...Big data analytics is projected to change the way companies manage and analyze large information set and how people produce massive amounts of data. A recent findings produced by few Internet and Online Business Degree looked at the future of this trend sweeping through the IT industry. This concept is up-growing one as the current data storage pattern utilized by the companies is not as productive as plotted. It is refers to following type of data 1) Traditional Enterprise Data:- includes customer related data ERP, CRM, web transaction 2) Machine Generated Data:- weblogs, Trading Systems etc 3) Social Data: - data of facebook, twitter, google etc. Big Data can be seen in the finance and business where enormous amount of stock exchange, banking, online and onsite purchasing data flows through computerized systems every day and are then captured and stored for inventory monitoring, customer behavior and market behavior. Day by day the capacity of data is increasing & many of industries are not able to manage it efficiently. By 2020, a total of 35 zeta-bytes of data will be produced as the average annual generation of information grows 43,000 percent, according to Computer Sciences Corporation. Big data may still be a relatively new phenomenon, but its impact is already being felt throughout various industries. Organizations that can effectively store, manage and analyze this information may set themselves apart from their competitors or, even better, make key advancements...
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...| PROMOTING INSTITUTIONAL SALES FOR DABUR PRODUCTS | | DILEEP SINGH SHEKHAWAT | 6/24/2010 | SUBMITTED BY:DILEEP SINGH SHEKHAWAT | DABUR INDIA LIMITED “ONE OF INDIA’S MOST ADMIRED COMPANY” TABLE OF CONTENT | TOPICS DESCRIPTION | PAGE NO… | Acknowledgement………………………………………………………..Business portfolio of Dabur…………………………………………….Introduction to Dabur…………………………………………………...About market research………………………………………………….Steps of market research………………………………………………..Data analysis and findings for corn flour…………………....................Data analysis and findings for lemoneeze…………………...................Data analysis and findings for capsico………………………................Data analysis and findings for coconut milk…………………………..Data analysis and findings for honey…………………………...............Data analysis and findings for tomato puree………………………….Data analysis and findings for tomato paste…………………………..Data analysis and findings for snack dressing…………………………Data analysis and findings for tomato ketchup……………………….Data analysis and findings for pineapple slice…………………………Data analysis and findings for fruit cocktail…………………………..Data analysis and findings for mango pulp…………………………….Data analysis and findings for keora water………………....................Conclusion and recommendations…………………………………….About institutions sales ………………………………………………..Bibliography………………………………………………………… | 789-16171819-2223-2526-2728-3031-3334-3738-3940-4243-4647-4950-5354-5556-575859-6061 | DECLARATION I DILEEP SINGH SHEKHAWAT...
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...is going. This vision is what should be translated into a business strategy, which serves to remind a company of its purpose. In an increasingly competitive global economy fuelled by technological advances, there is a seemingly prevalent idea that the customer is key and the use of marketing data is therefore crucial to a company’s success. However, the focal point is how a company can ensure their exposure to data is to be informed, not driven by data; and how the data can be used to the company’s advantage in order to achieve long term goals. Business Strategy Johnson et al. (2008), state that strategy is the direction and scope of an organisation over the long term. Without a strategy in place to refer to, it is easy for a business to become overly focussed on the day-to-day business activities, temporarily losing sight of the goals and aspirations they have set for the business. This loss of vision can in turn lead to strategic drift, a concept explained by Handy (1989), as being the cause for businesses becoming uncompetitive in their respective environments and ultimately failing as a result of being too slow to respond to external trends and losing touch with customers. One of the main causes for strategic drift is thought to be substantial changes in technology, which have been rapid across the span of the information age. Narayanan & Fahey (1986), highlight that as the external environment changes, business strategies must be modified to take account of newly emerging...
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...vertical, and if managed efficiently, it drives positive business and enables sustainable advantage, Matthew A and Stanley E (2013). If we observe carefully, huge amount of data is getting generated at each and every stages of the supply chain. In today’s digital world we are generating around 200 Exabyte of data each year, Silva R, Bogdan F and Marcin R (2013). Organizations are increasingly questioning their own ability to realize full potential from the huge amount of data they have within their supply chain, Steve...
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...BIG DATA Big data is a buzzword, or catch-phrase, meaning a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big data has the potential to help companies improve operations and make faster, more intelligent decisions. This data, when captured, formatted, manipulated, stored, and analyzed can help a company to gain useful insight to increase revenues, get or retain customers, and improve operations. Big Data: Volume or a Technology? While the term may seem to reference the volume of data, that isn't always the case. The term big data, especially when used by vendors, may refer to the technology (which includes tools and processes) that an organization requires to handle the large amounts of data and storage facilities. The term big data is believed to have originated with Web search companies who needed to query very large distributed aggregations of loosely-structured data. Success Story: Finding a Cloud Services Partner to Grow With An Example of Big Data An example of big data might be petabytes (1,024 terabytes) or exabytes (1,024 petabytes) of data consisting of billions to trillions of records of millions of people—all from different sources (e.g. Web, sales, customer contact center, social media, mobile data and so on). The...
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...CEO care about the single version of the truth? Describe at least one specific reason why companies struggle to achieve it? Provide one article to support your findings/conclusions? Dependable particular contemporary quadruplicate Chief Executive Officers assert their statement comprise effective propaganda they demand, in addition, just 13 percent of employment pioneers express their proclamation prevail constantly cutting edge, as appeared by a study by cloud-based power association strategies power Domo and Business Intelligence .A examination of more than 300 business pioneers, including 197 Chief Executive Officers and affiliation heads, discovered business pros think their affiliations need mind blowing mechanical gatherings for information driven fundamental activity, and that they are hampered by a failure to get to accommodating, proper information. The study, "What Business Leaders Hate about Big Data," found that choose 7 percent of supervisors say their reports can oblige their connection's making volume of information, and only 9 percent trust their reports show a solitary kind of the truth. The report in like way found that the most for the most part saw information disappointments among business pioneers are amassed in three zones, including how information is gone on. Around 75% (74 percent) of business pioneers said despite all that they get their information from different, separated sources, regardless of the way that more than half would need to get their information...
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...more ICT tools being developed and used in social science research, it is a good idea to reflect how ICT had effects on social science research as a whole as there is a lacking of such study. This study is underpinned on and concurred with DeLone & McLean’s (1992, 2003) Information Systems (IS) Success Model in which ICT had effects on productivity of social science researchers. This study is based on participative observation approach in which ICT had effects on social science research in the following three ICT application areas: a) Pre-data analysis, b) Data analysis, and c) Post-data analysis. These three ICT application areas had improved a researcher’s productivity in terms of speed, quantity, quality, complexity as well as cost perspective is also discussed. Some concerns of using ICT are also included in this paper which encompasses: a) High learning curve, b) Revised expectation on researcher, c) Research by the convenient of big data, and d) Decrease of social skills of researcher. Limitation, recommendation for future works and conclusion are also included Keywords – Information and Communication Technology, Social Science Research, Information Systems Success Model Introduction In 2010s, social science research is conducted differently from those in several decades before. Part of the factors may due to the advancement of...
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...New Frontier: Data Analytics Phylicia Marie Phillips Professor Progress Mtshali, Ph. D. Information Systems Decision-Making April 17, 2016 In the past, analytics was reserved for back-room debates by data geeks producing monthly reports on how things are going. Today, analytics make a difference in how a company does business, day to day, and even minute by minute; more specifically how Walmart does business. As many know, Walmart is an American based multinational retail corporation that operates a chain of hypermarkets, grocery stores and discount stores. With over eleven thousand stores and clubs in 27 countries, information technology and data analytics play a major role in Walmart’s survival and helps maintain its competitive advantage. Data Analytics Overview The business intelligence and analytic technologies and applications currently adopted in industry can be considered as BI&A 1.0, where data are mostly structured, collected by companies through various legacy systems, and often stored in commercial relational database management systems (Bottles and Begoli, 2014). The analytical techniques most commonly used in these systems, popularized in the 1990s, are mainly grounded in statistical methods developed in the 1970s and data mining techniques developed in the 1980s (Chiang, 2012). The digitalization of information has created more data and the development of cloud computing, and faster and faster computers has made the increased data more accessible...
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...Although the vital purpose of big data management is similar to, and a much better understanding of the issues, the values sought, and also the challenges that involved differing significantly between business companies and healthcare organizations. Business companies use big data to influence customers' desires and behavior patterns, develop distinctive core competencies, and build innovative products or services, whereas governments and healthcare stakeholders use big data and predictive analytics to look for sustainable solutions to such problems as pursuit public health, deciding and implementing more appropriate treatment methods for patients, supporting clinical enhancements, monitoring the protection of healthcare systems, reassuring...
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...Result Reporting How to analyze the focus groups results is by collecting data, information labels, knowledge (findings), theory, and implications. Data grouping will group answers from all interviews to each question. Information labels are to organize and classify answers into categories. Knowledge is to collect the information and answer the research objective, theory is what develops, and implications are what it means and what major themes emerge. This requires a little bit of time. A big idea or theme takes time to emerge. (www.focusgroupstips.com) Survey researchers employ a variety of techniques in the collection of survey data. People can be contacted and surveyed using several different modes: by an interviewer in-person or on the telephone, or on the internet, or by paper questionnaires. The choice of mode can affect who can be interviewed in the survey, the availability of an effective way to sample people in the population, how people can be contacted and selected to be respondents, and who responds to the survey. (Www.people-press.org/methodology/collecting-survey-data). Hiring a third party to collect the data for in surveys may be costly depending on what the survey is and who is giving it. But this also makes for a better collection of information because they are not involved in your business and will bring in good information for your business. The results of the research will be represented in an electronic presentation and emailed to various...
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...2010-1-10-131 Date of submission: November 29, 2011 Letter of Transmittal To Mrs. Rumana Afroze Faculty of Business Administration Department East-West University – Bangladesh Mohakhali, Dhaka Subject: Submission of Report. Dear Miss, It is our great pleasure to submit this report that you assigned on “Effect of personality on occupational stress in DHAKA BANK LIMITED” which has been prepared as a part of our Organizational Behavior course. We have tried our best to accomplish our research objectives successfully. This report definitely gives us an exceptional experience that will be of use in the future. The whole experience of this course enabled us to get an insight into the real life research situation. We will always be available for any supplementary interpretation or clarification that may require. Thank You. Quazi Aritra Reyan Salman Iftekhar Suny Syed Tasin Jahan Aknowledgement At this point we would specially like to thank those who had made it possible for us to prepare our report. Without their cooperation the completion of this report would have been difficult. We are most grateful to the many people in the banking sector in Bangladesh, bank employees, managers, and experts, who willingly cooperated in the difficult task of data gathering. We would also like to express our thanks to the respondents - the Directors and the Managing Committee of Dhaka Bank Ltd. Bangladesh...
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...build digital enterprises. Brad Brown, Johnson Sikes, and Paul Willmott As businesses continue to embrace digital tools their digital goals. We found that despite the and technologies—especially when engaging organizational and talent challenges, executives with customers—C-level executives in a recent remain optimistic about digital business. McKinsey survey say they are stepping up their 1 own involvement in shaping and driving digital 1 he online survey was in the T field from April 2 to April 12, 2013, and garnered responses from 850 C-level executives representing the full range of industries, regions, and com any sizes; 8.6 percent of p these executives have a spe i c fic technology focus. To adjust for differences in response rates, the data are weighted by the contribution of each respon- dent’s nation to global GDP. 2 n the 2012 survey, we asked I about three digital-business trends: big data and advanced analytics, digital marketing and social-media tools, and flexible delivery platforms. See Brad Brown and Johnson Sikes, “Minding your digital business: McKinsey Global Survey results,” May 2012, mckinsey.com. They report, for example, that their companies are strategies. This is vital to the success of digital using digital technology more and more to engage programs, as survey respondents most often cite with customers and reach them through new a lack of senior-management interest as...
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...The Big Data Challenges By Jamia Yant April 19th, 2012 Introduction When Volvo separated from Ford in 2010, it was breaking free from an IT infrastructure that consisted of a tangle of different systems and licenses. The need was there to develop a new stand alone IT infrastructure that could provide better Business Intelligence, boost communication capabilities and enrich collaborations. Volvo Car Corporation Integrates the Cloud into Its Networks The ability to collectively harness the wealth of data being mined was invaluable. Volvo collects terabytes of data from embedded sensors in their cars, from their customer relationship management (CRM) systems, from dealerships, product development and design systems and from their production/factory floors. Volvo then, via the cloud, transfers and archives this Big Data to its Volvo Data Warehouse where it can be stored for Long Term Archival and Retrieval or it can be accessed by Volvo’s employees. In 2010, Volvo stretched across eight main business units and twelve support areas with production plants in 19 countries. The platform used to link employees at the business units, support and production plants together are done via Volvo’s cloud with Saas software as a user interface and display. They have employee web portals, as well as supplier and vendor web portals to improve collaboration. Volvo has a high-performance infrastructure that includes parallel multi-processing, high-speed networking, and...
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...The Big Data Challenges By Jamia Yant April 19th, 2012 Introduction When Volvo separated from Ford in 2010, it was breaking free from an IT infrastructure that consisted of a tangle of different systems and licenses. The need was there to develop a new stand alone IT infrastructure that could provide better Business Intelligence, boost communication capabilities and enrich collaborations. Volvo Car Corporation Integrates the Cloud into Its Networks The ability to collectively harness the wealth of data being mined was invaluable. Volvo collects terabytes of data from embedded sensors in their cars, from their customer relationship management (CRM) systems, from dealerships, product development and design systems and from their production/factory floors. Volvo then, via the cloud, transfers and archives this Big Data to its Volvo Data Warehouse where it can be stored for Long Term Archival and Retrieval or it can be accessed by Volvo’s employees. In 2010, Volvo stretched across eight main business units and twelve support areas with production plants in 19 countries. The platform used to link employees at the business units, support and production plants together are done via Volvo’s cloud with Saas software as a user interface and display. They have employee web portals, as well as supplier and vendor web portals to improve collaboration. Volvo has a high-performance infrastructure that includes parallel multi-processing, high-speed networking, and...
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...The Big Data Challenges April 19th, 2012 Introduction When Volvo separated from Ford in 2010, it was breaking free from an IT infrastructure that consisted of a tangle of different systems and licenses. The need was there to develop a new stand alone IT infrastructure that could provide better Business Intelligence, boost communication capabilities and enrich collaborations. Volvo Car Corporation Integrates the Cloud into Its Networks The ability to collectively harness the wealth of data being mined was invaluable. Volvo collects terabytes of data from embedded sensors in their cars, from their customer relationship management (CRM) systems, from dealerships, product development and design systems and from their production/factory floors. Volvo then, via the cloud, transfers and archives this Big Data to its Volvo Data Warehouse where it can be stored for Long Term Archival and Retrieval or it can be accessed by Volvo’s employees. In 2010, Volvo stretched across eight main business units and twelve support areas with production plants in 19 countries. The platform used to link employees at the business units, support and production plants together are done via Volvo’s cloud with Saas software as a user interface and display. They have employee web portals, as well as supplier and vendor web portals to improve collaboration. Volvo has a high-performance infrastructure that includes parallel multi-processing, high-speed networking, and fast I/O storage...
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