{"id":17771,"date":"2017-05-02T05:00:13","date_gmt":"2017-05-02T12:00:13","guid":{"rendered":"http:\/\/insidebigdata.com\/?p=17771"},"modified":"2017-05-24T09:25:56","modified_gmt":"2017-05-24T16:25:56","slug":"big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/","title":{"rendered":"Big Data Use Case &#8211; Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights"},"content":{"rendered":"<p>The insideBIGDATA technology use case guide &#8211; <a href=\"http:\/\/insidebigdata.com\/white-paper\/insidebigdata-guide-to-using-the-cloud\/\" target=\"_blank\" rel=\"noopener noreferrer\">Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights<\/a> provides an in-depth look at a high-profile cloud migration use case. One of the most widely discussed topics in IT today is moving workloads to cloud. The process of deciding whether or when to migrate to the cloud can be daunting. Further, finding the right technology fit for your enterprise\u00a0 objectives can be challenging with a cloud solution ecosystem filled with alternatives. To make the cloud adoption process more straightforward, this\u00a0 white paper provided a number of areas for consideration when evaluating a cloud platform. We also focused on the experiences of a high-profile enterprise\u2014Ticketmaster\u2014during the company\u2019s migration to the cloud. Finally, we offered a top-tier cloud solution\u2014Teradata IntelliCloud\u2014as an\u00a0 excellent choice for transitioning from an on-premises system to one in the cloud.<\/p>\n<p><strong><img decoding=\"async\" loading=\"lazy\" class=\"alignright size-full wp-image-17773\" src=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/insideBIGDATA_UseCase_Tickmaster.png\" alt=\"\" width=\"266\" height=\"346\" srcset=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/insideBIGDATA_UseCase_Tickmaster.png 266w, https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/insideBIGDATA_UseCase_Tickmaster-231x300.png 231w, https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/insideBIGDATA_UseCase_Tickmaster-115x150.png 115w\" sizes=\"(max-width: 266px) 100vw, 266px\" \/>Accelerating Demand for Cloud Services<\/strong><\/p>\n<p>Demand for enterprise cloud services is growing exponentially. A recent Teradata survey indicates that by 2020, 90% of their customers expect to\u00a0 have a hybrid cloud environment\u2014and more than 85% expect to buy data warehousing as a service. These market needs must be addressed with\u00a0 simple, packaged solutions that combine leading data and analytic software as a service with unprecedented deployment choice and flexibility.\u00a0 Ultimately, these solutions need to free enterprises to focus on how analytic insight can move the needle for their company.<\/p>\n<p>According to Gartner, more and more enterprises are demanding that service offerings support hybrid scenarios that incorporate traditional on-premises technologies as well as new cloud technologies, and ultimately establish a hybrid IT environment [1] Enterprise solutions need to be designed to support this type of modern hybrid approach with comprehensive subscription services aligned to customer priorities. The solutions also\u00a0 need to support the same enterprise use cases and workloads that are available with on-premises systems, though with the advantages of subscription pricing in a software-as-a-service (SaaS) model. Common use cases for companies running their analytic ecosystem in this fashion are:<\/p>\n<ul>\n<li>Production<\/li>\n<li>Test and development<\/li>\n<li>Quality assurance<\/li>\n<\/ul>\n<p>Hybrid cloud use cases for enterprises employing both cloud and on-premises systems include:<\/p>\n<ul>\n<li>Cloud bursting<\/li>\n<li>Cloud data labs<\/li>\n<li>Cloud disaster recovery<\/li>\n<\/ul>\n<p>For enterprises considering a cloud solution, the topics of security and compliance are essential for success. A viable solution should include rigorous third party audits of managed cloud offerings to demonstrate compliance with security regulations and industry best practices such as ISO 27001, SOC 1, SOC 2, PCI, and HIPAA.<\/p>\n<p>The requisite solutions offer more choice, greater dexterity, and the ability for enterprises to increase their focus on extracting and applying analytic insights rather than on managing infrastructure. The objective is to increase business agility and boost focus on data-driven analytic insights that have meaningful business outcomes.<\/p>\n<p>The goal of this whitepaper is to make the case for this enterprise-class cloud solution by examining a high-profile use case example describing how\u00a0 Ticketmaster successfully migrated to the cloud through use of the Teradata IntelliCloud\u2122 technology suite.<\/p>\n<p><strong>Ticketmaster Background and Cloud Migration Motivations<\/strong><\/p>\n<p>Founded in an Arizona State University college dorm room more than 40 years ago, Ticketmaster has grown into a global ticket retailer serving 19\u00a0 countries. Ticketmaster sells hundreds of millions of tickets to every type of show and venue yearly. The company\u2019s online properties get over a billion\u00a0 unique visitors per year. The Ticketmaster e-commerce site is one of the top three in the world, while using analytics and data to always improve the\u00a0 fan experience and fill venues for its parent company, Live Nation Entertainment.<\/p>\n<blockquote><p>We needed a platform that was fast, predictable, scalable, something we could grow with and something that would grow with us as we continue to\u00a0 have additional data and demands placed on it,\u201d said Shawn Moon, Director of Database Solutions, when describing the Ticketmaster journey with\u00a0 Teradata in the cloud.<\/p><\/blockquote>\n<p>The chart below depicts the Ticketmaster data environment that existed during the cloud evaluation period. It\u2019s apparent that the company had data\u00a0 everywhere, from many different sources, on different platforms and with different schemas. There were silos of data with nothing truly shared, and\u00a0 trying to create a cohesive report with data sources from different systems was very difficult. Teradata was chosen to build a large, robust data\u00a0 warehouse to service all the company\u2019s needs.<\/p>\n<div id=\"attachment_17772\" style=\"width: 589px\" class=\"wp-caption aligncenter\"><img aria-describedby=\"caption-attachment-17772\" decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-17772\" src=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/Ticketmaster_data.png\" alt=\"\" width=\"579\" height=\"480\" srcset=\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/Ticketmaster_data.png 579w, https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/Ticketmaster_data-300x249.png 300w, https:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/Ticketmaster_data-150x124.png 150w\" sizes=\"(max-width: 579px) 100vw, 579px\" \/><p id=\"caption-attachment-17772\" class=\"wp-caption-text\">The Ticketmaster data chart was evidence that a solution was needed<\/p><\/div>\n<p>&nbsp;<\/p>\n<p>Over the next few weeks we will explore these big data analytics in the cloud topics:<\/p>\n<ul>\n<li>Accelerating Demand for Cloud Services, Ticketmaster Background and Cloud Migration Motivations<\/li>\n<li><a href=\"http:\/\/insidebigdata.com\/2017\/05\/09\/big-data-use-case-ticketmaster-cloud-migration-experiences\/\" target=\"_blank\" rel=\"noopener noreferrer\">Ticketmaster Cloud Migration Experiences and the Journey with Teradata into the Cloud<\/a><\/li>\n<li><a href=\"http:\/\/insidebigdata.com\/2017\/05\/17\/big-data-use-case-ticketmaster-learned\/\" target=\"_blank\" rel=\"noopener noreferrer\">What Ticketmaster Learned<\/a><\/li>\n<li><a href=\"http:\/\/insidebigdata.com\/2017\/05\/24\/big-data-use-case-teradata-intellicloud\/\" target=\"_blank\" rel=\"noopener noreferrer\">Teradata IntelliCloud and Hybrid Cloud Analytics<\/a><\/li>\n<\/ul>\n<p>If you prefer, the\u00a0complete\u00a0<em>insideBIGDATA technology use case guide &#8211; Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights<\/em> is\u00a0available\u00a0for\u00a0download in PDF from the<a href=\"http:\/\/insidebigdata.com\/white-paper\/insidebigdata-guide-to-using-the-cloud\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u00a0insideBIGDATA White Paper Library<\/a>, courtesy of Teradata.<\/p>\n<p>[1] \u201cBuild and Market Cloud-Based Offerings Primer for 2017\u201d published Jan 24, 2017 by analysts Ed Anderson, Gregor Petri<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The insideBIGDATA technology use case guide &#8211; Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights provides an in-depth look at a high-profile cloud migration use case. One of the most widely discussed topics in IT today is moving workloads to cloud. The process of deciding whether or when to migrate to the cloud can be daunting. Further, finding the right technology fit for your enterprise  objectives can be challenging with a cloud solution ecosystem filled with alternatives. To make the cloud adoption process more straightforward, this  white paper provided a number of areas for consideration when evaluating a cloud platform.<\/p>\n","protected":false},"author":37,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[65,115,66,186,87,180,56,101,1,58],"tags":[357,117,408,565,379,95],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Big Data Use Case - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Big Data Use Case - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"The insideBIGDATA technology use case guide - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights provides an in-depth look at a high-profile cloud migration use case. One of the most widely discussed topics in IT today is moving workloads to cloud. The process of deciding whether or when to migrate to the cloud can be daunting. Further, finding the right technology fit for your enterprise objectives can be challenging with a cloud solution ecosystem filled with alternatives. To make the cloud adoption process more straightforward, this white paper provided a number of areas for consideration when evaluating a cloud platform.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/\" \/>\n<meta property=\"og:site_name\" content=\"insideBIGDATA\" \/>\n<meta property=\"article:publisher\" content=\"http:\/\/www.facebook.com\/insidebigdata\" \/>\n<meta property=\"article:published_time\" content=\"2017-05-02T12:00:13+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2017-05-24T16:25:56+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/insidebigdata.com\/wp-content\/uploads\/2017\/05\/insideBIGDATA_UseCase_Tickmaster.png\" \/>\n<meta name=\"author\" content=\"Daniel Gutierrez\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@AMULETAnalytics\" \/>\n<meta name=\"twitter:site\" content=\"@insideBigData\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Daniel Gutierrez\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/\",\"url\":\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/\",\"name\":\"Big Data Use Case - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights - insideBIGDATA\",\"isPartOf\":{\"@id\":\"https:\/\/insidebigdata.com\/#website\"},\"datePublished\":\"2017-05-02T12:00:13+00:00\",\"dateModified\":\"2017-05-24T16:25:56+00:00\",\"author\":{\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/2540da209c83a68f4f5922848f7376ed\"},\"breadcrumb\":{\"@id\":\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/insidebigdata.com\/2017\/05\/02\/big-data-use-case-ticketmaster-using-cloud-capitalizing-performance-analytics-data-deliver-insights\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/insidebigdata.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Big Data Use Case &#8211; Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/insidebigdata.com\/#website\",\"url\":\"https:\/\/insidebigdata.com\/\",\"name\":\"insideBIGDATA\",\"description\":\"Your Source for AI, Data Science, Deep Learning &amp; Machine Learning Strategies\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/insidebigdata.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/2540da209c83a68f4f5922848f7376ed\",\"name\":\"Daniel Gutierrez\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/insidebigdata.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/5780282e7e567e2a502233e948464542?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/5780282e7e567e2a502233e948464542?s=96&d=mm&r=g\",\"caption\":\"Daniel Gutierrez\"},\"description\":\"Daniel D. Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \\\"data scientist\\\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. 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Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \"data scientist\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. Follow his data science musings at @AMULETAnalytics.","sameAs":["http:\/\/www.insidebigdata.com","https:\/\/twitter.com\/@AMULETAnalytics"],"url":"https:\/\/insidebigdata.com\/author\/dangutierrez\/"}]}},"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9eA3j-4CD","jetpack-related-posts":[{"id":17903,"url":"https:\/\/insidebigdata.com\/2017\/05\/17\/big-data-use-case-ticketmaster-learned\/","url_meta":{"origin":17771,"position":0},"title":"Big Data Use Case \u2013 What Ticketmaster Learned","date":"May 17, 2017","format":false,"excerpt":"The insideBIGDATA technology use case guide - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights provides an in-depth look at a high-profile cloud migration use case. One of the most widely discussed topics in IT today is moving workloads to cloud. The process of deciding\u2026","rel":"","context":"In &quot;Big Data&quot;","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2017\/04\/Teradata_cover.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":17819,"url":"https:\/\/insidebigdata.com\/2017\/05\/09\/big-data-use-case-ticketmaster-cloud-migration-experiences\/","url_meta":{"origin":17771,"position":1},"title":"Big Data Use Case \u2013 Ticketmaster: Cloud Migration Experiences","date":"May 9, 2017","format":false,"excerpt":"The insideBIGDATA technology use case guide - Ticketmaster: Using the Cloud Capitalizing on Performance, Analytics, and Data to Deliver Insights provides an in-depth look at a high-profile cloud migration use case. One of the most widely discussed topics in IT today is moving workloads to cloud. 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DB Lytix enables analysts to perform predictive and advanced statistical analysis on Teradata Database using in-database analytics.","rel":"","context":"In &quot;Big Data&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":15174,"url":"https:\/\/insidebigdata.com\/2016\/06\/12\/talend-goes-all-in-with-amazon-web-services\/","url_meta":{"origin":17771,"position":4},"title":"Talend Goes \u201cAll In\u201d with Amazon Web Services","date":"June 12, 2016","format":false,"excerpt":"Talend, a global leader in big data and cloud integration solutions, announced that it has achieved status as an Advanced Technology Partner in the Amazon Web Services (AWS) Partner Network (APN).","rel":"","context":"In &quot;Big Data&quot;","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":20748,"url":"https:\/\/insidebigdata.com\/2018\/07\/23\/best-insidebigdata-technology-guides\/","url_meta":{"origin":17771,"position":5},"title":"Best of insideBIGDATA Technology Guides","date":"July 23, 2018","format":false,"excerpt":"Over the years since I became Managing Editor for insideBIGDATA, we've had some amazing partner firms contract with us to write custom technology guides, white papers, and advertorials. 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