Database Management Systems

Option D is correct because a 10% cache hit ratio means 90% of data requests are going to disk, which is extremely poor performance - significantly increasing cache size will allow more data to stay in memory, reducing expensive disk operations. Changing application code (A) might help but cache sizing is the direct fix. Running queries twice (C) is nonsensical, and doing nothing (B) with a 10% hit ratio is unacceptable - this indicates severe cache starvation.

A personal contacts database is typically small-scale and for individual use. A personal computer provides sufficient resources and is cost-effective for this purpose. Mainframes and supercomputers are designed for enterprise or scientific computing with massive workloads, making them impractical choices.

Performance problems most often originate in the application program itself due to inefficient algorithms, poor data structures, unnecessary computations, or suboptimal database queries. While OS, hardware, and database issues can cause problems, they are less common than application-level issues.

For long-running batch operations, missing, fragmented, or poorly configured indexes are the most common cause of drastic performance degradation. Network delays or vendor limitations rarely account for a run-time disparity of 3 days versus 3 hours.

Data Driven is a valid option in the target settings for Update Strategy transformation. When selected, the Integration Service follows the row-by-row instructions (DD_INSERT, DD_UPDATE, DD_DELETE) coded in the Update Strategy transformation. Options A, B, and C (Merge, Insert into, Mount) are not standard target options in Informatica.

Yes, you can configure sessions to generate a new log file each run. This is done by enabling session log options and configuring the log file name to include timestamps or run instance IDs. Each execution then creates a separate log instead of overwriting.

Query Studio is designed for business users to create ad-hoc (on-demand) reports quickly without deep technical knowledge. Unlike Report Studio, which is for more complex professional report development, Query Studio focuses on simple, immediate reporting needs.

A Package in Cognos Framework Manager is a subset of the model that exposes specific portions of the complete model to report authors. Packages provide security, simplify complexity, and allow different user groups to see only relevant model elements.

A data warehouse is a centralized repository designed specifically for query, analysis, and decision-making. Unlike operational databases that process transactions, data warehouses consolidate historical data from multiple sources to support business intelligence activities. Options A and B describe general databases, while D is about implementation rather than purpose.

A conformed dimension is a dimension table with the same meaning and content across multiple fact tables in a data warehouse. It enables drill-across analysis by allowing different fact tables to be joined through the shared dimension, ensuring consistency in reporting. Option A is incorrect as conformed dimensions are not created together but are designed to be compatible. Option B is wrong as all dimensions have primary keys. Option C is vague.

A snowflake schema normalizes dimension tables into multiple related tables to reduce redundancy and save storage space. Unlike star schemas where dimensions are denormalized, snowflake schemas break down dimensions into hierarchical levels (e.g., product → product category → product type). Option A incorrectly suggests facts are normalized (they're not - facts remain denormalized). Option B is wrong because fact and dimension tables are not joined together in 3NF - only dimensions are normalized.

Dimensions contain descriptive attributes that provide context for facts in the data warehouse. They are subject-oriented (organized around business entities like customer, product, time) and non-volatile (data doesn't change once loaded). Options A and D are wrong because dimensions don't contain facts. Option B is incorrect as dimensions contain their own descriptive data, not primarily data about other dimensions.

Cardinality in Framework Manager defines the numerical relationship between two tables (1:1, 1:N, N:1, or N:N) regardless of table type. It can represent relationships between fact and dimension tables (common in star schemas), between dimension tables (when dimensions relate to each other), or between any other tables in the model. Cardinality affects how Framework Manager generates SQL and handles joins. Option D is incorrect because cardinality is defined per relationship, not by data source.

Cognos Report Studio provides multiple data container types for displaying data: Lists show tabular data, Crosstabs display matrix/pivot tables, Charts create visual representations, and Conditional Blocks show content based on specified conditions. All four listed options are valid data containers in Cognos, making "All the above" the correct answer.

OLAP (Online Analytical Processing) structures are designed for fast analysis of multidimensional data from multiple perspectives. While OLAP cubes can aggregate data from various sources for near real-time analysis, option C best describes their core analytical capability. Options A and B describe traditional dimensional modeling, while option D describes table join configuration, not OLAP's defining characteristic.