Question 1

Multidimensional data analysis techniques include advanced computational functions.

Accepted Answer

Multidimensional data analysis techniques often involve complex algorithms and statistical models that require advanced computational functions.

Question 2

Master data management's main goal is to provide a partial and segmented definition of all data within an organization.

Accepted Answer

Master data management aims to provide a comprehensive, consistent, and unified definition of all critical data within an organization to ensure accuracy and consistency across different systems and departments.

Question 3

Normalizing fact tables improves data access performance and saves data storage space.

Accepted Answer

Normalizing is typically applied to dimension tables to reduce data redundancy and improve data integrity, not to fact tables. Fact tables are usually designed to be denormalized to optimize data access performance in a data warehouse environment.

Question 4

Queries against operational data typically are broad in scope and high in complexity.

Accepted Answer

Queries against operational data are typically narrow in scope and simple, aiming at day-to-day operations rather than complex analysis.

Question 5

Relational data warehouses use multidimensional data schema support to handle multidimensional data.

Accepted Answer

The answer of Relational data warehouses use multidimensional data schema...

Question 6

In the prognosis phase, the data-mining findings are used to predict future behavior and forecast business outcomes.

Accepted Answer

In the prognosis phase of data mining, the findings are used to make predictions and forecasts about future behavior and business outcomes.

Question 7

Business intelligence (BI) architecture is composed of data, people, processes, technology, and the management of such components.

Accepted Answer

This is a true statement. BI architecture is a complex framework composed of different elements such as data, people, processes, and technology that work together to enable effective decision-making and business analysis. Effective management of these components is essential for the success of any BI initiative.

Question 8

Business intelligence is a framework that allows a business to transform data into information, information into knowledge, and knowledge into wisdom.

Accepted Answer

Business intelligence involves using data analysis tools and techniques to extract insights and valuable information from raw data. This information can then be used to make informed business decisions and gain a competitive advantage. The ultimate goal of business intelligence is to turn data into actionable insights that can drive business growth and success.

Question 9

Explanatory analytics employs mathematical and statistical algorithms, neural networks, artificial intelligence, and other advanced modeling tools to create actionable predictive models based on available data.

Accepted Answer

Explanatory analytics focuses on understanding past data and identifying relationships, while predictive analytics uses advanced tools to forecast future outcomes.

Question 10

Decision support data are a snapshot of the operational data at a given point in time.

Accepted Answer

Decision support data are derived from operational data, but they are tailored to meet the specific needs of decision-makers and are often presented in formats that are easier to analyze and interpret. They provide a snapshot of the operational data at a given point in time, but they are organized and presented in a way that makes them more relevant and useful for decision-making purposes.

Question 11

Operational data and decision support data serve the same purpose.

Accepted Answer

Operational data is used to run day-to-day operations and support transactional processes, while decision support data is used to analyze and make strategic business decisions. While both types of data are important, they serve different purposes.

Question 12

A star schema is designed to optimize data query operations rather than data update operations.

Accepted Answer

The star schema is optimized for fast querying of large datasets, but it can be less efficient for data updates due to its denormalized structure.

Question 13

The data warehouse development life cycle differs from classical systems development.

Accepted Answer

The data warehouse development life cycle is different from classical systems development as it involves multiple stages specific to data warehousing, such as data sourcing, data cleansing, data transformation, and data loading. Traditional systems development may have different stages and objectives.

Question 14

To provide better performance, some OLAP systems merge data warehouse and data mart approaches by storing small extracts of the data warehouse at end-user workstations.

Accepted Answer

The answer of To provide better performance, some OLAP systems...

Question 15

By default, the fact table's primary key is always formed by combining the superkeys pointing to the dimension tables to which they are related.

Accepted Answer

The fact table's primary key is not always formed by combining the superkeys pointing to the dimension tables. It could be a single column or a composite key consisting of multiple columns.

Question 16

Data warehouse data are organized and summarized by table, such as CUSTOMER and ADDRESS.

Accepted Answer

Data warehouse data are organized and summarized by subject areas rather than by table, focusing on concepts like customers, sales, and products rather than how data is stored in tables.

Question 17

Periodicity, usually expressed as current year only, previous years, or all years, provides information about the time span of the data stored in a table.

Accepted Answer

Periodicity does indicate the time span of data stored in a table, and is typically expressed as current year only, previous years, or all years.

Question 18

Business intelligence tools use the data warehouse data as the raw materials for data analytics to generate business knowledge.

Accepted Answer

Business intelligence tools are designed to gather, store, access, and analyze large amounts of data from multiple data sources, including data warehouses. The data warehouse provides the raw materials for data analytics to generate business insights and knowledge. Therefore, Business intelligence tools use the data warehouse data as the input to generate useful reports, visualizations, and dashboards that help decision-makers make informed decisions.

Question 19

A data store is used by data analysts to create queries that access the database.

Accepted Answer

The answer of A data store is used by data...

Question 20

A data warehouse designer must define common business dimensions that will be used by a data analyst to narrow a search, group information, or describe attributes.

Accepted Answer

The answer of A data warehouse designer must define common...

Quiz 13: Business Intelligence and Data Warehouses