3NF DATA MODELLING(BILL INMON) — Learn free

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Questions 1–10 of 10

1. What does Bill Inmon's 3NF Data Modelling approach build?
Question 1A. A centralised Enterprise Data Warehouse in normalised, typically Third Normal Form, structureB. A set of independent star-schema data marts built first for analyticsC. A key–value cache of loan recordsD. An append-only event logE. A graph of customers and officers
2. Which four characteristics describe the Inmon Enterprise Data Warehouse?
Question 2A. Denormalised, fast, intuitive and process-orientedB. Subject-oriented, integrated, time-variant and non-volatileC. Schema-less, distributed, partitioned and eventually consistentD. Immutable, append-only, replayable and streamingE. Hierarchical, navigational, rigid and pointer-based
3. What does a 3NF Enterprise Data Warehouse prioritise over direct query performance?
Question 3A. Horizontal scalabilityB. Developer productivityC. Data quality, traceability and long-term governanceD. Minimal table countE. Real-time responsiveness
4. How is Customer data from a CRM system and from a Core Banking system handled in an Inmon-style EDW?
Question 4A. Each system's customer records are stored in separate warehousesB. Only the CRM version is loadedC. They are stored as duplicate rows for traceabilityD. They are reconciled and integrated under a single enterprise identifierE. They are embedded together in one JSON document
5. How are business intelligence queries typically served in the Inmon architecture?
Question 5A. Directly from the normalised EDW tablesB. From a key–value cache in front of the EDWC. From the operational source systemsD. From a graph database layered on the EDWE. From dimensional data marts derived from the EDW, such as star or snowflake schemas
6. What metaphor describes the relationship between the Inmon EDW and downstream data marts?
Question 6A. Hub and spokes: the EDW is the hub and marts are spokes tailored for analytical use casesB. Parent and child: each mart owns part of the EDWC. Producer and consumer: marts emit events to the EDWD. Client and server: the EDW queries the martsE. Key and value: the EDW is the key and marts are values
7. In the Inmon-style loan approval EDW, which table has OfficerID and BranchID where BranchID is a foreign key?
Question 7A. LoanB. OfficerC. ApprovalD. BranchE. Status
8. In the 3NF loan approval EDW, what does one row of the Approval table represent?
Question 8A. One customerB. One loan accountC. One approval decision eventD. One branchE. One status value
9. Which of the following is NOT listed as a trade-off of 3NF Data Modelling in an EDW?
Question 9A. Designing and maintaining the EDW can be complex and time-consumingB. Query performance for end users may be slower unless marts are createdC. The model is less intuitive for business users than a star schemaD. Every data element loses traceability to its sourceE. Analytical queries may require multiple joins
10. How does Inmon's philosophy contrast with Kimball's approach?
Question 10A. Inmon builds star schemas first; Kimball builds a normalised core firstB. Inmon uses NoSQL; Kimball uses relational databasesC. Inmon rejects data marts entirely; Kimball rejects the warehouseD. Inmon is real-time; Kimball is batchE. Inmon is EDW-first, building the normalised core then deriving marts; Kimball is dimensional-first, building marts directly for analytics