Data Ethics
What is the primary purpose of data ethics?
To ensure responsible and ethical handling, use, and sharing of data.
What does open data mean?
Data that is freely available for anyone to access, use, and share.
What is structured data?
Data that is highly organized and easily searchable, typically stored in tables or databases.
What is decomposition in computational thinking?
Breaking down a complex problem into smaller, more manageable parts.
What is data pre-processing?
The process of cleaning, transforming, and preparing raw data for analysis.
What is informed consent in data collection?
Ensuring individuals are aware of how their data will be used and agreeing to its collection.
What is the main principle of public access in open data?
Ensuring that data is available to everyone without restrictions.
Give an example of unstructured data.
Text documents, emails, images, or videos.
What is pattern recognition?
Identifying trends, similarities, or patterns within data to make predictions or decisions.
Why is data cleaning important in data science?
To ensure that the data is accurate, consistent, and free of errors before analysis.
Name two ethical concerns that arise when using AI and machine learning models.
Bias in algorithms and lack of transparency in decision-making.
Name one challenge of using open data.
Incomplete or poorly documented datasets.
What is a key difference between structured and unstructured data?
Structured data is organized and can be easily processed, while unstructured data lacks a predefined format and is more difficult to analyze.
What is abstraction in computational thinking?
Focusing on the essential details of a problem and ignoring irrelevant information.
Name one common method used for data visualization.
Bar charts, pie charts, line graphs, or scatter plots.
What is the principle of fairness in data ethics?
Ensuring that data collection and analysis do not lead to discrimination or bias against certain groups.
What is the role of reusability in open data?
Ensuring data can be reused for different purposes without restrictions.
How can unstructured data be converted into structured data for analysis?
By using techniques such as text mining, natural language processing (NLP), and data transformation.
How would you apply decomposition to solving a problem in business operations?
Break the problem (e.g., reducing costs) into smaller tasks, such as analyzing labor, supply chain, and operational efficiency.
What does data integration involve?
Combining data from multiple sources into a unified dataset.
How can transparency in data usage foster trust between an organization and its users?
By openly sharing how data is collected, processed, and used, making users feel more secure and aware.
How does open data support innovation?
It allows individuals and organizations to build on existing data to develop new solutions, products, or research.
Why is it important for businesses to analyze both structured and unstructured data?
Structured data provides clear insights, while unstructured data (such as customer reviews) can offer deeper, qualitative insights that improve decision-making.
How can pattern recognition help in developing a predictive model for customer behavior?
By identifying recurring behaviors or trends in past customer data, businesses can predict future actions and tailor their strategies accordingly.
What is the goal of predictive analytics in data science?
To use historical data to predict future trends or behaviors.