{"id":31461,"date":"2023-01-24T06:00:00","date_gmt":"2023-01-24T14:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=31461"},"modified":"2023-01-23T14:46:22","modified_gmt":"2023-01-23T22:46:22","slug":"mit-experts-on-what-you-need-to-know-now-about-data-analytics","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/01\/24\/mit-experts-on-what-you-need-to-know-now-about-data-analytics\/","title":{"rendered":"MIT Experts on What You Need to Know Now about Data Analytics"},"content":{"rendered":"
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Data drives efficiencies, increases profitability, and bolsters innovation. Yet analytics skills remain outside the wheelhouse of many business leaders, who don\u2019t always have a clear view of what data sources and analyses are necessary to formulate the insights they are seeking.<\/p>\n\n\n\n

In a new series, “The Analytics Edge<\/a>,” published by MIT Sloan School of Management\u2019s\u00a0Ideas Made to Matter<\/em><\/a>, MIT Sloan faculty, alumni, and industry experts share practical tips for developing and cultivating a strong analytics practice designed to give companies and organizations a distinct advantage for the future.<\/p>\n\n\n\n

Data literacy for leaders<\/strong><\/a><\/p>\n\n\n\n

While data scientists may be in demand, data literacy starts with leaders who trust and understand data enough to make their best business decisions. For optimal success, leaders must also drive literacy efforts throughout their organization to create a culture of trust in data. MIT Sloan data experts share how best to move forward. <\/p>\n\n\n\n

Featuring:<\/strong> Barbara Wixom<\/a>, principal research scientist, the MIT Center for Information Systems Research<\/a>; and Rama Ramakrishnan<\/a>, MIT Sloan professor of the practice, data science and applied machine learning. <\/p>\n\n\n\n

Try this data framework for analytics advantage<\/strong><\/a><\/p>\n\n\n\n

Dimitris Bertsimas<\/a>, associate dean of the Master of Business Analytics<\/a> degree program at MIT Sloan, has developed an approach to help nontechnical business users to gain confidence using data to improve their decision-making. Bertsimas, a professor of operations research, lays out an analytics framework designed to help businesspeople determine which analytics approach is best suited for their application while improving their ability to leverage big data for better business outcomes. The framework is built upon data, models, decisions, and value, with an emphasis on decision-making. <\/p>\n\n\n\n

In-demand data and analytics skills to hire for now<\/strong><\/a><\/p>\n\n\n\n

Hiring managers from Netflix, Pfizer, Comcast and MFS Investment Management share their \u201cmust-have\u201d lists when it comes to hiring for data and analytics roles. In this article, they discuss essential technical skills and soft skills, and finding the elusive \u201csuper unicorn\u201d data scientist.<\/p>\n\n\n\n

Featuring:<\/strong> Trace Hawkins<\/a>, senior vice president of strategic analytics at Comcast; Jonathan Lowe<\/a>, data science lead for Pfizer\u2019s PGS Operations Insights; Nadine Kawkabani<\/a>, global business strategy director at MFS Investment Management; and Yichen Sun<\/a>, (MIT SM \u201913), data science manager at Netflix. <\/p>\n\n\n\n

What is synthetic data \u2014 and how can it help you competitively<\/strong><\/a><\/p>\n\n\n\n

Technological research and consulting firm Gartner estimates<\/a> that 60% of the data used in artificial intelligence and analytics projects will be synthetically generated by 2024. Indeed, synthetic data offers the opportunity to test new ideas and develop new products without putting personal or health data at risk, preserving the correlations among data variables. This article explores MIT research into the topic and how to apply it to your company. It also provides access to a free Synthetic Data Vault to guide organizations in building their own synthetic data sets.<\/p>\n\n\n\n

Featuring:<\/strong> Kaylan Veeramachaneni<\/a>, principal research scientist, the MIT Laboratory for Information and Decision Systems<\/a>; Ali Jahanian<\/a>, former AI research scientist in MIT CSAIL<\/a> and senior applied scientist at Amazon. <\/p>\n\n\n\n

How to build an effective analytics practice: 7 insights from MIT experts<\/strong><\/a><\/p>\n\n\n\n

From designing intelligent decision processes to tapping the full power of deep learning, faculty members who teach in MIT Sloan\u2019s Master of Business Analytics<\/a> degree program share mistakes to avoid, strategies to adopt, and technological developments that excite them most that can be applied to your business practices.<\/p>\n\n\n\n

Featuring<\/strong>: Dean Eckles<\/a>, MIT Sloan associate professor and affiliate faculty at the MIT Institute for Data, Systems & Society in the Schwarzman College of Computing<\/a>; Daniel Freund<\/a>, MIT Sloan assistant professor, operations management; associate professor of operations management; Alexandre Jacquillat<\/a>, MIT Sloan assistant professor, operations research and statistics; Retsef Levi<\/a>, MIT Sloan professor, operations management; Jordan Levine<\/a>, MIT Sloan lecturer, operations research and statistics; Rama Ramakrishnan<\/a>, MIT Sloan professor of the practice, data science and applied machine learning; and  Karen Zheng<\/a>, MIT Sloan associate professor, operations management. <\/p>\n\n\n\n

About\u00a0Ideas Made to Matter<\/em><\/strong><\/p>\n\n\n\n

Launched in 2018, MIT Sloan\u2019s\u00a0Ideas Made to Matter<\/em><\/a>\u00a0brings the work, ideas, and insights of MIT Sloan experts to global business leaders. The platform\u2019s journalists report on topics at the intersection of management and technology, including novel and effective use of data and analytics within organizations; navigating the digital economy; and leading organizations in an era when technology is changing how we work.\u00a0<\/p>\n\n\n\n

Ideas Made to Matter<\/em>\u00a0publishes on the MIT Sloan website, MIT Sloan social media channels, and in the\u00a0Thinking Forward<\/em>\u00a0newsletter<\/a>, delivered every Tuesday morning. To view new articles, please visit\u00a0Ideas Made to Matter<\/em><\/a>. <\/p>\n\n\n\n

Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n\n\n\n

Join us on LinkedIn: https:\/\/www.linkedin.com\/company\/insidebigdata\/<\/a><\/em><\/p>\n\n\n\n

Join us on Facebook: https:\/\/www.facebook.com\/insideBIGDATANOW<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

In a new series, “The Analytics Edge,” published by MIT Sloan School of Management\u2019s\u00a0Ideas Made to Matter, MIT Sloan faculty, alumni, and industry experts share practical tips for developing and cultivating a strong analytics practice designed to give companies and organizations a distinct advantage for the future.<\/p>\n","protected":false},"author":10513,"featured_media":17682,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[65,115,180,268,56,97,1],"tags":[314,280,710,96],"acf":[],"yoast_head":"\nMIT Experts on What You Need to Know Now about Data Analytics - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2023\/01\/24\/mit-experts-on-what-you-need-to-know-now-about-data-analytics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MIT Experts on What You Need to Know Now about Data Analytics - 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Meanwhile, the revenue share of the top 5% of businesses has increased 10 percentage points since the 1980s.\u2026","rel":"","context":"In "Big Data"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":17681,"url":"https:\/\/insidebigdata.com\/2017\/04\/22\/mit-sloan-professor-builds-new-meta-analysis-method-help-settle-unresolved-debates\/","url_meta":{"origin":31461,"position":3},"title":"MIT Sloan Professor Builds New Meta-analysis Method to Help Settle Unresolved Debates","date":"April 22, 2017","format":false,"excerpt":"Science progresses when researchers build on prior work to extend, test, and apply theories. Aggregating the quantitative findings from prior research \u2013 meta-analysis -- plays a significant role in advancing science, however current techniques have limitations. They assume prior studies share similar substantive factors and designs, yet many studies are\u2026","rel":"","context":"In "Big Data"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":24623,"url":"https:\/\/insidebigdata.com\/2020\/06\/19\/how-to-produce-cleaner-data-for-robust-pricing\/","url_meta":{"origin":31461,"position":4},"title":"How to Produce Cleaner Data for Robust Pricing","date":"June 19, 2020","format":false,"excerpt":"In this contributed article by MIT Sloan School of Management Prof. Negin Golrezaei, found that there are ways to limit price manipulation. The key is the pricing algorithm. Instead of using bids to directly set prices, a prominent group of researchers designed an algorithm that uses censored bids\u2013 in this\u2026","rel":"","context":"In "Analytics"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":21544,"url":"https:\/\/insidebigdata.com\/2018\/12\/13\/online-courses-data-driven-decision-making\/","url_meta":{"origin":31461,"position":5},"title":"Can Online Professional Development Courses Teach Data-Driven Decision Making?","date":"December 13, 2018","format":false,"excerpt":"MIT xPRO\u2019s Data Science program is segmented into six modules, each lead by a faculty member with expertise, research and teaching experience in that area. After just seven weeks, learners earn an MIT Professional Certificate in Data Science. 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