{"id":2673,"date":"2013-02-26T10:00:00","date_gmt":"2013-02-26T18:00:00","guid":{"rendered":""},"modified":"2025-04-24T07:14:27","modified_gmt":"2025-04-24T14:14:27","slug":"oreilly-strata-busting-big-data-adoption-mythspart-1","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/sql-server\/blog\/2013\/02\/26\/oreilly-strata-busting-big-data-adoption-mythspart-1\/","title":{"rendered":"O\u2019Reilly Strata: Busting Big Data Adoption Myths\u2013Part 1"},"content":{"rendered":"
Think infrastructure and scalability will impede your path to big data analytics? Windows Azure HDInsight is your big data solution.<\/strong><\/i><\/p>\n It\u2019s the first day of the O\u2019Reilly Strata conference in Santa Clara, CA and I\u2019m looking forward to learning more about big data and talking to all of the customers, partners and industry influencers at the conference. Nowadays big data = big buzz. With all the noise out there about big data, it’s only natural that there might be some confusion around how to get started, doubts about whether or not your current IT stack measures up, and questions around the actual value for your business.<\/p>\n Supporting big data from an infrastructure and scalability perspective is all about elastic scale and compute in the cloud at a reasonable price. Windows Azure HDInsight, Microsoft\u2019s 100% Apache Hadoop compatible offer in the cloud currently in preview, will give businesses the ability to store and process large volumes of data while eliminating any up front infrastructure cost as you pay only for the storage and compute capacity that you use \u2013 not the racks of servers offered by many other big data vendors.<\/p>\n For more information about Windows Azure HDInsight Service visit www.microsoft.com\/bigdata<\/a>, and be sure to check back to read more in part 2<\/a> and part 3<\/a> of our big data myths series.<\/p>\n Eron Kelly Think infrastructure and scalability will impede your path to big data analytics? Windows Azure HDInsight is your big data solution.<\/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-2673","post","type-post","status-publish","format-standard","hentry","content-type-thought-leadership","review-flag-1593580427-503","review-flag-1593580410-819","review-flag-2-1593580436-981","review-flag-3-1593580441-293","review-flag-idc-1680212586-709","review-flag-micro-1680215164-570"],"yoast_head":"\n
<\/a>The truth? Getting started with big data is less of a challenge than you might think and businesses can often take advantage of existing infrastructure and tooling investments to begin doing big data analytics now. We explored some of these issues during our Big Data Week<\/a> earlier this month but would like to zero in on one of the more common big data myths \u2013 that it\u2019s too difficult for an organization\u2019s IT stack to support big data from an infrastructure and scalability perspective. A recent study by ConStat (commissioned by Microsoft) found that nearly one-third (32%) of 282 US businesses surveyed expect the amount of data they store to double in the next two to three years. And analyst firm IDC found that 24% of organizations in Europe believe their infrastructure is not ready to support that growth and big data analytics.*<\/p>\n
\nGeneral Manager
\nSQL Server<\/p>\n","protected":false},"excerpt":{"rendered":"