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All Flashcards
What is the purpose of data mining?
To discover useful information and relationships within large datasets.
Why is data visualization important?
It makes trends and patterns easier to see and understand, especially with large datasets.
What is the key to making raw data useful?
Data transformation.
Why is it important to remember that correlation does not equal causation?
Just because two things happen together doesn't mean one caused the other.
What are some examples of data processing?
Spreadsheet programs, text analysis tools and search tools.
What is the goal of data filtering?
To create and extract subsets of data based on specific criteria.
What is an iterative process in data transformation?
Data being run through processing programs multiple times.
What is the purpose of identifying trends in data?
To understand how data changes over time.
What is the significance of identifying outliers?
To find unexpected spikes or dips in data.
What is the relationship between data mining and data processing?
Data mining helps us find the 'what,' while data processing is how we get there.
What is Data Mining?
Examining large datasets to find useful information, patterns, or relationships.
What is Data Processing?
Using computer programs to record, modify, and organize data.
What is Text Analysis?
Looking for patterns within text to categorize or classify it.
What is Data Visualization?
Creating tables and diagrams to visually represent data.
What is Data Filtering?
Creating and extracting subsets of data based on specific criteria.
What is Data Transformation?
Modifying data to extract more information.
What is a Pattern in data analysis?
Something that repeats in a dataset.
What is a Trend in data analysis?
Rising, falling, or fluctuating data over time.
What is Correlation in data analysis?
Relationships between variables.
What are Outliers in data analysis?
Unusual data points.
What are the differences between data mining and data processing?
Data mining: Discovering patterns | Data processing: Recording, modifying, and organizing data.
What are the differences between a pattern and a trend in data analysis?
Pattern: Repeating data | Trend: Data changing over time.
What are the differences between correlation and causation?
Correlation: Relationship between variables | Causation: One variable directly causes another.
What are the differences between data filtering and data transformation?
Data filtering: Creating subsets | Data transformation: Modifying data to extract more information.
What are the differences between identifying trends and identifying outliers?
Trends: General direction of change | Outliers: Unusual data points.
What are the differences between text analysis and data visualization?
Text analysis: Finding patterns in text | Data visualization: Representing data visually.
What are the differences between data processing and data visualization?
Data processing: Recording, modifying, organizing data | Data visualization: Visually representing data.
What are the differences between patterns and correlations?
Patterns: Repeating sequences | Correlations: Relationships between variables.
What are the differences between data mining and text analysis?
Data mining: Analyzing large datasets | Text analysis: Analyzing patterns in text.
What are the differences between data filtering and data mining?
Data filtering: Creating subsets | Data mining: Discovering patterns in large datasets.