You have read about the power of Data Science and how it is being used in our daily lives at an increasing rate. Businesses make use of data science and analytics to help them find solutions to various business problems. The healthcare industry makes use of data science to provide better care to their patients. It is being used to make predictions regarding COVID-19 and stock market analysis too. Let us learn more about the latest advances in the field of Data Science and Analytics over the past week.
“Big Data and Big Fight”, an east zone webinar organized by Express Computer in association with SAS saw eminent speakers from various east and northeast states. It was held on July 23, 2020, in light of sharing experiences of handling the pandemic. The main aim of the webinar was to understand the best practices followed by various states and how they handled the COVID-19 pandemic. They talk about how they used data analytics and predictive analysis to increase their effectiveness and help in preventing the spread of the deadly virus.
The keynote speaker of the webinar was Mrinalini Shrivastava, who is the Secretary of the Department of Information Technology. The state of Sikkim says that they were able to detect the presence of the virus back in January and had started efforts to strengthen the healthcare facilities. They also leveraged predictive analysis to train end-users about the situation of COVID-19. The state stopped allowing foreigners in February and sealed the state borders to help in preventing the spread.
Data Science can be used to give us a unique perspective on how we understand the stock market and financial data. Certain basic principles are followed during trading, such as sell, buy, or hold. Our main goal is to make high profits. Various trading platforms are becoming increasingly popular. It is important to understand certain key concepts in Data Science for you to be able to determine whether it is worth investing in a particular stock and perform stock market analysis.
Data Science relies heavily on forecasting future outcomes and data modeling. In the stock market, a time series model is used to predict the rise and fall of share prices. Classification models, algorithms, training, and testing are a few other concepts that are used.
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