Data science

Data science

1. ¿What is data science?

   • Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data. These insights can be used to guide decision making and strategic planning.

2. ¿What is the difference between Data Science and Data Analytics?

   • While Data Science focuses on finding meaningful correlations between large datasets, Data Analytics is designed to uncover the specifics of extracted insights. In other words, Data Analytics is a branch of Data Science that focuses on more specific answers to the questions that Data Science brings forth.

3. ¿Where are each of them applied?

   • Data Science — Math, Advanced Statistics, Predictive Modelling, Machine Learning, Programming along with – Proficiency in using big data tools like Hadoop and Spark Expertise in SQL and NoSQL databases like Cassandra and MongoDB Experience with data visualization tools like QlikView, D3.js, and Tableau. Dexterity in programming languages like Python, R, and Scala.
   • Data Analytics — Knowledge of Intermediate Statistics and excellent problem-solving skills along with Dexterity in Excel and SQL database to slice and dice data. Experience working with BI tools like Power BI for reporting Knowledge of Stats tools like Python, R or SAS

4. ¿What knowledge and / or skills do you need to be a data scientist or data analyst?

   • Data Analyst Responsibilities. In both the data science and data analysis fields, professionals need to be comfortable with data management, information management, spreadsheets, and statistical analysis. They must manipulate and structure data in a way that is useful and understandable to business stakeholders.

5. Relationship with the movies

   • The big short
     • The relationship between the movie "The big short" and the data and the data analysys is that, with the help ot those rechources the principal characters can improve and analyze the market and with that information they can know when the market was fallen, so, with those rechources they can make an algorytm and understand the market
   • Margin Call
     • Margin Call is based on the 2007-2008 financial crisis. In the film, volatility levels in mortgage-backed securities are exceeding historical levels. This means that the firm's position in those assets is dangerously overleveraged and a decline in their value large enough to cause the firm's bankruptcy could occur in the near future.So the relationship in this movie between data science and data analysis because with the information they can understand the market and made actions to prevent the failure of the market that happens at 2008