Data
Data consists of raw facts and figures that can be processed by computers to extract meaningful information.
Types of Data:
- Quantitative: Numerical values (e.g., temperature readings, test scores).
- Qualitative: Descriptive values (e.g., colors, opinions).
Data Representation:
- All data is represented in binary (0s and 1s). For example:
- Text uses character encodings like ASCII or Unicode.
- Images are stored as grids of pixels with RGB color codes.
- Audio and video are represented as waveforms sampled at regular intervals.
Cleaning and Transforming Data:
- Removing duplicates or errors.
- Converting formats for compatibility.
- Normalizing values for consistency, especially in big data projects.
Data Analysis:
- Identifying trends through sorting, filtering, and statistical analysis.
- Visualizing results with charts and graphs to support decision-making.
Ethical Considerations:
- Privacy and security of data in storage and transit.
- Bias in Algorithms processing data.
- Laws like GDPR and HIPAA governing data use.