A common educational path is an engineering degree paired with an MBA. They’re leaders, managers, and entrepreneurs, but with a technical bent. “ Cathy O’Neilĥ Data Science team individual data scientist profiles are merged to make a Data science team team profile should align with the profile of the data problems to tackleĬlustering and visualization of data science subfields based on a survey of data science practitioners (Analyzing the Analyzers by Harlan Harris, Sean Murphy, and Marck Vaisman, 2012) Data Businesspeople are the product and profit-focused data scientists. You actually need to know how and why it works, so that when it doesn’t work, you can adjust. Its acolytes possess a practical knowledge of tools and materials, coupled with a theoretical understanding of what’s possible.” Mike Driscoll (CEO of Metamarket) Drew Conway’s Venn diagram of data science Many posers “It’s not enough to just know how to run a black box algorithm. Data science is the civil engineering of data. And data science is not merely statistics, because when statisticians finish theorizing the perfect model, few could read a tab-delimited file into R if their job depended on it. But data science is not merely hacking-because when hackers finish debugging their Bash one-liners and Pig scripts, few of them care about non-Euclidean distance metrics. Presentation on theme: "Introduction to Data Science"- Presentation transcript:Ģ What is Data Science? Data scientists, "The Sexiest Job of the 21st Century" (Davenport and Patil, Harvard Business Review, 2012) Much of the data science explosion is coming from the tech-world What does Data Science mean? Is it the science of Big Data? What is Big Data anyway? Who does Data Science and where? What existed before Data Science came along? Is it simply a rebranding of statistics and machine learning? “Anything that has to call itself a science isn’t.” Hype increases noise-to-signal ratio in perceiving reality and makes it harder to focus on the gems Why and how to hire a data scientist?ģ Why now? massive amounts of data about many aspects of our lives, both online and offline activities, real- time as well as past-time Datafication=“taking all aspects of life and turning them into data” “Once we datafy things, we can transform their purpose and turn the information into new forms of value.” abundance of inexpensive computing power, communication capacity proliferation of small footprint low-power sensors (IoT) feedback loop between our behavior, environment, and data productsĤ Data Science take I “Data science, as it’s practiced, is a blend of Red-Bull-fueled hacking and espresso-inspired statistics.
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