Podcast
Questions and Answers
Which statement best describes data?
Which statement best describes data?
What is the primary process involved in datafication?
What is the primary process involved in datafication?
Data science can be defined as which of the following?
Data science can be defined as which of the following?
Which of the following is NOT a benefit of data science?
Which of the following is NOT a benefit of data science?
Signup and view all the answers
How does data science contribute to creating new industries?
How does data science contribute to creating new industries?
Signup and view all the answers
What is a common application of data in the banking sector?
What is a common application of data in the banking sector?
Signup and view all the answers
Which of the following describes the role of a data scientist?
Which of the following describes the role of a data scientist?
Signup and view all the answers
In what way can social platforms like Facebook utilize data?
In what way can social platforms like Facebook utilize data?
Signup and view all the answers
What is the primary role of a data engineer within an analytics team?
What is the primary role of a data engineer within an analytics team?
Signup and view all the answers
Which of the following is NOT one of the five essential steps for performing data science?
Which of the following is NOT one of the five essential steps for performing data science?
Signup and view all the answers
During the exploratory data analysis (EDA) phase, which technique is used for identifying outliers?
During the exploratory data analysis (EDA) phase, which technique is used for identifying outliers?
Signup and view all the answers
What is the first step in the data science process?
What is the first step in the data science process?
Signup and view all the answers
Which of the following could be considered a source of data when attempting to answer a data science question?
Which of the following could be considered a source of data when attempting to answer a data science question?
Signup and view all the answers
What is the purpose of plotting distributions of all variables during EDA?
What is the purpose of plotting distributions of all variables during EDA?
Signup and view all the answers
Which action is primarily performed in the 'obtaining the data' step of the data science process?
Which action is primarily performed in the 'obtaining the data' step of the data science process?
Signup and view all the answers
In the context of data science, what is the significance of domain knowledge?
In the context of data science, what is the significance of domain knowledge?
Signup and view all the answers
What is a primary role of a data scientist?
What is a primary role of a data scientist?
Signup and view all the answers
Which of the following skills is essential for a data scientist?
Which of the following skills is essential for a data scientist?
Signup and view all the answers
What is one of the three basic areas essential for understanding data science?
What is one of the three basic areas essential for understanding data science?
Signup and view all the answers
Why is new vocabulary necessary in the field of data science?
Why is new vocabulary necessary in the field of data science?
Signup and view all the answers
What does the term 'domain knowledge' refer to in data science?
What does the term 'domain knowledge' refer to in data science?
Signup and view all the answers
What common issue do data scientists often face when handling data?
What common issue do data scientists often face when handling data?
Signup and view all the answers
Which area does NOT contribute to a data scientist's expertise?
Which area does NOT contribute to a data scientist's expertise?
Signup and view all the answers
What does a data scientist primarily use computer programming for?
What does a data scientist primarily use computer programming for?
Signup and view all the answers
What is the primary goal of exploratory data analysis (EDA)?
What is the primary goal of exploratory data analysis (EDA)?
Signup and view all the answers
In the context of data science, which step comes first in the process?
In the context of data science, which step comes first in the process?
Signup and view all the answers
Which of the following statements differentiates EDA from data visualization?
Which of the following statements differentiates EDA from data visualization?
Signup and view all the answers
What should be included in the modeling step of the data science process?
What should be included in the modeling step of the data science process?
Signup and view all the answers
What is an essential part of the communication and visualization step in data science?
What is an essential part of the communication and visualization step in data science?
Signup and view all the answers
In the example predicting neonatal infection, what is the first step of the workflow?
In the example predicting neonatal infection, what is the first step of the workflow?
Signup and view all the answers
Which decision-making process is recommended during the modeling stage of the data science workflow?
Which decision-making process is recommended during the modeling stage of the data science workflow?
Signup and view all the answers
What is a critical aspect to focus on during exploratory data analysis?
What is a critical aspect to focus on during exploratory data analysis?
Signup and view all the answers
What is the primary purpose of math and statistics in data science?
What is the primary purpose of math and statistics in data science?
Signup and view all the answers
Why is Python often chosen for data science tasks?
Why is Python often chosen for data science tasks?
Signup and view all the answers
What role does a data engineer fulfill in the data science process?
What role does a data engineer fulfill in the data science process?
Signup and view all the answers
Which of the following programming languages is NOT commonly associated with data science?
Which of the following programming languages is NOT commonly associated with data science?
Signup and view all the answers
In the data science process, what should be done if duplicates or outliers are found in the dataset?
In the data science process, what should be done if duplicates or outliers are found in the dataset?
Signup and view all the answers
What is domain knowledge, and why is it important in data science?
What is domain knowledge, and why is it important in data science?
Signup and view all the answers
What task is typically associated with the job of data engineers?
What task is typically associated with the job of data engineers?
Signup and view all the answers
What is a characteristic feature of Python that contributes to its popularity in data science?
What is a characteristic feature of Python that contributes to its popularity in data science?
Signup and view all the answers
Study Notes
Introduction to Data Science
- Data science is the art and science of acquiring knowledge through data.
- Data science uses data to acquire knowledge for making decisions, predicting the future, and understanding the past/present, including creating new industries/products.
- Data is individual units of information that describe a single quality or quantity of an object.
- Data is a collection of facts such as numbers, words, measurements, observations, or descriptions of things.
- Data can be qualitative or quantitative, with qualitative data being descriptive like "great fun" and quantitative data being measurable like 5, 3.265...
Data All Around
- A vast amount of data is collected and warehoused.
- Data is collected from various sources, including web data, telecom, bank/credit transactions, online trading and purchasing, and social networks.
Data is the New Oil
- Data is valuable but needs refining to be usable.
- Data analysis is needed to utilize the value in the collected data.
Digging for Data: Datafication
- Datafication is the technological trend of turning many aspects of life into data.
- It's a process of taking all aspects of life and turning them into data.
- Datafication allows transforming the purpose of things and turning information into new forms of value.
Datafication Examples
- Social Platforms (Facebook): Collect and monitor data about actions and friendships to market products and services.
- Banking: Data such as income, gender, age, etc. can be used to determine the likelihood of a person paying back a loan.
- Life Insurance Industry: Data collected helps in calculating risk levels for life insurance plans.
Risk Prediction in Life Insurance Industry
- Various attributes (product information, age, height, weight, BMI, employment information, insurance history, family history, medical history, medical keywords) are used for risk prediction.
- Risk level is an ordinal measure with 8 levels.
Data Scientist Profile
- Data science involves expertise in data visualization, machine learning, mathematics, statistics, computer science, and domain expertise.
- No single person possesses all aspects of data science, thus, teamwork is needed.
Why Data Science
- In today's age, there's a surplus of data.
- The volume of data makes human parsing impossible.
- Data collection comes in various forms and from different sources.
- Data often comes disorganized, may be missing or incorrect, and may vary greatly in scale.
Main Areas of Data Science
- Math/Statistics: Using equations and formulas for analysis.
- Computer Programming: Using code to create outcomes.
- Domain Knowledge: Understanding the problem domain.
Data Science Venn Diagram
- The three areas (math/statistics, computer science/IT, and domain/business knowledge) intersect to form data science.
Data Science Process
- Step 1: Asking an Interesting Question: Framing the problem for a data science solution. This includes understanding the domain knowledge and refining the question.
- Step 2: Obtaining Data: Finding and collecting data that can answer the question. Data sources can be private or public.
- Step 3: Explore Data (EDA): Examining the data using plots, graphs, and summary statistics (Data profiling). The goal is understanding the data's shape, patterns, and potential errors.
- Step 4: Modeling: Using statistical or machine learning models or validating them through metrics.
- Step 5: Communicating and Visualizing Results: Reporting findings to stakeholders, presenting insights through visualizations, and communicating results.
Data Engineer
- Data engineers prepare data for analysis and operations.
- Data pipelines, integrating, cleansing, and structuring data is a typical data engineering task.
- Data engineers provide ready-to-use data for data scientists.
Example: Predicting Neonatal Infection
- Data science is applied to the problem of predicting neonatal infections in prematurely born children.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Related Documents
Description
Explore the fundamental concepts of data science, its importance, and how data is collected and utilized in various sectors. This quiz covers key definitions, types of data, and the value of data in decision-making and industry innovation.
