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Data science unit2
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Data science

  1. 1. Data Science
  2. 2. Overview o Data ? o What is Data Science? o What’s the need of Data science? o Where does this data come from? o Who are Data Scientists o Case study
  3. 3. Data :- is a collection of facts, such as numbers, words, measurements, observations or just descriptions of things.
  4. 4. What is Data Science? Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information. The goal of data science is to gain insights and knowledge from any type of data — both structured and unstructured. Data science is often confused with data mining. However, data mining is a subset of data science. It involves analyzing large amounts of data (such as big data) in order to discover patterns and other useful information. Data science covers the entire scope of data collection and processing. Data Science VS Data Mining
  5. 5. ● IBM predicted that demand for data scientists will soar by 28% by 2022 ● Data scientist roles have grown over 650% since 2012, but currently, 35,000 people in the US have data science skills, while hundreds of companies are hiring for those roles. ● Software engineering is a common starting point for professionals who are in top five fasting growing jobs today. The career path to Machine Learning Engineer and Big Data Developer begins with a solid software engineering background. ● Data Science gives you career flexibility Why the hype Around Data Science
  6. 6. 1. Why data science ? 2. Why do we need Data science ? 3. What is Data Science useful for?
  7. 7. The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and insights from the data Data Science is a very recent terminology . Before Data Science, we had statisticians. These statisticians experienced in qualitative analysis of data and companies employed them to analyze their overall performance and sales. 1.
  8. 8. From business to the health industry, science to our everyday lives, marketing to research, in fact, for everything in a fraternity, data is required to thrust the movement forward. Computer science and information technology have taken over our lives, and it is advancing with each passing day with such velocity and variety that the operational techniques used a few years back have now become obsolete. Every field of science and study or organization, therefore, needs an updated set of operational systems and technology to keep up with the challenges of today and tomorrow as well as to derive solutions for unanswered questions. 2.
  9. 9. o Data is the key component for every business, as businesses need it to analyze their current scenario based on past facts and performance and make decisions for future challenges. o They need data to survive in today’s competitive market and mature their decision-making power, which would enhance their productivity and profitability. o Today, data science is the requirement of every business to make business forecasts and predictions based on facts and figures, which are collected in the form of data and processed through data science. Data Science for Business 3.
  10. 10. Data Science for Medical Research • The medical science industry also thrives on data science as it has also provided solutions for long-standing complexities. In recent years, there has been an immense increase in deadly disease outbreaks and new fatal viruses due to pollution, unsafe and unhealthy practices, and improper diet, etc. • The scientists can research new medicines and study their possible outcomes on the human compositional basics. Data science has powered the data to be turned into visualizations and graphical presentations to study the patterns of behavior and course of actions of many unseen components of the human body. It helps scientists find a cure for diseases that had no possible treatment in the past.
  11. 11. Data Science for Social Media Data science implications and integration on social media websites and public socializing platforms have taken the process of datification to another level. Most of the data of consumer behavior, choices, and preferences are being collected through online platforms, which help the business grow.
  12. 12. “Big Data” Sources Every: Click Ad impression Billing event Fast Forward, pause,… Server request Transaction Network message Fault … User Generated (Web & Mobile) …. . Internet of Things / M2M Health/Scientific Computing It’s All Happening On- line Big Data is a collection of data that is huge in volume, yet growing exponentially with time.
  13. 13. “Data is the New Oil” – World Economic Forum 2011
  14. 14. What can you do with the data? Traffic Prediction and Earthquake Warning 18 Crowdsourcing + physical modeling + sensing + data assimilation to produce:
  15. 15. Who are Data Scientists?
  16. 16. A Data Scientist is the Adult version of kid who cant stop Asking “WHY?” - Russ Thompson Senior Research Scientist at Alexa
  17. 17. • There are several definitions available on Data Scientists. In simple words, a Data Scientist is one who practices the art of Data Science. • Data scientists are those who crack complex data problems with their strong expertise in certain scientific disciplines. They work with several elements related to mathematics, statistics, computer science, etc
  18. 18. Data Science: Case Study NETFLIX One of the best ways to explain the benefits of data science to people who don’t quite grasp the industry is by using Netflix-focused examples. • Yes, Netflix is the largest internet- television network in the world. But what most people don’t realize is that, at its core, Netflix is a customer-focused, data- driven business. • Founded in 1997 as a mail-order DVD company, it now boasts more than 53 million members in approximately 50 countries.
  19. 19. Some Interesting Facts about Netflix(source) — •Despite more competition, Netflix still has the largest subscriber count in 2020 •60 million US adults have a Netflix subscription •The company is older than most users realize •41% of Netflix users are watching without paying thanks to password and account sharing •Netflix was one of the first streaming services available as an app on different devices 📺
  20. 20. Conclusion • Data science is vital in almost every field. It needs to develop and progress within its systems to handle emerging issues in every industry, business, and organization. The system which solves problems should be advanced enough to provide simple solutions • This will also have the need for data scientists, data engineers, and data analysts in the market. Data scientists will even be further high demand. There is also the scope for the educational institutions to provide expansion and planning to serve the vehement outburst of interest in data science and design academic programs accordingly.
  21. 21. THANK YOU BY:- Deeksha Srivas

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