### What is raw data? - [ ] Data that has been processed and organized for analysis. - [x] Initial data that is unprocessed and unorganized. - [ ] Summarized data ready for reporting. - [ ] Data that is ready for direct implementation. > **Explanation:** Raw data is the initial data collected, which is unprocessed and unorganized, representing the real-world conditions without transformation or analysis. ### Why is raw data important? - [ ] It is already spotless and requires no further processing. - [x] It provides a truthful and unmodified snapshot of real-world conditions. - [ ] It is easy to analyze without any modifications. - [ ] It has been already cleaned and corrected for analysis. > **Explanation:** Raw data provides a truthful and unmodified snapshot of the real-world circumstances it measures, making it invaluable for accurate analysis and conclusions. ### Which of the following is an example of raw data? - [ ] Summarized sales report. - [ ] Analyze data trends. - [x] Sensor readings directly from collection devices. - [ ] Final thesis draft. > **Explanation:** Sensor readings directly from collection devices are an example of raw data as it is collected data in its original form without any processing. ### What is a common problem associated with raw data? - [ ] It is always 100% accurate. - [ ] It is always well-organized. - [ ] It is already in a format ready for analysis. - [x] It often contains noise or irrelevant information. > **Explanation:** Raw data often contains noise, which includes irrelevant or redundant information that can complicate direct analysis. ### Which term describes transforming raw data into a more usable format? - [x] Data processing - [ ] Data storage - [ ] Data deletion - [ ] Data archiving > **Explanation:** Data processing is the act of transforming raw data into a more understandable and usable format. ### What process involves detecting and correcting inaccuracies in raw data? - [ ] Data collection - [x] Data cleaning - [ ] Data visualization - [ ] Data archiving > **Explanation:** Data cleaning involves detecting and correcting (or removing) corrupt or inaccurate records from a dataset, ensuring the quality of the data. ### In which field is raw data especially important? - [ ] Only in historical studies - [ ] Only in pure mathematics - [ ] Only in music studies - [x] Data science > **Explanation:** Raw data is especially important in data science as it serves as the foundation for analytics, machine learning, and other forms of data-driven research. ### Can raw data be analyzed directly without any treatment? - [ ] Yes, it can be analyzed as it is always clean and organized. - [x] No, it often requires preprocessing and cleaning. - [ ] Maybe, depending upon what kind of analysis is needed. - [ ] Yes, no transformations or modifications are needed. > **Explanation:** Raw data is typically unprocessed and may require cleaning and preprocessing to make it suitable for analysis. ### What are transactional records an example of? - [ ] Processed data - [ ] Summarized data - [x] Raw data - [ ] Visualized data > **Explanation:** Transactional records in their unaggregated form are examples of raw data collected from business transactions. ### What is the result of raw data after it has been processed? - [ ] Raw data - [ ] More raw data - [x] Processed (or cleaned) data - [ ] Summarized report > **Explanation:** After raw data has been processed, it becomes processed or cleaned data, which is ready for analysis and extracting insights.