Read section 7.8 "Applications of Stream Analytics" to identify the application areas that have benefited from stream analytics. Pick the industry of your career choice. Go to teradatauniversitynetwork.com and read three cases or white papers that discuss big data analytic in your field. Write a summary of each case or white paper and answer the following questions: 1. What trends or themes have emerged from your readings? 2. Discuss the commonalities and differences between the readings. 3. Identify 3 Issues within the industry that can be tackled utilizing big data in the future. Discuss the issue in detail and how big data can be used to mitigate the issue. Instructions: Include a summary of each case and white paper (with references and in-text citations). Papers should follow APA (6th Edition) conventions Provide definitions of all course terms related to your response. Answers should be based on course-related knowledge/research and not on opinions and experience. Evidence is necessary to inform decisions. You will be graded on how well you integrate course concepts, theories, and research . Any instance of plagiarism will result in a failing grade. Repeated instances will result in a falling grade for the course. Papers should not exceed 5 pages (excluding title page, relerences, etc.) . tU8cqVGpZNOOb45XCyGbNESPHJ50M/view?ts=5fac180 7.8 Applications of Stream Analytics Because of its power to create insight instantly, helping decision makers to be on top of events as they unfold and allowing organizations to address issues before they become problems, the use of streaming analytics is on an exponentially increasing trend. The fol- lowing are some of the application areas that have already benefited from stream analytics. e-Commerce Companies like Amazon and eBay (among many others) are trying to make the most out of the data that they collect while a customer is on their web site. Every page visit, every product looked at, every search conducted, and every click made is recorded and ana- lyzed to maximize the value gained from a user's visit. If done quickly, analysis of such a stream of data can turn browsers into buyers and buyers into shopaholics. When we visit an e-commerce Web site, even the ones where we are not a member, after a few clicks here and there we start to get very interesting product and bundle price offers. Behind the scenes, advanced analytics are crunching the real-time data coming from our clicks, and the clicks of thousands of others, to understand what it is that we are interested in (in some cases, even we do not know that and make the most of that information by making creative offerings. Telecommunications The volume of data that come from call detail records (CDR) for telecommunications companies is astounding. Although this information has been used for billing purposes for quite some time now, there is a wealth of knowledge buried deep inside this Big Data that the telecommunications companies are just now realizing to tap For instance, CDR data can be analizuod to prevent churn by identifying networks of callers, intuencers Telecommunications The volume of data that come from call detail records (CDR) for telecommunications companies is astounding. Although this information has been used for billing purposes for quite some time now, there is a wealth of knowledge buried deep inside this Big Data that the telecommunications companies are just now realizing to tap. For instance, CDR data can be analyzed to prevent churn by identifying networks of callers, influencers, 410 Chapter 7 Big Data Concepts and Tools leaders, and followers within those networks and proactively acting on this information As we all know, influencers and leaders have the effect of changing the perception of the followers within their network toward the service provider either positively or negatively Using social network analysis techniques, telecommunication companies are identifying the leaders and influencers and their network participants to better manage their customer hase. In addition to chur analysis, such information can also be used to recruit new members and maximize the value of the existing members Continuous streams of data that come from CDR can be combined with social media data (sentiment analysis) to assess the effectiveness of marketing campaigns Insight gained from these data streams can be used to rapidly react to adverse effects (which may lead to loss of customers) or boost the impact of positive effects (which may lead to maxi- mizing purchases of existing customers and recruitment of new customers) observed in the campaigns. Furthermore, the process of gaining insight from CDR can be replicated for data networks using Internet protocol detail records House most telecommunications companies provide bath of these service typer a holistic optimization of all offerings and marketing campaigns could lead to extraordinary market gains. Application Case 776 un example of law Sales.ces a better sense of its customers be upon an analysis Page 438 / 515 Read section 7.8 "Applications of Stream Analytics" to identify the application areas that have benefited from stream analytics. Pick the industry of your career choice. Go to teradatauniversitynetwork.com and read three cases or white papers that discuss big data analytic in your field. Write a summary of each case or white paper and answer the following questions: 1. What trends or themes have emerged from your readings? 2. Discuss the commonalities and differences between the readings. 3. Identify 3 Issues within the industry that can be tackled utilizing big data in the future. Discuss the issue in detail and how big data can be used to mitigate the issue. Instructions: Include a summary of each case and white paper (with references and in-text citations). Papers should follow APA (6th Edition) conventions Provide definitions of all course terms related to your response. Answers should be based on course-related knowledge/research and not on opinions and experience. Evidence is necessary to inform decisions. You will be graded on how well you integrate course concepts, theories, and research . Any instance of plagiarism will result in a failing grade. Repeated instances will result in a falling grade for the course. Papers should not exceed 5 pages (excluding title page, relerences, etc.) . tU8cqVGpZNOOb45XCyGbNESPHJ50M/view?ts=5fac180 7.8 Applications of Stream Analytics Because of its power to create insight instantly, helping decision makers to be on top of events as they unfold and allowing organizations to address issues before they become problems, the use of streaming analytics is on an exponentially increasing trend. The fol- lowing are some of the application areas that have already benefited from stream analytics. e-Commerce Companies like Amazon and eBay (among many others) are trying to make the most out of the data that they collect while a customer is on their web site. Every page visit, every product looked at, every search conducted, and every click made is recorded and ana- lyzed to maximize the value gained from a user's visit. If done quickly, analysis of such a stream of data can turn browsers into buyers and buyers into shopaholics. When we visit an e-commerce Web site, even the ones where we are not a member, after a few clicks here and there we start to get very interesting product and bundle price offers. Behind the scenes, advanced analytics are crunching the real-time data coming from our clicks, and the clicks of thousands of others, to understand what it is that we are interested in (in some cases, even we do not know that and make the most of that information by making creative offerings. Telecommunications The volume of data that come from call detail records (CDR) for telecommunications companies is astounding. Although this information has been used for billing purposes for quite some time now, there is a wealth of knowledge buried deep inside this Big Data that the telecommunications companies are just now realizing to tap For instance, CDR data can be analizuod to prevent churn by identifying networks of callers, intuencers Telecommunications The volume of data that come from call detail records (CDR) for telecommunications companies is astounding. Although this information has been used for billing purposes for quite some time now, there is a wealth of knowledge buried deep inside this Big Data that the telecommunications companies are just now realizing to tap. For instance, CDR data can be analyzed to prevent churn by identifying networks of callers, influencers, 410 Chapter 7 Big Data Concepts and Tools leaders, and followers within those networks and proactively acting on this information As we all know, influencers and leaders have the effect of changing the perception of the followers within their network toward the service provider either positively or negatively Using social network analysis techniques, telecommunication companies are identifying the leaders and influencers and their network participants to better manage their customer hase. In addition to chur analysis, such information can also be used to recruit new members and maximize the value of the existing members Continuous streams of data that come from CDR can be combined with social media data (sentiment analysis) to assess the effectiveness of marketing campaigns Insight gained from these data streams can be used to rapidly react to adverse effects (which may lead to loss of customers) or boost the impact of positive effects (which may lead to maxi- mizing purchases of existing customers and recruitment of new customers) observed in the campaigns. Furthermore, the process of gaining insight from CDR can be replicated for data networks using Internet protocol detail records House most telecommunications companies provide bath of these service typer a holistic optimization of all offerings and marketing campaigns could lead to extraordinary market gains. Application Case 776 un example of law Sales.ces a better sense of its customers be upon an analysis Page 438 / 515