Types of problems would you use big data analysis

 

         1.     What types of problems would you use big data analysis for?





Data science dares to ask further questions, looking at unstructured “big data” derived from millions of sources and nontraditional mediums such as text, video, and images. This allows companies to make better decisions based on its customer data. Here, we look at two real-world examples of how data science drives business innovation across various industries and solves complex problems.

 

                Data science revolutionizes sports analytics.

 Over the past few years, the Strategic Innovations Group at the consulting firm Booz Allen Hamilton has been doing just that — working to transform the way teams utilise data. Using data science and machine learning tactics, Booz Allen’s team developed an application for MLB coaches to predict any pitcher’s throw with up to 75% accuracy, changing the way that teams prepare for a game. Looking at all pitchers who had thrown more than 1,000 pitches, the team developed a model that considers current at-bat statistics, in-game situations, and generic pitching measures to predict the next pitch.

                Nonprofits solve the most pressing social issues with data.

 Founded in 2014, San Francisco-based Bayes Impact is a group of experienced data scientists assisting nonprofits in tackling some of the world’s heaviest data challenges. Since it’s founding, Bayes has helped the U.S. Department of Health make better matches between organ donors and those who need transplants, worked with the Michael J. Fox Foundation to develop better data science methods for Parkinson’s research, and created methods to help detect fraud in microfinance. Bayes is also developing a model to help the City of San Francisco harness data science to optimize essential services like emergency response rates. Through organizations like Bayes, data science has the power to make a significant social impact in our data-driven world.

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