{"id":190676,"date":"2014-04-17T00:00:00","date_gmt":"2014-03-25T13:27:01","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/quick-answers-from-large-data\/"},"modified":"2017-04-19T12:21:55","modified_gmt":"2017-04-19T19:21:55","slug":"quick-answers-from-large-data","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/quick-answers-from-large-data\/","title":{"rendered":"Quick Answers From Large Data"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Tempe is an interactive system for exploring large data sets. It accelerates faster machine learning by facilitating quick, iterative feature engineering and data understanding. Tempe is a combination of three technologies:<\/p>\n<ul>\n<li>Trill: a high-speed, temporal, progressive-relational stream-processing engine 100 times faster than StreamInsight. <\/li>\n<li>WINQ: a layer that emulates LINQ but provides progressive queries\u2014providing \u201cbest effort\u201d partial answers. <\/li>\n<li>Stat: an interactive, C# integrated development environment that enables users to visualize progressive answers. <\/li>\n<\/ul>\n<p>The combination of these technologies enables users to try and discard queries quickly, enabling much faster exploration of large data sets. <\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tempe is an interactive system for exploring large data sets. It accelerates faster machine learning by facilitating quick, iterative feature engineering and data understanding. Tempe is a combination of three technologies: Trill: a high-speed, temporal, progressive-relational stream-processing engine 100 times faster than StreamInsight. WINQ: a layer that emulates LINQ but provides progressive queries\u2014providing \u201cbest effort\u201d [&hellip;]<\/p>\n","protected":false},"featured_media":198254,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13563],"msr-video-type":[],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-190676","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/-p_0fv6q3po","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/190676"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/190676\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/198254"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=190676"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=190676"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=190676"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=190676"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=190676"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=190676"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}