Data Product — Learn free

Self-check

Questions 1–10 of 10

1. In which layer of an enterprise data environment are data products primarily built and operated?
Question 1A. The OLTP (Online Transaction Processing) layerB. The OLAP (Online Analytical Processing) layerC. The network security layerD. The email server layerE. The hardware firmware layer
2. At its core, what is a data product?
Question 2A. A hardware device for storing databasesB. A licence to use a third-party analytics toolC. A tangible, consumable asset that derives its value from data and is presented so that users, human or machine, can act upon itD. A transactional application that records sales ordersE. A spreadsheet template with no data in it
3. What is the defining purpose of a Data Product Application (DPA)?
Question 3A. To directly answer specific business questions with immediate insight delivery, typically as dashboards, reports, Excel files or data exportsB. To provide a production-grade dataset for reuse by other systemsC. To generate transactional data for operational processesD. To enforce data contracts across many downstream consumersE. To store raw data in its natural state
4. What does Data-As-a-Product (DAaP) refer to?
Question 4A. A one-off dashboard built for a single executiveB. A transactional system that captures ordersC. An Excel export intended for offline analysis onlyD. Curated, production-grade datasets or models designed explicitly for consumption by other users, systems or applicationsE. A physical device that collects sensor data
5. Why do schema, structure or logic changes to a Data-As-a-Product require rigorous impact assessment and governance?
Question 5A. Because DAaP products are never allowed to changeB. Because multiple downstream consumers may depend on the productC. Because DAaP products are stored only in OLTP systemsD. Because they are consumed by a single executiveE. Because changes automatically delete the underlying data
6. A dashboard originally built for one internal team attracts interest from other teams and applications wanting to reuse its curated data, so it gains stronger modelling, governance and versioning. Which journey does this illustrate?
Question 6A. From OLAP to OLTPB. From DAaP to DPAC. From data lake to data warehouseD. From raw data to archived dataE. From DPA to DAaP
7. Which of the following is NOT listed among the questions to consider for successful data product development?
Question 7A. Who the end user or system isB. What questions the product is meant to answerC. How the data lifecycle and governance will be maintainedD. Which programming language the developers preferE. Whether the product is application-facing (DPA) or platform-facing (DAaP)
8. Which of the following is given as an example of a data product?
Question 8A. A recommendation system such as those used by Netflix or Amazon to personalise suggestionsB. A paper filing cabinetC. An office chairD. A printed telephone directoryE. A conference room booking whiteboard
9. What stages does the development process of a data product involve?
Question 9A. Marketing, sales and customer supportB. Data collection, processing, analysis and creation of a user interface or platform for accessing insightsC. Hiring, onboarding and training staffD. Budgeting, procurement and auditingE. Compression, archiving and deletion
10. Where does the value of a data product lie?
Question 10A. In the physical size of its databaseB. In the number of columns it containsC. In its ability to turn raw data into actionable insights that help users make better decisions, improve processes or gain a competitive advantageD. In the cost of the hardware it runs onE. In how many transactions it records per second