{"id":280,"date":"2021-09-02T00:00:00","date_gmt":"2021-09-02T00:00:00","guid":{"rendered":"https:\/\/tac.debuzzify.com\/?p=280"},"modified":"2023-06-27T06:29:54","modified_gmt":"2023-06-27T06:29:54","slug":"data-science-will-be-democratized","status":"publish","type":"post","link":"https:\/\/www.the-analytics.club\/data-science-will-be-democratized\/","title":{"rendered":"Data Science Will Be Democratized (In Less Than 10 Years)"},"content":{"rendered":"\n
I trust the first profound attempt was in\u00a01985<\/em>. A revolutionary software changed the way we think about data. It allowed ordinary people to do extraordinary data analyses. We call it\u00a0Excel<\/a>, developed by Microsoft initially for Macintosh.<\/p>\n\n\n\n Since then, the field of data science has evolved and become accessible to everyone.<\/p>\n\n\n\n Thanks to this improvement today, everyone enjoys the great benefits of data science. Soon all the remaining barriers will disappear too. <\/p>\n\n\n\n But will the advances in data science lead to the extinction of data scientists<\/a>?<\/p>\n\n\n\n Data literacy and critical thinking is the answer.<\/p>\n\n\n\n Exceptional mathematical skills, programming in more than one language are no longer required. Any high-school kid knows enough mathematics to begin their data science journey.<\/p>\n\n\n\n If you are a research scientist, you may have to. But not many data scientists are inventing new algorithms. Instead, they solve practical problems by using them. For them, algorithms are configurable black boxes.<\/em> Their internals doesn’t matter all the time.<\/p>\n\n\n\n Likewise, you never have to learn programming to become a data scientist. Not anymore. You can use tools such as KNIME, Rapid Miner, AutoML, and Data Robot Instead. They allow you to\u00a0program your logic without a programming language.<\/em><\/p>\n\n\n\n Related: How to Become a Terrific Data Scientist (+Engineer) Without Coding?<\/a><\/em><\/strong><\/p>\n<\/blockquote>\n\n\n\n Case study: The Royal Bank of Canada sets a great example. Their business people excel at data science<\/a>, too, with the latest technologies. Here’s a whitepaper<\/a> that explains their success story.<\/p>\n\n\n\n A lab coat and goggles won’t make a chemist. Likewise, programming skills won’t create data scientists. It’s only a preference.<\/p>\n\n\n\n We spent the last couple of decades in data science, fitting models to real-world problems. We worked hard to make predictions accurate by tuning hyperparameters manually<\/em>. Most of our energy went coding<\/em> them with our bare hands and optimizing<\/em> them to match the computing power.<\/em><\/p>\n\n\n\n But the landscape is changing.\u00a0Hyperparameter tuning<\/em>, which I thought would always remain manual,\u00a0is now\u00a0semi-automated<\/a>. Programming too is getting out of the way with projects such as\u00a0Github Copilot.<\/a><\/p>\n\n\n\n It’s fascinating to think about\u00a0what’s left in data science for our kids.<\/em>\u00a0But there are.\u00a0Their efforts will be focused more on the problem definition rather than solving them. Because\u00a0machines solve their problems if they are well-defined.<\/em><\/p>\n\n\n\n Future generations won’t be fitting models and tuning them for accuracy and performance. Domain experts will take over<\/em> the application, and data scientists will focus on developing the science itself.<\/p>\n\n\n\n It’s the democratization of data science.<\/em> At the current rate, it won’t take another decade to realize it.<\/p>\n\n\n\n Data science becomes accessible to more people every day. Thanks to the rapid improvements in knowledge sharing, infrastructures, open-source software, and access to data, it’s not limited to high-tech companies only.<\/p>\n\n\n\n In the future, the application of data science won’t be the role of a data scientist. Domain experts will handle it themselves with great platforms such as KNIME.<\/p>\n\n\n\n The development of science will be the responsibility of data scientists. But that, too, won’t be the same as even complex things such as hyperparameter tuning and programming are automated.<\/p>\n\n\n\n Thanks for the read, friend. It seems you and I have lots of common interests. Say Hi to me on LinkedIn<\/strong><\/a>, Twitter<\/strong><\/a>, and Medium<\/strong><\/a>. <\/p>\n\n\n\n\n
\n\n\n\nWhat makes a data scientist in the future?<\/h1>\n\n\n\n
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\n\n\n\nYour kids won’t be solving the same problems you do today.<\/h1>\n\n\n\n
\n\n\n\nIn Summary,<\/h1>\n\n\n\n
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