{"id":32808,"date":"2017-12-08T01:00:00","date_gmt":"2017-12-08T01:00:00","guid":{"rendered":"https:\/\/cloudcomputing.sys-con.com\/node\/4199805"},"modified":"2017-12-08T01:00:00","modified_gmt":"2017-12-08T01:00:00","slug":"slides-maprs-data-first-approach-cloudexpo-bigdata-ai-analytics","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/slides-maprs-data-first-approach-cloudexpo-bigdata-ai-analytics\/","title":{"rendered":"[slides] @MapR&#8217;s Data First Approach | @CloudExpo #BigData #AI #Analytics"},"content":{"rendered":"<p>To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. In his session at @BigDataExpo, Jack Norris, Senior Vice President, Data and Applications at MapR Technologies, reviewed best practices to show how companies develop, deploy, and dynamically update these applications and how this data-first approach is fundamentally different from traditional applications. He covered examples of how leading companies have identified ways to simplify data streams in a publish-and-subscribe framework (for example, how focusing on a stream of electronic medical records simplified the deployment of real-time applications for hospitals, clinics, and insurance companies). He also detailed how a data-first approach can lead to rapid deployment of additional real-time applications as well as centralize and simplify many data management and administration tasks.<\/p>\n<p><a href=\"https:\/\/cloudcomputing.sys-con.com\/node\/4199805\" >read more<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve reven&#8230;<\/p>\n","protected":false},"author":143,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-32808","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/32808","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/143"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=32808"}],"version-history":[{"count":1,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/32808\/revisions"}],"predecessor-version":[{"id":32809,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/32808\/revisions\/32809"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=32808"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=32808"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=32808"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}