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Questions 1–10 of 10

1. From which Greek roots does the word Epistemology come?
Question 1A. Epi meaning "upon" and stema meaning "structure"B. Ethos meaning "character" and logos meaning "word"C. Episteme meaning "knowledge" and logos meaning "discourse" or "communication"D. Epistole meaning "letter" and nomos meaning "law"E. Episteme meaning "belief" and logos meaning "number"
2. What central concept does Epistemology explore?
Question 2A. Justified knowledgeB. Data storage efficiencyC. Network topologyD. Statistical samplingE. Financial forecasting
3. Which of the following is NOT one of the questions Epistemology addresses?
Question 3A. What do we know?B. How can we claim to know something?C. What validates our beliefs?D. How do we ascertain the certainty of our knowledge?E. How much does it cost to store the data?
4. How do data science teams turn raw data into knowledge in the Big Data era?
Question 4A. By archiving it in a data warehouseB. By applying machine learning or deep learning models to extract insightsC. By converting it into structured tablesD. By encrypting it before analysisE. By publishing it to business users unchanged
5. Why is a justification of knowledge essential in Data Epistemology?
Question 5A. To reduce the size of the datasetB. To satisfy licensing requirementsC. To speed up model trainingD. To ensure that the insights extracted align with their origins and truly reflect what was expectedE. To remove the need for evidence
6. What kind of validation does Data Epistemology emphasise?
Question 6A. Evidence-based validationB. Opinion-based validationC. Vendor-based validationD. Cost-based validationE. Schedule-based validation
7. What is identified as a key challenge in Big Data from an epistemological point of view?
Question 7A. Choosing a cloud providerB. Finding enough storageC. The generation and validation of knowledgeD. Hiring database administratorsE. Converting unstructured data into images
8. Which relationships must be analysed to address the challenge of knowledge generation in Big Data?
Question 8A. Between the budget, the timeline and the teamB. Between the hardware, the network and the softwareC. Between the customer, the supplier and the regulatorD. Between the tables, the columns and the indexesE. Between the knowledge produced, the entities that produce it and the methods used to generate it
9. How does the view of knowledge in I Am Datapedia! differ from the conventional view?
Question 9A. Knowledge is considered impossible to derive from dataB. Knowledge can be derived directly from data, rather than only building on informationC. Knowledge is treated as identical to wisdomD. Knowledge is considered only to come from qualitative researchE. Knowledge is treated as a subset of raw data
10. In evidence-based validation, on what does qualitative research rely?
Question 10A. The number of models trainedB. The speed of the databaseC. The seniority of the analystD. The quality of the design and the data collectedE. The size of the budget