Data Detritus — Learn free

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Questions 1–10 of 10

1. How is Data Detritus defined?
Question 1A. Data that has never been analysed because of technology barriersB. Data that is used only during auditsC. Data that is corrupted during transferD. Data that is no more required and of no use anymoreE. Data duplicated across several systems
2. Which description distinguishes Detritus data from Dark data and Dormant data?
Question 2A. Detritus data was and is not in useB. Detritus data was once in use but will not be in use anymoreC. Detritus data is hardly in useD. Detritus data is used every dayE. Detritus data is data whose format cannot be read
3. Why is Detritus data normally not deleted or purged?
Question 3A. Because it is too large to delete efficientlyB. Because it is still used for daily analyticsC. Because deleting it would break data pipelinesD. Because it is needed to train new modelsE. Because Regulatory or Compliance parties can still require it
4. Which banking example illustrates Data Detritus?
Question 4A. The first transaction of a customer who has been active with the bank for 20 yearsB. The daily balance of every current accountC. Card transactions from the last quarter used for fraud detectionD. The interest rate table for mortgagesE. Yesterday's ATM withdrawals
5. Is all Dark Data bad?
Question 5A. Yes, all Dark Data should be purgedB. Yes, because it never has valueC. NoD. Only if it is structuredE. Only if it is older than five years
6. Can all Dark Data be deleted or purged?
Question 6A. Always yesB. NeverC. Only structured Dark DataD. Yes and No, depending on whether it may still be requiredE. Only after it becomes Dormant
7. Which business model is said to delete or purge most of its data after extracting valuable insights from it?
Question 7A. BankingB. E-commerceC. GovernmentD. HealthcareE. Insurance
8. In a nutshell, what should happen to data that was in use in the past compared with the rest?
Question 8A. Everything should be kept in the data warehouse foreverB. Everything should be deleted after one yearC. Past data should be moved to the operational databaseD. Past data should be re-analysed each quarterE. Data that was in use is most probably kept in cold storage, and the rest can be deleted or purged
9. Compared with Detritus data, what characterises traditional Dark Data?
Question 9A. It was never in use because of technology barriersB. It was valuable once and then became DormantC. It is always deleted after an auditD. It is only found in e-commerceE. It is used heavily by regulators
10. Given that Twitter alone processes about 52 terabytes of data daily, what is recommended for such huge social media data rather than keeping all of it forever?
Question 10A. Keep all of it in the data warehouseB. Purge all of it immediately after collectionC. Convert the elements that were used for decision-making into Dark data and delete or purge the restD. Move all of it to tape drives permanentlyE. Hand all of it to regulators