Types of Data — Learn free

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Questions 1–10 of 10

1. What are the three fundamental types of data?
Question 1A. Numeric, text and dateB. Structured, semi-structured and unstructuredC. Public, private and secretD. Hot, warm and coldE. Raw, clean and archived
2. Which description fits STRUCTURED data?
Question 2A. Organised in a predefined format, typically rows and columnsB. Free text with no formatC. Images and videos onlyD. Data that changes structure on every entryE. Data that cannot be exported
3. A table with 6 columns and 10 rows is exported. Some cells are empty. What type of data is it?
Question 3A. The empty rows are droppedB. The structure stays intact: every row keeps the same number of columnsC. Columns with empty cells are removedD. It becomes unstructuredE. It must be converted to JSON
4. Which formats are examples of semi-structured data?
Question 4A. CSV and spreadsheetsB. XML and JSONC. MP4 and MP3D. PDF and WordE. JPEG and PNG
5. How does semi-structured data differ from structured data when exported, in the employee-contact example?
Question 5A. It always has more rowsB. Rows may have varying numbers of columns because only populated fields are includedC. It cannot be exported at allD. Every row has exactly six columnsE. It is always encrypted
6. Which platforms are examples of sources of semi-structured data?
Question 6A. Bank ledgersB. Facebook and TwitterC. SpreadsheetsD. Payroll systemsE. Barcode scanners
7. Which of these is typical UNSTRUCTURED data?
Question 7A. A CSV fileB. A relational tableC. Images, videos, audio files, emails and PDFsD. A JSON document with fixed keysE. A spreadsheet
8. What can sometimes impose a semblance of structure on unstructured data?
Question 8A. Deleting half of itB. MetadataC. Printing itD. Renaming the filesE. Compressing it
9. Which is a characteristic of unstructured data?
Question 9A. Known structure before data entryB. Easy, automated extractionC. Format unknown until examined, with continuous analysis requiredD. A fixed number of columnsE. No possibility of machine-learning insights
10. In the facial-image illustration, what makes it possible for algorithms to extract features consistently?
Question 10A. Randomly rotating each imageB. Aligning all images consistently in a structured grid, helped by metadataC. Storing images as textD. Reducing every image to one pixelE. Removing all metadata