analytics<\/a> results in just the right ways. A lot of this has to do with sorting through structured and unstructured data sets conceptually, not going into the system and head-counting data, but instead, having a philosophy of data that focuses on just the most vital data sets and discards irrelevant and indigestible data.<\/p>\nAll of these strategies will lead an enterprise to eventual success with big data systems. Companies need to look critically at implementation in terms of practicality, so as not to disrupt existing operations. They need to look at how new and modern tools will sit on top of legacy systems or how big data will be migrated through a new IT architecture. With careful research and analysis, leadership teams can circumnavigate the pitfalls of big data and get winning results for an enterprise.<\/p>\n","protected":false},"excerpt":{"rendered":"
All sorts of businesses are jumping on the big data bandwagon, but some are having much better results than others. Where do some enterprises go so wrong, and where do others go so right? Achieving good results with big data starts with sufficient system capacity. When leaders engineer the right kinds of solutions for a […]<\/p>\n","protected":false},"author":7646,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_lmt_disableupdate":"","_lmt_disable":"","om_disable_all_campaigns":false,"footnotes":""},"q-acat":[386,392],"class_list":["post-41507","q-a","type-q-a","status-publish","format-standard","hentry","q-acat-emerging-technology","q-acat-identity-access-governance"],"acf":[],"yoast_head":"\n
How can an enterprise achieve analytic agility with big data? - Techopedia<\/title>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n