses maps, charts, graphs, animation and other means to represent the information in a way that is easy to digest and understand. Advantages of Data Visualization: (1) They display data more visually and thus complex problems will be simpler. You can see the relationship between data. (2) They enable business users to visually explore data by spotting patterns, identifying opportunities for further analysis and convey visual results using Web reports, the ipad, or an Android tablet. (3) Data visualization also offers individuals, both within and outside a company, better understanding of data. (4) Data visualization has a potential to liberate data from the hands of statisticians, giving more users access to data. (5) Good visualization can help you see patterns and discern meanings where they otherwise might be impossible to detect. 5. Business Intelligence Business intelligence (BI) is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. BI can handle large amounts of information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability.

4 44 Prasad Kawade / International Journal of Information Science and Intelligent System (2014) BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. If understood broadly, business intelligence can include the subset of competitive intelligence. 6. Implementation and Applications Figure 2. System architecture Chart Manager is a component that fetches the data from the database and also populates this data into Data Values component and then pass this data to Web interface. Chart Manager is responsible for managing all the data for visualization Web Interface component is responsible for passing the data to the html file. This component also converts the array of long integer into a single into a single string known as json string. JavaScript is a html file which contains all the attributes like alignment, size, color and view for visualization. The device shown in the picture is mobile device or Tablet for the end user. It displays the data as visualization. Reporting Applications-Reporting Applications are everywhere. They report anything from system performance to quarterly sales. Data visualization is as important to reporting solutions as the back-end server would be. Right from plotting System Throughput in a System Performance Report to the Sales v Revenue figures in a Sales Report, charts and graphs help Executive Dashboards & Business Monitoring-The bigger an organization grows, the more they need to monitor it. This is done by seeing a snapshot of the performance of the organization, and the various departments therein which is what a dashboard is all about. This helps in identifying the negative trends and weeding them out and also identifying where

5 Prasad Kawade / International Journal of Information Science and Intelligent System (2014) 45 growth has been achieved. Creating BI dashboards like calculating Return on Investment (ROI) or displaying various Key Performance Indicators (KPIs) is pretty much indispensable to most of the medium and large-sized organizations. Figure 3. Workflow of system Interactive Maps -Visualization of data in the form of interactive maps is important in specific websites & applications which involve location-based decision-making. "Sales by Region" and "Airline Routes" maps are pretty commonplace nowadays. One of the best applications of integrating data with interactive maps is "Geo Targeted Advertising" or "Local Business Ads" on Google Maps. 7. Screen Shots Figure 4. Project icon on mobile device

6 46 Prasad Kawade / International Journal of Information Science and Intelligent System (2014) 8. Conclusion Figure 5. Displaying charts applications Data Visualization allows designers to present a large amount of information using abstract representations. The mobile applications have become more prevalent across a number of vertical markets. Mobile application plays an important role in maintaining business and future development of the company. Large amount of data can be displayed on mobile devices using various techniques. It over shadow the various problems like no need to open laptops, no need to maintain large excel sheets. It also helps the sale person to track their tasks. Rendering graphics on handheld devices is still considered a formidable task. In this paper we presented a solution for Big Data Analytic and Visualization on Mobile Devices and we showed that interactive frame rates can be achieved with large amount of displayed data. References [1] Jeff Kelly - [2] Avin Pattath, Brian Bue, Yun Jang, David Ebert, Xuan Zhong, Aaron Ault Edward Coyle. Interactive Visualization and Analysis of Network and Sensor Data on Mobile Devices. [3] Anirban Mukherjee, Joydip Datta, Raghavendra Jorapur, Ravi Singhvi, Saurav Haloi, Wasim Akram. Shared Disk Big Data Analytics with Apache Hadoop. [4] Bhuvan Unhelkar(Method Science),San Murugesan(BRITE Professional Services). The Enterprise Mobile Applications Development Framework. [5] Challenges in developing a Mobile Application. [6] Verkooij, K. and Spruit, M., Mobile Business Intelligence: Key considerations for Implementation Projects, Journal of Computer Information Systems, vol.54, no.1, pp , [7] [8] B. Unhelkar, Mobile Enterprise Architecture: Model and Application, Cutter Enterprise Architecture Practice Executive Report. index.html. [9] Miran MoSmondor, Hrvoje KonieriEki and Igor S. Pandiid. 3D Visualization of Data on Mobile Devices. [10] Guojun Yu, Xiaoyao Xie, Zhijie Liu, The Design and Realization of Open-Source Search Engine Based on Nutch.