40 Questions
What is the primary goal of a data entrepreneur?
To create a vision for a business and use data science expertise to turn it into reality
What is characterized as data that exceeds the processing capacity of conventional database systems?
Big Data
What is the purpose of Hadoop?
To reduce big data into smaller datasets for data scientists to analyze
What is the defining characteristic of a data entrepreneur?
Craving creative freedom as a founder
What do machine learning engineers, data engineers, and data scientists play in the modern data ecosystem?
Crucial roles
What is the primary function of data science?
To improve business performance
What is big data characterized by?
Exceeding the processing capacity of conventional database systems
What is required to use big data?
A Hadoop cluster
What is one of the reasons cited for Python's current popularity?
Everything you need to learn and do in Python is free
What does the graph of Google search trends over the last five years indicate?
Python's popularity has been increasing
Where can you find the most current stable build of Python?
python.org website
What is Anaconda typically referred to as?
A data science platform
What do you need to install along with Anaconda?
Microsoft VS Code
What is required to download Anaconda?
Nothing, it's free
What is the primary purpose of logistic regression?
To estimate values for a categorical target variable
What is the purpose of a code editor?
To type Python code
What is the function of a Python interpreter?
To run Python code
What is a key benefit of using logistic regression?
It provides probability estimates for each of its predictions
What is the main difference between univariate and multivariate outlier detection?
Univariate detection looks at features individually, while multivariate detection looks at relationships between features
What is the main purpose of detecting outliers in a dataset?
To remove anomalies that can affect analysis
What is Ordinary Least Squares (OLS) regression used for?
To fit a linear regression line to a dataset
What type of data is suitable for logistic regression?
Categorical data with a target variable that describes the class
What is a potential application of outlier detection?
To detect fraud or cybersecurity attacks
What is a key assumption of many statistical and machine learning approaches?
That the data has no outliers
What kind of data is available on the World Bank Open Data page?
Data on agriculture, economy, environment, science, and more
What is the main purpose of the World Bank?
To provide loans to developing countries
What is unique about the Knoema platform?
It houses over 500 databases
What kind of data can be accessed through the World Bank’s Open Data API?
Any data available on the World Bank Open Data page
What is Quandl?
A Toronto-based website for searching numeric data
How many datasets does Quandl link to?
Over 10 million datasets
What is the range of velocity at which big data enters an average system?
Between 30 kilobytes per second to 30 gigabytes per second
What kind of data is NOT available on Knoema?
Social media data
What type of data is commonly generated from human activities and doesn't fit into a structured database format?
Unstructured data
What is the main difference between the World Bank Open Data page and Quandl?
One provides data only from the World Bank, the other provides data from multiple sources
What is the primary challenge posed by high-velocity, real-time moving data?
Obstacle to timely decision-making
What is an example of semistructured data?
JSON files
What is a common source of big data?
All of the above
What is the primary feature of structured data?
It can be stored in a traditional relational database management system
What is an example of heterogeneous data?
Any combination of graph data, JSON files, XML files, social media data, and structured tabular data
What is the primary challenge posed by high-variety data?
Handling heterogeneous data sources
Study Notes
Exploring Career Alternatives in Data Science
- A data entrepreneur builds businesses by delivering exceptional data science services and products, using data science expertise to guide the business.
- Data entrepreneurs crave creative freedom and are founders of their own businesses.
Defining Big Data and the Three Vs
- Big Data characterizes data that exceeds the processing capacity of conventional database systems due to its size, speed, or lack of structural requirements.
- Hadoop is a data processing platform that reduces big data into smaller, more manageable datasets for data scientists to analyze.
- The Three Vs of Big Data are:
- Velocity: data enters systems at velocities ranging from 30 kilobytes to 30 gigabytes per second.
- Variety: big data is composed of structured, semistructured, and unstructured data from various sources.
- Volume: big data storage and processing capabilities require significant investments.
Identifying Important Data Sources
- Various sources generate large volumes of data, including:
- Social media
- Financial transactions
- Health records
- Click-streams
- Log files
- Internet of Things
Regression Methods
- Logistic regression is a machine learning method used to estimate values for a categorical target variable based on selected features.
- Ordinary least squares (OLS) regression is a statistical method that fits a linear regression line to a dataset, useful for models with multiple independent variables.
Detecting Outliers
- Outliers are data points with values significantly different from the majority of data points.
- Outlier detection is essential for data analysis and can be done using univariate or multivariate approaches.
Exploring Data Worldwide
- The World Bank Open Data page provides datasets on various indicators, including:
- Agriculture and rural development
- Economy and growth
- Environment
- Science and technology
- Financial sector
- Poverty and income
- Knoema is a platform with 500+ databases, including government data, international organization data, and corporate data.
- Quandl is a search engine for numeric data, linking to over 10 million datasets from various sources, including the United Nations and central banks.
Why Python Is Hot
- Python's popularity is due to:
- Ease of learning
- Free resources
- Ready-made tools for current hot technologies like data science, machine learning, and artificial intelligence
- Google search trends show Python's increasing popularity over the last five years.
Choosing the Right Python
- Python versions have different release dates, and the most current stable build is recommended.
Tools for Success
- A good Python interpreter and editor are necessary for coding.
- Anaconda is a complete Python development environment with a graphic user interface and includes VS Code.
- Installing Anaconda and VS Code involves downloading from the official website and following on-screen instructions.
Explore the role of a data entrepreneur, combining data science skills with business acumen to deliver exceptional services and products.
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