{"id":2113,"date":"2013-08-15T11:00:00","date_gmt":"2013-08-15T18:00:00","guid":{"rendered":"https:\/\/blogs.technet.microsoft.com\/dataplatforminsider\/2013\/08\/15\/watch-now-faster-business-insights-for-all-big-data-small-data-all-data\/"},"modified":"2024-01-22T22:49:12","modified_gmt":"2024-01-23T06:49:12","slug":"watch-now-faster-business-insights-for-all-big-data-small-data-all-data","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/sql-server\/blog\/2013\/08\/15\/watch-now-faster-business-insights-for-all-big-data-small-data-all-data\/","title":{"rendered":"Watch Now – Faster Business Insights for All. Big Data. Small Data. All Data."},"content":{"rendered":"

At Microsoft we believe that data, big and small, goes through a process or lifecycle called the Data Science Process, and is as relevant today as it was hundreds of years ago.<\/font><\/p>\n

The first step<\/b> along the data science process, is getting EASY access to data, big and small, to drive the best business decisions.\u00a0 And we would assert that\u2019s not just about IT\u2019s access to data \u2013 it\u2019s also very much about empowering end-users.\u00a0 <\/font><\/p>\n

The second step<\/b> is making it easier for the people closest to YOUR business to create a theory, model that theory, refine it and reveal those invaluable business insights.\u00a0 This involves engaging more people through powerful tools that they’re familiar with \u2013 so there\u2019s no learning curve. It comes down to just users and data, and if you can unlock this, you get to that magical point where insights are revealed. <\/font><\/p>\n

The third and final step<\/b> is creating repeatable business processes that deliver insights automatically by deploying your \u201cdata science process\u201d across a complete data platform.\u00a0 It can’t just be about storing relational data, and it can’t just be about storing unstructured data in a Hadoop cluster.\u00a0 It really does have to be about thinking about a more complete solution. You want that ROI on your data, and by operationalizing your data science process, you\u2019re going to see those returns.<\/font><\/p>\n

To help you better understand the impact of the Data Science Process and its effect on big data, Microsoft has recorded an exclusive webcast briefing, “<\/font>Faster Business Insights For All<\/font><\/a>\u201d produced in association with CIO Magazine. Microsoft is investing across all stages of the data science process \/ lifecycle.\u00a0 <\/font><\/p>\n

In this moderated discussion, featuring Jim Mallon, Executive Digital Director of Enterprise Solutions Group at IDG and Eron Kelly, General Manager of SQL Server Marketing at Microsoft, you\u2019ll hear about the Data Science process that underlies everyone\u2019s quest for insight from data, and how an integrated data platform is key to success. <\/font><\/p>\n

At Microsoft we believe in the power of providing everyone in business the ability to make sense of data on their own terms, in context. When that\u2019s possible amazing insights and breakthroughs happen.<\/font><\/p>\n

Click here<\/font><\/a> to view this webcast on big data!<\/font><\/p>\n","protected":false},"excerpt":{"rendered":"

At Microsoft we believe that data, big and small, goes through a process or lifecycle called the Data Science Process, and is as relevant today as it was hundreds of years ago. The first step along the data science process, is getting EASY access to data, big and small, to drive the best business decisions.<\/p>\n","protected":false},"author":1457,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ep_exclude_from_search":false,"_classifai_error":"","_classifai_text_to_speech_error":"","footnotes":""},"post_tag":[],"product":[],"content-type":[2445],"topic":[],"coauthors":[2487],"class_list":["post-2113","post","type-post","status-publish","format-standard","hentry","content-type-thought-leadership"],"yoast_head":"\nWatch Now - Faster Business Insights for All. Big Data. Small Data. 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