美国数据科学与商业分析硕士 - 知乎专栏
{"debug":false,"apiRoot":"","paySDK":"/api/js","wechatConfigAPI":"/api/wechat/jssdkconfig","name":"production","instance":"column","tokens":{"X-XSRF-TOKEN":null,"X-UDID":null,"Authorization":"oauth c3cef7c66aa9e6a1e3160e20"}}
{"database":{"Post":{"":{"contributes":[{"sourceColumn":{"lastUpdated":,"description":"留学路上，让你易知易行","permission":"COLUMN_PUBLIC","memberId":,"contributePermission":"COLUMN_PUBLIC","translatedCommentPermission":"all","canManage":true,"intro":"汇聚国内Top 1%留学咨询师，让申请不再有信息差","urlToken":"eknowns","id":19656,"imagePath":"v2-8754fbf069a7fdb810b7bf1.jpg","slug":"eknowns","applyReason":"0","name":"留学可以很简单","title":"留学可以很简单","url":"/eknowns","commentPermission":"COLUMN_ALL_CAN_COMMENT","canPost":true,"created":,"state":"COLUMN_NORMAL","followers":331,"avatar":{"id":"v2-8754fbf069a7fdb810b7bf1","template":"/{id}_{size}.jpg"},"activateAuthorRequested":false,"following":false,"imageUrl":"/v2-8754fbf069a7fdb810b7bf1_l.jpg","articlesCount":47},"state":"accepted","targetPost":{"titleImage":"/e3f0a9265ecfae3e1b85e_r.jpg","lastUpdated":,"imagePath":"e3f0a9265ecfae3e1b85e.jpg","permission":"ARTICLE_PUBLIC","topics":[,63708],"summary":"提到数据科学，一定要介绍的学校当然是北卡罗来纳州立大学，作为最早开设数据分析硕士的学校，他们甚至主动调研其他美国院校的相关项目，详见。但是这份名单中包含了所有的full-time、part-time和online的项…","copyPermission":"ARTICLE_COPYABLE","translatedCommentPermission":"all","likes":0,"origAuthorId":0,"publishedTime":"T17:43:52+08:00","sourceUrl":"","urlToken":,"id":1137139,"withContent":false,"slug":,"bigTitleImage":false,"title":"美国数据科学与商业分析硕士","url":"/p/","commentPermission":"ARTICLE_ALL_CAN_COMMENT","snapshotUrl":"","created":,"comments":0,"columnId":19656,"content":"","parentId":0,"state":"ARTICLE_PUBLISHED","imageUrl":"/e3f0a9265ecfae3e1b85e_r.jpg","author":{"bio":"为你挑选，行业Top1%的留学咨询师（）","isFollowing":false,"hash":"1fffbbbf0e6f7","uid":564700,"isOrg":false,"slug":"yi-zhi-xing-qiu","isFollowed":false,"description":"在易知星球找顾问，不需要碰运气。\n只为学生挑选，留学行业内Top1%的咨询师，提供从全程申请到单项定制的多元化服务。","name":"易小星","profileUrl":"/people/yi-zhi-xing-qiu","avatar":{"id":"v2-c98f64db5ea","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},"memberId":,"excerptTitle":"","voteType":"ARTICLE_VOTE_CLEAR"},"id":429064}],"title":"美国数据科学与商业分析硕士","author":"yi-zhi-xing-qiu","content":"提到数据科学，一定要介绍的学校当然是北卡罗来纳州立大学，作为最早开设数据分析硕士的学校，他们甚至主动调研其他美国院校的相关项目，详见。但是这份名单中包含了所有的full-time、part-time和online的项目，并不适合国内的学生，于是小编重新整理了前100中国际生可申请的项目，并按照大家习惯的综合排名进行排序。另外，想了解数据科学和商业分析到底是学什么的，可以参考NYU的以及IBM的。Harvard University：University of Chicago：Columbia University： or Stanford University：Massachusetts Institute of Technology：Duke University：Northwestern University：Washington University in St. Louis：Cornell University：Georgetown University：Carnegie Mellon University： or University of Southern California： or University of Virginia：Wake Forest University：New York University：University of Rochester： or
College of William and Mary：Georgia Institute of Technology：Case Western Reserve University：University of California—San Diego：University of Illinois—Urbana-Champaign：Rensselaer Polytechnic Institute：University of Miami：University of Texas—Austin：University of Washington：Pepperdine University：George Washington University： or Worcester Polytechnic Institute：University of Maryland—College Park：University of Connecticut：Purdue University—West Lafayette：Southern Methodist University： or Fordham University：University of Minnesota—Twin Cities： or American University：Indiana University—Bloomington：Michigan State University：Stevens Institute of Technology：University of Iowa：North Carolina State University—Raleigh：更多干货，敬请关注，或者我们的微信公号：易知星球。","updated":"T09:43:52.000Z","canComment":false,"commentPermission":"anyone","commentCount":16,"collapsedCount":0,"likeCount":121,"state":"published","isLiked":false,"slug":"","lastestTipjarors":[],"isTitleImageFullScreen":false,"rating":"none","titleImage":"/e3f0a9265ecfae3e1b85e_r.jpg","links":{"comments":"/api/posts//comments"},"reviewers":[],"topics":[{"url":"/topic/","id":"","name":"留学美国"},{"url":"/topic/","id":"","name":"商业分析"},{"url":"/topic/","id":"","name":"大数据"}],"adminClosedComment":false,"titleImageSize":{"width":620,"height":260},"href":"/api/posts/","excerptTitle":"","column":{"slug":"eknowns","name":"留学可以很简单"},"tipjarState":"activated","tipjarTagLine":"希望对大家有帮助哦~","sourceUrl":"","pageCommentsCount":16,"tipjarorCount":0,"annotationAction":[],"hasPublishingDraft":false,"snapshotUrl":"","publishedTime":"T17:43:52+08:00","url":"/p/","lastestLikers":[{"bio":"时差党","isFollowing":false,"hash":"e6fbff89397fcce204cdc6c733e67400","uid":224000,"isOrg":false,"slug":"jing-yue-92-16","isFollowed":false,"description":"","name":"憬阅","profileUrl":"/people/jing-yue-92-16","avatar":{"id":"adb1ada9e2d411ac00fab35","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},{"bio":"我肯定不是最差的。","isFollowing":false,"hash":"0ddb7fe69a1e","uid":32,"isOrg":false,"slug":"tan-xu-xuan","isFollowed":false,"description":"或许并不是一无是处的人。","name":"王八十八一斤","profileUrl":"/people/tan-xu-xuan","avatar":{"id":"b","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},{"bio":null,"isFollowing":false,"hash":"9d70c10f60c694cba854e","uid":865000,"isOrg":false,"slug":"aa-kenn","isFollowed":false,"description":"","name":"aa kenn","profileUrl":"/people/aa-kenn","avatar":{"id":"bf5cdf02cd5c9efb572a1","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},{"bio":"用一生作赌注。","isFollowing":false,"hash":"1ce5f563cebef332f06932","uid":937200,"isOrg":false,"slug":"cao-mei-wei-de-shao-nv-z","isFollowed":false,"description":"努力考研的出国党","name":"草莓味的少女z","profileUrl":"/people/cao-mei-wei-de-shao-nv-z","avatar":{"id":"v2-affdf599d35d824dcac60","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},{"bio":"学生","isFollowing":false,"hash":"0fe6d047c55b529b607bd0","uid":278000,"isOrg":false,"slug":"yin-ye-70-49","isFollowed":false,"description":"","name":"茵爷","profileUrl":"/people/yin-ye-70-49","avatar":{"id":"da8e974dc","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false}],"summary":"提到数据科学，一定要介绍的学校当然是北卡罗来纳州立大学，作为最早开设数据分析硕士的学校，他们甚至主动调研其他美国院校的相关项目，详见。但是这份名单中包含了所有的full-time、part-time和online的项…","reviewingCommentsCount":0,"meta":{"previous":null,"next":{"isTitleImageFullScreen":false,"rating":"none","titleImage":"/50/e4b51a09fdab_xl.jpg","links":{"comments":"/api/posts//comments"},"topics":[{"url":"/topic/","id":"","name":"金融工程学"},{"url":"/topic/","id":"","name":"留学"},{"url":"/topic/","id":"","name":"金融"}],"adminClosedComment":false,"href":"/api/posts/","excerptTitle":"","author":{"bio":"为你挑选，行业Top1%的留学咨询师（）","isFollowing":false,"hash":"1fffbbbf0e6f7","uid":564700,"isOrg":false,"slug":"yi-zhi-xing-qiu","isFollowed":false,"description":"在易知星球找顾问，不需要碰运气。\n只为学生挑选，留学行业内Top1%的咨询师，提供从全程申请到单项定制的多元化服务。","name":"易小星","profileUrl":"/people/yi-zhi-xing-qiu","avatar":{"id":"v2-c98f64db5ea","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false},"column":{"slug":"eknowns","name":"留学可以很简单"},"content":"注：原文来自QuantNet作者Peter Wagner，曾任摩根斯坦利和雷曼兄弟高管。小编特意翻译成中文，并于文末总结附赠生僻词汇和词组搭配，以供大家学习。Since writing for this blog in January about the HFT/algo job market, I’ve received many inquiries from students asking about the “requirements” for quant jobs on Wall Street. “Do I need a PhD?” is a frequent question. Each time I receive one of these inquiries, I struggle with the answer. 自从写了有关高频算法交易的就业市场的博客后，我收到了很多学生的询问，他们问我华尔街的“宽客”工作要求。其中一个常见问题就是“我需要PhD学位么？”每次收到这样的问题，我都要思躇良久。My instinct is no. But when I look at who is working in these jobs, I do see a predominance of PhD’s in the top positions. PhD’s in mathematics, physics, operations research, EE, etc. are common in the quant community. So it’s tempting to tell students that a PhD is helpful, but it feels like the wrong answer. 我的本能会说不，但是当我着眼于宽客岗位上的人时，的确会发现PhD学位在顶部职位的显著优势。在宽客群体中，拥有数学、物理、运筹、电子工程等专业的PhD学位是很普遍的。因此，答案倾向于告诉学生PhD是有帮助的，但是这个答案感觉起来又是错误的。In my gut I know that the people getting these jobs are not getting offers because they have extra letters after their name. The people in these positions are there because they have proved over their academic and professional lives that they are:我的直觉告诉我，得到宽客工作的人不是因为他们的名字后多了什么学位头衔，而是因为他们在学术和职业生涯中证明了他们具有以下的品质：Very smartQuantitative thinkersGood at figuring things out with minimal guidanceDedicated非常聪明；量化思维者；善于在最少的指导下解决问题；专注。But the above is a generic list of attributes for hiring into just about any job. So what is it that makes someone hirable as a quant? The list isn’t long:但是以上这些特征适用于任何工作。究竟什么特征才能让人胜任宽客工作呢？这份特征的名单也不长：Education in advanced math (stochastic calculus, statistics, probability, etc.)Good software development skillsGood data analysis skills具备高级的数学方面教育（例如随机微积分，统计学，概率论等）；擅长软件开发；优良的数据分析能力。Okay, now combine the two lists, and you have the list of qualifications for a quant.结合这两份名单，你就可以知道成为宽客的必要条件了。So, back to the question of whether to get a PhD. Should I get a PhD?, asks one student who is angling for a career in quantitative finance. Will it help me? Is it necessary? No, it’s definitely not necessary. Will it help? Empirically, it seems to help. But does it? I’ve finally come to clarity on the subject with the help of a conversation today with the director of a quant group supporting credit trading for a major investment bank.回到要不要拿到PhD学位的问题。PhD是必需的么？肯定不是。PhD有帮助么？经验上来看，似乎是有帮助，但果真如此么？我和一个负责投行信用交易支持的宽客组主管聊了这个问题，最终我有了清晰的答案。Of the two lists above, the important qualifications are on the first list. This list has nothing to do with your education. Your success in any field depends on the first list. The 2nd list consists of skills, skills that can come from your education or experience. They are enabling skills, but they are not dictators of success. All career success comes from differentiating oneself with respect to the elements on the first list. You can get a PhD, spend the money and the time, but if you don’t differentiate yourself in the fundamental elements of success, the PhD won’t help.在上面两个名单中，更重要的是第一个名单里面的品质特征。这份名单与你的教育无关，而你在任何领域取得成功都依赖于这份名单。第二份名单都是些技能，而技能来自于你的教育和经历，它们能够让你有能力胜任工作，但是却不是成功的缔造者。所有的职业成功都依赖于第一份名单的因素。你可以花费时间和金钱去读PhD，但是如果你不具备成功的根本因素，PhD学位也帮不了你。So why are there so many PhD’s in quantitative roles, anyway? I think the answer is pretty obvious. Very smart people with quantitative instincts are drawn to the PhD path. Later they find that they are well suited to a career in finance. They satisfy both lists and hence are successful in quantitative roles in finance. Almost without exception, these are individuals who pursued a PhD based on their interests and passions (EE, Physics, Applied Math, etc.), not people who pursued a PhD as a means to a job in finance. QED: A PhD is not a requirement for a career as a quant in finance.那为什么宽客中有这么多PhD呢？我觉得答案很明显。非常聪明而且有量化直觉的人自身向往去读PhD。然后他们发现，他们非常适合在金融业工作。他们同时满足上面两个名单，因此才会在量化金融领域取得成功。几乎毫无例外地，这些人读PhD是因为兴趣和热情，而不是因为想把PhD当做进入金融业的手段。证毕：PhD学位不是从事金融宽客的必需品。I feel this article isn’t complete without addressing the MFE degree. The MFE provides students with the fundamental skills utilized in quantitative jobs. If you can afford it, it’s an easy way to satisfy List 2. However, it’s by no means a ticket to success in quantitative finance. I’ll explore the MFE further in my next post, “The MFE, Is it a Contra-indicator?”我觉得如果不谈一下金融工程硕士学位，这篇文章就不完整。金工硕士学位可以提供给学生量化工作中要用到的基本技能。如果你能够负担起学费，这会是一个捷径来满足第二个名单，但它绝不是通往量化金融成功的门票。文末小结PhD学位并不是在金工领域取得成功的原因，只不过宽客天才因为喜欢顺便读了个PhD而已。想要取得成就，无论什么行业，都要做到专注、量化思维和善于解决问题，当然还要有聪明的天赋。HFT/algo：HFT是High Frequency Trading的缩写，即高频交易；algo是Algorithmic Trading的缩写，即算法交易。quant：宽客，指从事量化金融/计算金融工作的人，其工作就是设计并实现金融的数学模型（主要采用计算机编程）。predominance：n. 优势；卓越 empirically：adv. 以经验为主地；经验主义地in my gut：在我看来；凭我直觉figuring ... out：解决；算出；想出；理解；断定angle for：谋取；追逐；试图得到 differentiate ... with respect to：数学里用来表示求导，differentiate f(x) with respect to xbe drawn to：被…所吸引without exception：一律；毫无例外地by no means：决不；毫不；一点也不","state":"published","sourceUrl":"","pageCommentsCount":0,"canComment":false,"snapshotUrl":"","slug":,"publishedTime":"T11:56:52+08:00","url":"/p/","title":"学习金融工程真的需要PhD学位么？","summary":"注：原文来自QuantNet
作者Peter Wagner，曾任摩根斯坦利和雷曼兄弟高管。小编特意翻译成中文，并于文末总结附赠生僻词汇和词组搭配，以供大家学习。Since writing for this blog in January about the HFT/algo job…","reviewingCommentsCount":0,"meta":{"previous":null,"next":null},"commentPermission":"anyone","commentsCount":0,"likesCount":2}},"annotationDetail":null,"commentsCount":16,"likesCount":121,"FULLINFO":true}},"User":{"yi-zhi-xing-qiu":{"isFollowed":false,"name":"易小星","headline":"在易知星球找顾问，不需要碰运气。\n只为学生挑选，留学行业内Top1%的咨询师，提供从全程申请到单项定制的多元化服务。","avatarUrl":"/v2-c98f64db5ea_s.jpg","isFollowing":false,"type":"people","slug":"yi-zhi-xing-qiu","bio":"为你挑选，行业Top1%的留学咨询师（）","hash":"1fffbbbf0e6f7","uid":564700,"isOrg":false,"description":"在易知星球找顾问，不需要碰运气。\n只为学生挑选，留学行业内Top1%的咨询师，提供从全程申请到单项定制的多元化服务。","profileUrl":"/people/yi-zhi-xing-qiu","avatar":{"id":"v2-c98f64db5ea","template":"/{id}_{size}.jpg"},"isOrgWhiteList":false,"badge":{"identity":null,"bestAnswerer":null}}},"Comment":{},"favlists":{}},"me":{},"global":{"experimentFeatures":{"ge3":"ge3_9","ge2":"ge2_1","nwebStickySidebar":"sticky","nwebAnswerRecommendLive":"newVersion","newMore":"new","sendZaMonitor":"true","liveReviewBuyBar":"live_review_buy_bar_2","liveStore":"ls_a2_b2_c1_f2","homeUi2":"default","answerRelatedReadings":"qa_recommend_by_algo_related_with_article","qrcodeLogin":"qrcode","newBuyBar":"liveoldbuy","newMobileColumnAppheader":"new_header","zcmLighting":"zcm","favAct":"default","appStoreRateDialog":"close","mobileQaPageProxyHeifetz":"m_qa_page_nweb","iOSNewestVersion":"4.2.0","default":"None","wechatShareModal":"wechat_share_modal_show","qaStickySidebar":"sticky_sidebar","androidProfilePanel":"panel_b"}},"columns":{"next":{},"eknowns":{"following":false,"canManage":false,"href":"/api/columns/eknowns","name":"留学可以很简单","creator":{"slug":"yi-zhi-xing-qiu"},"url":"/eknowns","slug":"eknowns","avatar":{"id":"v2-8754fbf069a7fdb810b7bf1","template":"/{id}_{size}.jpg"}}},"columnPosts":{},"columnSettings":{"colomnAuthor":[],"uploadAvatarDetails":"","contributeRequests":[],"contributeRequestsTotalCount":0,"inviteAuthor":""},"postComments":{},"postReviewComments":{"comments":[],"newComments":[],"hasMore":true},"favlistsByUser":{},"favlistRelations":{},"promotions":{},"switches":{"couldAddVideo":false},"draft":{"titleImage":"","titleImageSize":{},"isTitleImageFullScreen":false,"canTitleImageFullScreen":false,"title":"","titleImageUploading":false,"error":"","content":"","draftLoading":false,"globalLoading":false,"pendingVideo":{"resource":null,"error":null}},"drafts":{"draftsList":[],"next":{}},"config":{"userNotBindPhoneTipString":{}},"recommendPosts":{"articleRecommendations":[],"columnRecommendations":[]},"env":{"edition":{},"isAppView":false,"appViewConfig":{"content_padding_top":128,"content_padding_bottom":56,"content_padding_left":16,"content_padding_right":16,"title_font_size":22,"body_font_size":16,"is_dark_theme":false,"can_auto_load_image":true,"app_info":"OS=iOS"},"isApp":false},"sys":{},"message":{"newCount":0},"pushNotification":{"newCount":0}}有人了解美国的商业数据分析硕士专业吗？ - 知乎340被浏览68491分享邀请回答10219 条评论分享收藏感谢收起3414 条评论分享收藏感谢收起查看更多回答美国商业分析研究生到底在学什么？ - 知乎21被浏览3052分享邀请回答21 条评论分享收藏感谢收起有人了解美国的商业数据分析硕士专业吗？
我的图书馆
有人了解美国的商业数据分析硕士专业吗？
这里有一个网站专门介绍Business Analytics申请的: 以下是其中一篇介绍BA具体学什么的文章， 应该是写的蛮清楚的。Business analytics到底学什么，很多同学都有这个问题，网上有些解释比较笼统，大多也是没读过businessanalytics的人士总结的。我这篇文章用比较通俗易懂的语言，来给大家介绍下businessanalytics到底学什么。Business analytics不仅在国内没有任何大学开设过这个专业，就算是在美国也是最近3年才涌现出来的一个新兴学科。要回答businessanalytics学什么，就要先明白为什么会出现businessanalytics这个专业。Businessanalytics专业的出现，完全是被社会企业用人的需求所倒逼出来的。而这个需求的诞生，归根到底就是三个字：大数据。2007年移动互联网出现后，企业经营的数据大量增加。以前企业用Excel、Word做做财务、市场、运营的分析就可以了，现在出现了大量新的数据可以帮助企业了解消费者、提升运营水平。大家都知道数据是金矿，于是肯定要人去分析这些数据。但以前企业的businessanalyst一看到这样大量的数据就傻眼了。数据往往大到下载到excel里面直接excel爆掉的程度。即使切成小块，动不动几百列的数据，缺乏统计知识的传统businessanalyst完全不知道怎么去分析。于是有的企业说，我们不是有统计专业的同学吗，把他们从生产车间、制药实验室里面拉出来，让他们来分析分析。结果发现统计专业的同学对分析实验结果很在行，对business和市场却是一窍不通。另外，传统的businessanalyst和学统计的同学，面对储存数据的系统、逐渐流行的分析数据的开源软件，也就是计算机方面的东西，明显知识储备不足。但找学计算机的码农来做数据分析，他们对商业和统计知识基本一无所知。也就是说，分析企业中的数据，也就是businessanalytics这个领域，是business、statistics和computerscience三个领域知识的结合。传统的businessanalyst、statistician和码农如果能够合体，才能成为适合新时代的businessanalytics人员。于是企业要求学校，特别是商学院，开设这样的专业，培养对business、统计和计算机都有所掌握的人员，于是businessanalytics孕育而生。看到这里你应该明白了，business analytics要学的东西，就是三个方面：business、统计、计算机。这里的business我不想多做说明，和大家熟知的business的课程是一致的，就是marketing、finance这些。但是统计和计算机，则和传统的统计和计算机教学有很大的差别。我接下来详细讲一下。传统的统计，主要是学习对实验结果做显著性检验，比如一队小白鼠吃药，一队小白鼠不吃药，谁的身体比较好？有没有显著性的差别？以前商业中大量招聘统计专业同学的是市场调研机构：一队消费者看了广告，一队消费者没看广告，谁对品牌认知度高？有没有显著性区别？另外，统计讲究抽样，消费者太多没办法一一访问，于是抽样，于是就要看抽样的合理性。现代企业中的数据分析，可以说和这些传统的统计方法，有了很大的改变。businessanalytics的统计知识，主要是学习如何建立和评估多变量的统计模型，最典型的例子就是回归分析模型。回归分析在传统的统计中，可能只是重要的一块而已，而在businessanalytics的教育中的统计部分，几乎是全部。除了回归分析（包括逻辑回归），其他businessanalytics中要学的统计知识差不多也就是相关系数、时间序列之类，也都是小头。传统统计中的显著性检验、抽样方法，businessanalytics基本不教。所以我看到我去年辅导的学员从UTbusiness analytics毕业了去沃尔玛做senior statistical analyst，我觉得很搞笑。她去考国内统计专业大一的专业课，估计都不懂。只能说沃尔玛其实需要的就是现代的businessanalytics人员，但老title一直没换。接下来说下business analytics要学的计算机知识。计算机博大精深，幸运的是businessanalytics只用学其中可能是最简单的三块：第一就是数据库和SQL，因为企业里面数据都是储存在系统里面的。你要分析数据，首先要知道怎么把数据按照你要的方式提取出来。这就是用SQL写代码提取数据。学校一般不会花很多时间去教你，但是这个是学、做analytics的基础的基础。第二就是学习怎么在统计软件中进行编程。以前提到分析数据，国内最熟悉的是SPSS，像Excel一样妥妥拽拽就行了。但其实美国根本就没人用。现在分析数据的流行工具，必须通过写代码的方式进行操作，最典型的工具就是R和Python。这里的编程，其实是统计编程，和真正编网站的C语言、Java是很不一样的，也容易的多，但是仍是类似的编程思维。第三要学的计算机知识就是现在最流行的机器学习，机器学习基本上是代替和补充前面所说的回归分析等统计模型方法。做的事情几乎是一样的，就是建模，但做的方法是计算机的。不过很多原则其实和统计的回归分析是一样的，也都是用R或者Python的代码来实现，实现起来，不会比回归分析难太多，大家大可放心。说了这么多，我们来举个企业里面数据分析的例子来对应相应business analytics要学的技能。你要分析可口可乐的广告投放是否有作用。传统的businessanalyst说了一堆逻辑，只有简单的数据图表支持。你说，啥年代了，还不拿历史存储的大数据说话？市场调研公司里面的统计专家告诉你应该抽样发问卷调研消费者，你也让他一边去，过去广告投放的时间、区域和销量的变化数据全调出来进行多变量的建模，还搞什么抽样调研。于是你作为businessanalytics的毕业生，首先运用对business、市场的知识对问题进行分析，比如，广告是如何影响销量的？投少了会不会没作用？投多了是不是边际效应递减？除了广告之外，还需要考虑哪些其他的变量？电视、互联网广告，是否有1+1大于2或者小于2的内在联系？商业分析的框架搭好后，就是数据分析了。你首先非常熟悉公司的数据库架构，然后用学过的SQL知识写SQL代码把数据从数据库里按照你的要求提取出来。进行了简单的数据清理整理探索之后，你就开始建立统计回归模型，而这个建模的过程，你都是在R或者Python通过写代码完成的。你可以在R或者Python里面除了回归分析，也试试机器学习，对回归分析进行一个补充，比如检查是否有些变量被回归分析的模型所遗漏。这些也就是在R和Python里面多写几行代码。最后，你run出了模型的结果，你要用你的统计知识对结果进行分析，判断广告到底对销量是如何影响。最后结合你的business的知识，对你的老板进行汇报。以上这些，都是这些年学business analytics、做businessanalytics的总结。
TA的最新馆藏[转]&
喜欢该文的人也喜欢