...Cloud computing and analytics Name: Course: Tutor: Date: 1. Introduction Organizations and individuals collect vast amounts of data in their day to day operations. Data growth comes from multiple sources: From the use of computing within an enterprise for business functions such as commerce, customer service, and resource management. Use of communication devices, including computers, tablets, and mobile phone by individuals for both work and personal use also increases the daily data collected. The instrumentation of physical infrastructure, such as electrical grids, highways, and buildings for more efficient monitoring and management, opens the opportunity to collect a lot of data. It is expected that the trend will continue as both enterprises and individuals find value in access to information and communication. The challenge lies in managing the dynamic nature of the data, keeping the data secure and applying the right analytic technique to use the information most effectively. New advances in computing technologies make it possible for organizations to take full advantage of the vast amount of data they collect. 2. Architecture Design Cloud computing is an umbrella term. It encompasses many types of services. What cloud computing does is take a process anchored to one company, one data center and one facility. It enables businesses to move from working within their own IT bubble and use the cloud to access technologies they need, when they need them, at the scale they...
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...Big data can provide many benefits for businesses, but the complexities of dealing with systems like Hadoop can make it expensive and time consuming to roll out projects. California-based Kyvos Insights is launching a new product specifically designed for big data that enables business users to easily and quickly derive powerful insights from their data for more informed decision-making, with no programming required. Kyvos helps enterprises remove the complexities of Hadoop and deal with data at any scale with fast response times and an interactive experience. Its 'cubes on Hadoop' technology allows business users to visualize, explore and analyze big data interactively, working directly on Hadoop. "Companies are collecting unprecedented amounts of data, but it's very difficult for a business user to directly access and interacts with this data in a meaningful way," says Ajay Anand, vice president of products at Kyvos Insights. "Kyvos addresses this need by enabling interactive analytics on big data using Hadoop at any scale, with instant response times. Business users can now visually analyze their data and get insights instantly, without having to wait, so they can make smarter, more informed decisions". The product has been developed with the help of industry leaders most affected by the benefits and challenges presented by big data analytics. It's being used in industries including telecommunications, media and entertainment, financial services, technology and...
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...of the analysis of the application of human cognitive to the administration and choice in different business issues. The paper gives the idea of BI, types of BI, open source software, review on some popular open source tools of BI, and Benefits. Open Source Business Intelligence Tools Business intelligence is a technology driven procedure for analyzing information and displaying significant data to help corporate administrators, business chiefs and other clients to make more informed business decisions. The process of taking substantial measures of data, examining that data, displaying a high level set of reports that gather the essence of that data into the premise of business activities, and empowering administrations to settle on major day by day business choices. BI as way and system for enhancing business performance by giving capable assists for executives to empower them to have actionable data at hand. BI tools are seen as technology that change the productivity of business operation by giving an expanded worth to the endeavor information and consequently the way this data is used. (Ranjan, 2007) Implementation of BI in organizations differs from scope of metrics to accomplish...
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...August 2013 Big Data Analytics How Cisco IT Built Big Data Platform to Transform Data Management EXECUTIVE SUMMARY CHALLENGE ● Unlock the business value of large data sets, including structured and unstructured information ● Provide service-level agreements (SLAs) for internal customers using big data analytics services ● Support multiple internal users on same platform SOLUTION ● Implemented enterprise Hadoop platform on Cisco UCS CPA for Big Data - a complete infrastructure solution including compute, storage, connectivity and unified management ● Automated job scheduling and process orchestration using Cisco Tidal Enterprise Scheduler as alternative to Oozie RESULTS ● Analyzed service sales opportunities in one-tenth the time, at one-tenth the cost ● $40 million in incremental service bookings in the current fiscal year as a result of this initiative ● Implemented a multi-tenant enterprise platform while delivering immediate business value LESSONS LEARNED ● Cisco UCS can reduce complexity, improves agility, and radically improves cost of ownership for Hadoop based applications ● Library of Hive and Pig user-defined functions (UDF) increases developer productivity. ● Cisco TES simplifies job scheduling and process orchestration ● Build internal Hadoop skills ● Educate internal users about opportunities to use big data analytics to improve data processing and decision making NEXT STEPS ● Enable NoSQL Database and advanced analytics capabilities...
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...Everyday enormous amount of data is being produced worldwide. Companies capture trillions of bytes of information about their customers, suppliers, and operations. IT organizations are exploring the analytics technologies to explore web-based data sources and extract value from the social networking boom. The organizations are trying to leverage Big Data by trying to make sense from the data that they have and by securing it. Already the forward thinking players of the banking, insurance, manufacturing, retail, wholesale, healthcare, communications, transportation, construction, utilities, and education are successfully using big data by exploiting meaningful information from all the data they have and using that information in formulating their strategic moves. The Volvo Car Corporation (VCC) is the well-known auto manufacturer founded in 1927 in Gothenburg, Sweden. The Volvo Car Corporation drives product design, quality, cost reduction, and customer satisfaction through data-driven decision-making. The aggregate data volume is large and growing rapidly. In keeping with then-prevailing standards for IT architecture, the company originally began collecting this data in a dedicated data mart. The Volvo Car Corporation wanted to create an effective marketing campaign to tie in with the popular Twilight movie franchise and to create an interactive game would connect to global audience. The idea for the game was that users could play to win a new Volvo XC60 car. In an effort...
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...Analytics as a Service POV Bhagyashree V1 The no-pain route to analytics Analytics, the trend sweeping businesses There is a new corner office and it belongs to the Chief Analytics Officer (CAO). For businesses with access to large data streams, analytics holds the key to making fast and accurate decisions. CAOs can now use data for a variety of purposes. It can help manage operational efficiencies, discover customer needs, identify new markets, give shape to new products and value-added services and develop defensible differentiators. In other words, the onus to support the organizational business strategy now falls upon the CAO. And assisting CAOs with this goal is the science of analytics. Analytics is being recognized as a key business differentiator across the industries. All business functions in every organization recognize the need of quality data to drive decisions. In this competitive world, every critical decision counts CAOs are tasked to make this data and insights to make it available to anyone, anytime and anywhere. —In the current digital era, lack of actionable insights means loss of business momentum, customer attrition and erosion of market share. CAOs are therefore careful when they embark upon the analytics transformation journey. They know it requires the ability to balance the business landscape with technological developments. Through targeted business and technology capabilities realized by a proven methodology that prepares , analyses and visualizes...
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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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...Gartner's 2012 Hype Cycle for Emerging Technologies Identifies "Tipping Point" Technologies That Will Unlock Long-Awaited Technology Scenarios 2012 Hype Cycle Special Report Evaluates the Maturity of More Than 1,900 Technologies Big data, 3D printing, activity streams, Internet TV, Near Field Communication (NFC) payment, cloud computing and media tablets are some of the fastest-moving technologies identified in Gartner Inc.'s 2012 Hype Cycle for Emerging Technologies. Gartner analysts said that these technologies have moved noticeably along the Hype Cycle since 2011, while consumerization is now expected to reach the Plateau of Productivity in two to five years, down from five to 10 years in 2011. Bring your own device (BYOD), 3D printing and social analytics are some of the technologies identified at the Peak of Inflated Expectations in this year's Emerging Technologies Hype Cycle (see Figure 1). Gartner's 2012 Hype Cycle Special Report provides strategists and planners with an assessment of the maturity, business benefit and future direction of more than 1,900 technologies, grouped into 92 areas. New Hype Cycles this year include big data, the Internet of Things, in-memory computing and strategic business capabilities. The Hype Cycle graphic has been used by Gartner since 1995 to highlight the common pattern of overenthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation. The Hype Cycle Special Report is updated annually to track technologies...
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...4. 4.1 Big Data Introduction In 2004, Wal-Mart claimed to have the largest data warehouse with 500 terabytes storage (equivalent to 50 printed collections of the US Library of Congress). In 2009, eBay storage amounted to eight petabytes (think of 104 years of HD-TV video). Two years later, the Yahoo warehouse totalled 170 petabytes1 (8.5 times of all hard disk drives created in 1995)2. Since the rise of digitisation, enterprises from various verticals have amassed burgeoning amounts of digital data, capturing trillions of bytes of information about their customers, suppliers and operations. Data volume is also growing exponentially due to the explosion of machine-generated data (data records, web-log files, sensor data) and from growing human engagement within the social networks. The growth of data will never stop. According to the 2011 IDC Digital Universe Study, 130 exabytes of data were created and stored in 2005. The amount grew to 1,227 exabytes in 2010 and is projected to grow at 45.2% to 7,910 exabytes in 2015.3 The growth of data constitutes the “Big Data” phenomenon – a technological phenomenon brought about by the rapid rate of data growth and parallel advancements in technology that have given rise to an ecosystem of software and hardware products that are enabling users to analyse this data to produce new and more granular levels of insight. Figure 1: A decade of Digital Universe Growth: Storage in Exabytes Error! Reference source not found.3 1 ...
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...Table of Contents 1.0 Background description of Amazon.com 3 2.0 What is Big Data? 4 2.1 The Business View 5 2.2 Technical View 5 3.0 Amazon.com and Big Data 6 4.0 Identification of Amazon.com’s "Big Data" needs 6 5.0 Big Data problems to be solved and Big Data solutions 6 6.0 What are AWS (Amazon.COM web services) problems and what is the solution for it 8 6.1 Kinesis other advantages 9 7.0 Conclusion 10 8.0 References 11 1.0 Background description of Amazon.com History Amazon.com, Inc. (Amazon.com) serves consumers through its retail websites and focus on selection, price, and convenience. The Company offers programs that enables sellers to sell their products on its Websites and their own branded Websites and to fulfill orders through them , and programs that allow authors, musicians, filmmakers, application developers, and others to publish and sell content. The Company operates in two segments: North America and International. The Company serves consumers through its retail websites, and focus on selection, price, and convenience. The Company designs its Websites to enable millions of products to be sold by the Company and by third parties across dozens of product categories. Customers access its Websites directly and through its mobile Websites and apps. It also manufactures and sells Kindle devices. In October 2013, Amazon.com Inc acquired TenMarks Education Inc. Effective February 5, 2014, Amazon.com Inc acquired Double Helix Games...
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...BU 415 Analysis: What did organization do well? * Connected all devices allowing for synergy between users devices, this also makes people buy all of their products since only their products are all connected (drives sales) * The syncing of all items (emails, documents etc) allows for business’ to have people work from home, vacation etc which increases workers satisfaction (the flexibility of being able to wdo work anywhere) * Information systems promote business cohesion, efficiency, globalized markets and workplace * iCloud API addition provides value for the developers of Mac Apps allowing them to integrate iCloud into their apps. Third party iOS and OS X developers who want to keep loyal users and attract new users, can engage consumers through iCloud’s network of users providing flexibility to reach thousands of apps regardless of the device they are using. What measures might have facilitated or improved the process? * Apple’s ultimate goal is to create a world of only Apple devices and their associated platforms where users can live and work. Apple’s vision creates a perception of exclusivity and builds a barrier to entry. However, this can either be viewed as facilitating the company’s underlying goal or hindering it. Apple operates in a closed system with proprietary hardware and software that is often incompatible with software applications used in the business realm. Keeping both short and long term sustainability in mind, the introduction...
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...Introduction 2 Assumptions 3 Data Availability 3 Overnight processing window 3 Business sponsor 4 Source system knowledge 4 Significance 5 Data warehouse 6 ETL: (Extract, Transform, Load) 6 Data Mining 6 Data Mining Techniques 7 Data Warehousing 8 Data Mining 8 Technology in Health Care 9 Diseases Analysis 9 Treatment strategies 9 Healthcare Resource Management 10 Customer Relationship Management 10 Recommended Solution 11 Corporate Solution 11 Technological Solution 11 Justification and Conclusion 12 References 14 Health Authority Data (Appendix A) 16 Data Warehousing Implementation (Appendix B) 19 Data Mining Implementation (Appendix B) 22 Technological Scenarios in Health Authorities (Appendix C) 26 Technology Tools 27 Data Management Technology Introduction The amount of information offered to us is literally astonishing, and the worthiness of data as an organizational asset is widely acknowledged. Nonetheless the failure to manage this enormous amount of data, and to swiftly acquire the information that is relevant to any particular question, as the volume of information rises, demonstrates to be a distraction and a liability, rather than an asset. This paradox energies the need for increasingly powerful and flexible data management systems. To achieve efficiency and a great level of productivity out of large and complex datasets, operators need have tools that streamline the tasks of managing the data and extracting valuable...
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...Paper Big Data Analytics Extract, Transform, and Load Big Data with Apache Hadoop* ABSTRACT Over the last few years, organizations across public and private sectors have made a strategic decision to turn big data into competitive advantage. The challenge of extracting value from big data is similar in many ways to the age-old problem of distilling business intelligence from transactional data. At the heart of this challenge is the process used to extract data from multiple sources, transform it to fit your analytical needs, and load it into a data warehouse for subsequent analysis, a process known as “Extract, Transform & Load” (ETL). The nature of big data requires that the infrastructure for this process can scale cost-effectively. Apache Hadoop* has emerged as the de facto standard for managing big data. This whitepaper examines some of the platform hardware and software considerations in using Hadoop for ETL. – e plan to publish other white papers that show how a platform based on Apache Hadoop can be extended to W support interactive queries and real-time predictive analytics. When complete, these white papers will be available at http://hadoop.intel.com. Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 The ETL Bottleneck in Big Data Analytics The ETL Bottleneck in Big Data Analytics. . . . . . . . . . . . . . . . . . . . . . 1 Big Data refers to the large amounts, at least terabytes, of poly-structured data that...
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...Assignment 1: The New Frontier: Data Analytics xxxxxx Professor xxxx CIS500: Information System Decision Making April 17, 20xx Strayer University The New Frontier: Data Analytics Abstract The word “tweet” was first defined as “a chirping noise” whose origin dated back to 1768. Since 2011, Merriam Webster dictionary extends that definition to mean “a post made on the Twitter online messaging service”. Mention of the adoption of “tweet” into the Merriam Webster Dictionary is designed to illustrate two main points; that information can be ambiguous and that technology can reweave the very fabric of human culture. According to research done by Zikopoulos, Eaton, Deroos, Deutsch, & Lapis (2012), there exists 800,000 petabytes (PB) of data stored in the world in the year 2000. By their estimates, that number could reach 35 zettabytes (ZB) by the year 2020 (p. 39). The ability to analyze and process the enormous amount of data is a costly undertaking for companies that are behind the curve and a lucrative business for those that are ahead of the game. Each tweet and post contribution from the users that share the web space further buries the proverbial haystack. It is the ability to sift through the data that determines whether a company can gain traction in their respective industry or if they are simply spinning their wheels. This research paper, centered on Capital Cube and their parent company analytixinsight, will aim to discuss how data analytics is paramount to present and...
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...A New Era for Big Data COMP 440 1/12/13 Big Data Big Data is a type of new era that will help the competition of companies to capture and analyze huge volumes of data. Big data can come in many forms. For example, the data can be transactions for online stores. Online buying has been a big hit over the last few years, and people have begun to find it easier to buy their resources. When the tractions go through, the company is collecting logs of data to help the company increase their marketing production line. These logs help predict buying patterns, age of the buyer, and when to have a product go on sale. According to Martin Courtney, “there are three V;s of big data which are: high volume, high variety, high velocity and high veracity. There are other sites that use big volumes of data as well. Social networking sites such as Facebook, Twitter, and Youtube are among the few. There are many sites that you can share objects to various sources. On Facebook we can post audio, video, and photos to share amongst our friends. To get the best out of these sites, the companies are always doing some type of updating to keep users wanting to use their network to interact with their friends or community. Data is changing all the time. Developers for these companies and other software have to come up with new ways of how to support new hardware to adapt. With all the data in the world, there is a better chance to help make decision making better. More and more information...
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