Introduction to Data Science and its Scope
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The document introduces data science, highlighting its crucial role in converting vast amounts of data into actionable insights using various advanced techniques. It outlines the expected growth in data science careers and market size, along with the significance of Python in enhancing user experiences for major tech companies like Netflix and Google. Additionally, it poses questions related to the components, scope, and impact of data science in modern business environments.
Introduction to Data Science and its Scope
- 1. Introduction to Data Presented By : Lipika Sharma MTech Bits Pilani INTRODUCTION TO DATA SCIENCE 24/5/24
- 2. DATA IS THE NEW OIL In our increasingly connected society, we generate over 328 million terabytes of data daily.
- 3. Types of Data and Information WHAT IS DATA SCIENCE Data science employs mathematics, statistics, computer programming, advanced analytics, artificial intelligence, and machine learning to convert raw data—like the duration of video viewership—into actionable insights, such as market research aimed at retaining viewers for longer periods.
- 4. Types of Data and Information WHY DATA SCIENCE ?????? • According to the US Bureau of Labor Statistics, the number of jobs requiring Data Science skills is expected to grow by 27.9 percent by 2026. • The data science market size is expected to grow from USD 95.3.9 billion in 2021 to USD 322.9 billion by 2026. • According to latest reports, data engineering is one of the fastest-growing domains in technology, with over 88.3 percent growth in job postings. • The average salaries in data science and machine learning jobs are surging sky-high with a data scientist getting USD 176,213, and a data engineer taking home USD 166,992. • According to latest reports by Forbes, 5 percent of all data analytics and data science jobs can be found in IT, finance, insurance and related professional services. • About 80 percent of the firms across the globe are investing a large part of their earnings into creating a skillful data analytics division, thus hiring the smartest of people in the industry domain
- 6. Data Science Process - OSEMN • O – Obtain data • S – Scrub data • E – Explore data • M – Model data • N – Interpret results
- 7. DATA SCIENCE FOR BUSINESS
- 9. What is Python ?
- 10. Why Python ?
- 11. • Python is made even more trustworthy by the fact that it is used by tech giants like Google and Netflix. Even companies like Uber and Dropbox also use Python for more structural programs. Let's look at Python’s utility in these firms: • Netflix utilizes Python to recommend TV shows based on the user's watch history. • Instagram gives users a more unique and personalized explore section using Python. • Spotify enhances its user experience by creating personalized music recommendation lists using Python. • Google has improved its search engine functionality with the help of a Python course created for aspiring developers.
- 12. Q N A
- 13. Q1 Explain what data science is
- 14. Q2 What are the main components of data science?
- 15. Q3 How does data science differ from traditional data analysis?
- 16. Q4 What is the scope of data science in business?
- 17. Q5 Why is data science important in modern business environments?
- 18. Q6 How can data science improve customer experiences?
- 19. Q7 Can you give an example of how a business might use data science for strategic decision-making?