GRAPH DATABASES — Learn free

Self-check

Questions 1–10 of 10

1. How do graph databases store data?
Question 1A. As nodes representing entities and edges representing relationships between themB. As rows partitioned by a primary keyC. As JSON documents with embedded arraysD. As key–value pairsE. As fact tables joined to dimension tables
2. What is the primary goal of graph databases?
Question 2A. Performing bulk aggregations over millions of rowsB. Uncovering insights from relationships and networksC. Providing ultra-fast lookup by keyD. Validating API payload structureE. Reconstructing state by replaying events
3. In the loan approval graph example, which edge connects a Customer to a Loan?
Question 3A. approved_byB. issued_atC. applies_forD. subclass_ofE. is_a
4. In the fraud detection scenario using Neo4j, which pattern is described as suspicious?
Question 4A. A customer with several repayments on the same loanB. A loan issued at the customer's home branchC. A loan officer working at a single branchD. Multiple customers sharing the same contact details, or one officer repeatedly approving loans for tightly connected individualsE. A guarantor with a high credit score
5. Why can graph databases discover connection patterns more easily than relational systems?
Question 5A. Because they store all data in one partitionB. Because they enforce Third Normal FormC. Because they cache every record in memoryD. Because they use a fixed tree structureE. Because relationships are stored explicitly and navigated directly rather than inferred through multiple complex joins
6. Which of the following is NOT listed as a limitation of graph databases?
Question 6A. Inability to perform multi-hop queriesB. Being more niche than relational or document storesC. Not being optimised for bulk aggregations such as summing loan amounts across millions of recordsD. Requiring specialised query languages such as Cypher or GremlinE. Additional learning overhead
7. Why are graph databases described as a natural host for semantic models?
Question 7A. Because they prioritise self-contained recordsB. Because they treat relationships as first-class elements, aligning with models that focus on meaning and how things relateC. Because they enforce strict domain constraintsD. Because they are optimised for tables and joinsE. Because they store only hierarchical data
8. What distinguishes a metagraph from a simple graph?
Question 8A. It stores only taxonomiesB. It replaces edges with tablesC. It allows relationships about relationships, such as an officer approving a loan under a specific policy ruleD. It stores only numeric dataE. It forbids class hierarchies
9. What does a knowledge graph combine?
Question 9A. Fact tables and dimension tablesB. Keys, values and partitionsC. Events, timestamps and consumersD. Facts, ontologies and taxonomies into a unified networkE. Classes, methods and inheritance
10. What contrasting questions do relational models and semantic models answer?
Question 10A. Relational: "How fast is the query?"; semantic: "How much does it cost?"B. Relational: "Who owns the data?"; semantic: "Where is it stored?"C. Relational: "When did it happen?"; semantic: "Who caused it?"D. Relational: "Which node has the most edges?"; semantic: "Which table has the most rows?"E. Relational: "How is the data structured?"; semantic: "What does this data represent?"