...Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise, including Web-browsing trails, point-of-sale data, ATM records, and other customer information generated within an organization (Levine, 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations, but along with the possibilities, there are challenges. Managers must understand the pitfalls and limitations, as well as the potential of big data (Levine, 2013). The focus of this report is the business potential and implications of big data as well as understanding the challenges and limitations of big data management. The potentials for big data are numerous; however, in this report only five potentials and implications for use are discussed. These include the following: knowledge management, social media, in travel, banking, and marketing and advertising. Knowledge Management One of the greatest potential for big data is knowledge management. A goal of knowledge management is the ability to integrate information from multiple perspectives to provide the insights required for valid decision-making such as where to invest marketing dollars, how much to invest, or whether to expand into a new geographic market (Lamont, 2012). In terms of knowledge management, three dimensions...
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...The Impact of Big Data By Ijaaz Lagardien Group 3A 214167542 1|Page Contents Plagiarism Declaration ....................................................................................................................................... 3 Abstract ............................................................................................................................................................. 4 Keywords ........................................................................................................................................................... 4 Introduction ....................................................................................................................................................... 4 Semi-structured data ......................................................................................................................................... 5 What is structured data ................................................................................................................................. 5 What is semi-structured data ........................................................................................................................ 5 Types of semi-structured data....................................................................................................................... 5 Unstructured data ......................................................................................................
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...Evolution of Big Data Defining Big Data “Data-driven decision making, popularized in the 1980s and 1990s, has evolved into a vastly more sophisticated concept known as big data that relies on software approaches generally referred to as analytics”(Picciano, 2012). Big data is one of the great new frontiers of IT. Data is exploding so fast and the promise of deeper insights is so compelling that IT managers are highly motivated to turn big data into an asset that can be managed and exploited for their organization. In information technology-big data refers to the extremely large volume of data that needs to be captured, stored, searched, shared, analyzed and visualized. Big Data is not just about lots of data, it is actually a concept providing an opportunity to find new insight into and organizations existing data as well guidelines to capture and analyze future data. It makes any business more agile and robust so it can adapt and overcome business challenges. It is an overall measurement of large complex data, specifically data that falls into the “3V’s model”: high volume, high velocity, and high variety. For example, big data can be applied to the wealth of information derived from social media or data obtained from the billions of mobile phones in use daily. In a business sense, big data is a part of analytics that relies on analytic application to confirm anticipated information and trends about...
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...amount of data being handled and processed has increased tremendously. Big Data analytics plays a very significant part in reducing the size of the data as well as the complexity in applications that are being used for Big Data. Big Data Visualization is an important approach in creating meaningful visuals and graphical representations from the Big Data that help in better decision making and that give a clear insight into the data. Visualization, Big Data, Big Data Visualization, data visualization techniques are some of the topics that are discussed in this paper and examples for visualizations have been presented as well. Keywords— Visualization, Data processing, Data analytics, Big Data, Interactive visualizations. I. VISUALIZATION...
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...Grocery Stores market research report provides key industry analysis and industry statistics, measures market size, analyzes current and future industry trends and shows market share for the industry’s largest companies. IBISWorld publishes the largest collection of industry reports so you can see an industry’s supply chain, economic drivers and key buyers and markets. Market Share of Companies Kroger Publix Super Markets Inc. Safeway Industry Statistics & Market Size Revenue $584bn | Annual Growth 10-15 1.3% | Annual Growth 15-20 | | Profit | Employment 2,489,995 | Businesses 42,036 | Industry Analysis & Industry Trends The Supermarkets and Grocery Stores industry has grown over the past five years, benefiting from a strengthening domestic economy. As per capita disposable income has grown over this period, some consumers traded up to premium, organic and all-natural brands, helping lift industry revenue. Over the next five years, the industry is anticipated to grow as a result of rising discretionary income, albeit at a more conservative rate than in the previous five-year period. As health concerns intensify, more consumers will seek all-natural and organic products, which are priced at a premium... purchase to read more Industry Report - Starting a New Business Chapter Barriers to entry in the Supermarkets and Grocery Stores industry are moderate. However, the level of initial capital investment is high. In the past, the major operational cost...
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...Customer analytics in the age of social media : TDWI best practices report Cary : SAS Institute . (039032) T DW I R E S E A R C H T DW I BE S T P R AC T ICE S RE P O R T THIRD QUARTER 2012 CUSTOMER ANALYTICS IN THE AGE OF SOCIAL MEDIA By David Stodder CO-SPONSORED BY tdwi.org Third QUArTEr 2012 TDWI besT pracTIces reporT CuSToMEr A n A ly T IC S In T HE AGE of SoCI A l MEdI A By David Stodder Table of Contents Executive Summary Research Methodology and Demographics 3 4 5 Customer Analytics and the Social Media Frontier Stepping into the Age of Social Media . . . . . . . . . . . . . . . . . .6 The Importance of Customer Analytics . . . . . . . . . . . . . . . . . .7 Benefits and Barriers to Implementation 10 Business Benefits Sought from Customer Analytics . . . . . . . . . . 10 Barriers to Adoption of Customer Analytics . . . . . . . . . . . . . . 12 role of Analytics in Increasing Marketing roI . . . . . . . . . . . . . 13 Analytics Tools, Data Sources, and Techniques 17 BI, olAP, and data discovery for Customer Analytics . . . . . . . . . 18 In-Memory Computing for More rapid discovery Analysis . . . . . . . 20 Predictive Analytics, data Mining, and Advanced Statistics Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 filling the role of the data Scientist for Customer Analytics...
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...the store, they would be able to do so in smooth and seamless way. Oasis a fashion retailer from UK has currently implemented this kind of system. 2. The mobile wallet The credit card and debit card won’t be out of use any time soon. But use of mobile internet is increasing day by day. With 3G-4G services emerging at an accelerated pace “mobile wallet” is going to get a huge chunk of payment market. As people tend to carry as less thing with them as possible the mobile wallet will be the one replacing the different payment method people uses at the retail stores(both online & offline). Google wallet, Paypal is few of the service which provides the mobile wallet. 3. More personalized in store experience Retailers will be implementing the solutions to create more personalized in store experience. Ecommerce sites has been doing this for years by tailored landing pages, retailers will also be bringing more and more technologies in the store to address to each and every customer in any place in store. Technologies like iBeacon, Estimote, In-store mobile devices will allow the stores to create an experience which will be both interactive and engaging. 4. Reinvention of loyalty programs Retailers will be working on their loyalty programs to retain more and more customers. The loyalty cards are on their way out and will be replaced by rewards that incorporate social behavior, shopping behavior and more. Office Depot a...
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...I. Big data emerging factor in IT area A. World’s notice for big data An appearance of tablet PC and social media was the hottest issue in IT market in last year. There are some successful global companies that go along the trends although it is not that long period since they appeared in the world, such as Apple, Google, Facebook, and Twitter. They have something in common. That is, they are based on ‘Big Data’ technology. As a result of using ‘big data’, the amount of stored data by their big data system during 2012 is much more than that of data which had been produced and stored until 2011. It helps to solve several problems in the company. Due to the geometrical increase of the amount of data, the important of big data will be continuous. Big data is selected as one of noticeable keyword in 2013 IT area with mobility, social, and cloud. It will be main factor of growth of IT infrastructure in the medium to longer term and is expected to provide new strategic superiority for many companies. It is highly acclaimed at the domestic market and also the foreign market. Several successful cases of applying big data shows that it can be positive factor helping to recover global economy. Moreover, it is not limited to IT-related business but the introduction in various areas will create value. B. Background of emerging big data In fact, there are many efforts to extract meaningful information through collection and analysis of huge amount of data. Through this effort...
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...to share his opinion on social media. He does not trust advertising and only connect with brands he feels are authentic. He conditioned expect everything immediately and now. Here is another info graphic but about marketing data and consumer privacy and what consumer really think. It shows that more than half are concerned that their private information is used for marketing purposes. Contradicting are that most people do not use “do not track” features. 40 % would give up personal information in exchange for free products. More than half of people do not read privacy policies online before making a purchase but most people expect consumer protection groups to monitor how brands use their personal data We talked about the benefit of Big Data for consumers so we thought to include some downside as well. For instance Big Data knows you are broke. Data brokers sell list of people with financial issues to marketers. Data brokers get this information about tracking your browser, the credit card you apply for, surveys you take and other sources. The media broker Media list, says the list feature “highly responsive opportunity seekers” who are ripe for promotional offers, contests and other “opportunities to make easy money” Basically taking advantage of people and their situation. Data brokers also collect and sell consumer information such as list of seniors with dementia, people with medical condition and crime victims. Marketers buy this data so they can target shoppers...
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...04-19-2015 The New Frontier: Data Analytics (Course title: Info System Decision Making) Professor: Clifton Howell Student: Deep Ajabani Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have the biggest possible impact. Analytics have been used in business since the management exercises were put into place by Frederick Winslow Taylor in the late 19th century. Henry Ford measured the time of each component in his newly established assembly line. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have changed and formed with the development of enterprise resource planning (ERP) systems, data warehouses, and a large number of other software tools and processes. In later years the business analytics have exploded with the introduction to computers. This change has brought analytics to a whole new level and has made the possibilities endless. As far as analytics has come in history, and what the current field of analytics is today many people would never think that analytics started in the early 1900s with Mr. Ford. We are going to have a look on Big Data Analytics. Let’s have a look on advantages of big data analytics. It helps marketing companies build models based on historical data to predict who will respond...
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...INTRODUCTION TO BIG DATA IN RETAIL Big Data is a massive pool of data (both structured and unstructured) that cannot be processed using traditional database and software techniques. When any particular organization uses this catch phrase they refer to the technology that can be used to channelize this huge pool of data into some useful information. This channelization includes modification, creation, manipulation, storage, transfer, sharing and analysis of the data. Big data in Retail Consider a situation in which it is the busiest shopping time of the year and only one particular product is flying off the shelf. In the past, the stores who reacted to this demand forecast or had good amount of inventory of that product had an advantage....
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...INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework. Keywords: Business intelligence and analytics, big data analytics, Web 2...
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...The New Frontier: Data Analytics CIS 500: Information Systems For Decision-Making Anywhere we travel on the internet we have been bombarded with seemingly codependent requests to, “Like US!”, “Follow US!”, “Watch US!”, “Share US!” from businesses of all types. If you think about it, this is exactly the dynamic. Businesses are in a dependent relationship, relying on the consumers for their survival. If a business wants to engage and remain in a viable relationship, it has to have a product/service the consumer desires and be able to deliver it in a manner that the consumer perceives as valuable. Even if a business has the “next greatest thing”, the consumer will not engage/continue in the relationship if the business does not or cannot provide it in a valuable way to the consumer. Amazon is one company that has been able to successfully develop this dynamic relationship. So then how does a business become and remain successful in the relationship? They need a better understanding of what the consumer wants by improving their Business Intelligence (BI). For decades, businesses have used statistics to analyze data to obtain information and insights for improving BI. With the advent of the computer, data analysis moved from statistical based inferences about the data to a more scientific method based on empirical results. This was the foundational begins of Data Analytics. Data Analytics, as defined in our course text is, specialized software, capabilities, and...
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...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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...ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework. Keywords: Business intelligence and analytics, big data analytics...
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