Question 1

Logical schema design goals: which targets should a good logical design meet to keep data clean, queryable, and performant?

Accepted Answer

Introduction / Context: A logical schema describes how information is organized into entities, attributes, and relationships. A high-quality design prevents anomalies, supports intuitive queries, and enables efficient access. The question asks which goals a good logical schema should achieve. Given Data / Assumptions: We are evaluating logical (not physical) design aims. We want data to remain consistent and reliable over time. We want SQL to be straightforward, and performance to be reasonable. Concept / Approach: Logical design aims to reduce redundancy and inconsistency (via appropriate normalization and constraints), make querying intuitive (clear table boundaries and keys), and facilitate efficient access (appropriate keys and relationships that physical design can further optimize). These goals reinforce one another; neglecting any leads to maintenance pain, slow queries, or incorrect results. Step-by-Step Solution: Identify the three goals: consistency, queryability, efficiency.Recognize that sound logical design addresses all three simultaneously.Select “All of the above.” Verification / Alternative check: Standard data modeling guidance (keys, normalization, referential integrity) explicitly targets consistency; clear schemas simplify query writing; and well-chosen keys/relations are prerequisites for physical tuning. Why Other Options Are Wrong: Picking only one or two ignores the holistic nature of logical design.“None” is invalid because these are established design objectives. Common Pitfalls: Over-normalizing without considering query paths, or denormalizing without constraints; both can hurt either consistency or efficiency. Final Answer: All of the above

Question 2

Interfacing a DBMS with other tools: information can be transferred between a database and which types of end-user programs through import/export or connectors?

Accepted Answer

Introduction / Context: Databases rarely live in isolation. Users pull data into spreadsheets for analysis, mail merge into documents, or chart results in graphics tools. The question asks which categories of programs can exchange data with a DBMS, typically via import/export, ODBC/JDBC, or built-in connectors. Given Data / Assumptions: We consider common desktop tools used with data. Connectivity may use CSV/JSON exports, direct drivers, or APIs. Transfer can be bidirectional: import to DBMS or export from it. Concept / Approach: Modern DBMS platforms provide many integration paths: spreadsheets (for pivoting and modeling), word processors (for mail merge or templated documents), and graphics/BI programs (for visualization). Because all three interactions are common and supported, the inclusive answer applies. Step-by-Step Solution: List typical tools used alongside databases: spreadsheet, word processor, graphics/BI.Note available connectors or file formats enabling exchange.Conclude that all listed program types can transfer information with a DBMS. Verification / Alternative check: Real-world workflows: export query results to CSV for spreadsheets; mail merges with word processors; dashboards built in visualization tools fed directly by database connectors. Why Other Options Are Wrong: Choosing a single program type understates common practice.“None” contradicts ubiquitous integration features of DBMSs. Common Pitfalls: Copy-pasting data without preserving data types or encodings; prefer structured exports and parameterized connections. Final Answer: All of the above

Question 3

DDL packaging: in SQL, which statement can group multiple CREATE TABLE, CREATE VIEW, and GRANT commands to be issued together within a single, atomic schema definition?

Accepted Answer

Introduction / Context: When initializing a new application schema, it is helpful to create tables, views, and privileges together to ensure the database is left in a consistent state. SQL provides a statement that lets you bundle such DDL in one logical unit. Given Data / Assumptions: We want to include CREATE TABLE, CREATE VIEW, and GRANT together. The goal is atomicity and organization during schema deployment. We reference broadly recognized SQL features (not vendor-specific packages). Concept / Approach: The CREATE SCHEMA statement defines a schema and can include a set of subordinate DDL statements within it. This lets a database apply the set as one coherent definition. CREATE PACKAGE is a program unit construct in some vendors (not generic SQL for DDL grouping). CREATE CLUSTER is a storage/organization feature in certain engines, unrelated to bundling mixed DDL with grants. Step-by-Step Solution: Identify the need: bundle multiple DDL statements.Map to the SQL feature designed for defining a schema atomically: CREATE SCHEMA.Exclude unrelated constructs (packages, clusters). Verification / Alternative check: Standards and vendor docs show CREATE SCHEMA supporting contained CREATE TABLE/VIEW and GRANT, applying them as one schema definition unit. Why Other Options Are Wrong: CREATE PACKAGE: program library feature, not general DDL bundling for tables/views/grants.CREATE CLUSTER: storage/segment concept, not transactionally bundling mixed DDL statements.All/None: incorrect because “CREATE SCHEMA” is the precise match. Common Pitfalls: Mixing transactional assumptions across engines; some databases auto-commit DDL, so use migration tools or explicit schema scripts for safe deployment. Final Answer: CREATE SCHEMA

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