Question 1

When querying a dimensional database,a user went from summarized data to its underlying details.The function that served this purpose is

Accepted Answer

Drill down is the function that enables a user to go from summarized data to its underlying details by expanding the dimensions in a dimensional database.

Question 2

How does the use of cloud computing affect the scalability of a data warehouse?

Accepted Answer

Cloud computing allows for dynamic allocation of hardware resources, allowing data warehouses to easily scale up or down as needed without having to physically add or remove hardware. This makes scalability much easier and more efficient than traditional on-premise data warehouses.

Question 3

Why is a performance management system superior to a performance measurement system?

Accepted Answer

While both systems are useful for evaluating and tracking employee performance, a performance management system goes beyond just measuring performance by incorporating goal setting, development plans, and ongoing feedback and coaching to improve performance. Without taking action based on the performance measurements, a performance measurement system alone has limited usefulness.

Question 4

When representing data in a data warehouse,using several dimension tables that are each connected only to a fact table means you are using which warehouse structure?

Accepted Answer

This is the definition of a star schema in a data warehouse where multiple dimension tables are connected to only one fact table. This structure is commonly used in data warehousing because it simplifies the querying process and makes it easier to aggregate data efficiently. Snowflake schema is similar, but has additional levels of normalization in the dimension tables. Relational schema is a more generalized term used for any type of database that is organized based on the relational model, while dimensional schema is another term for the star schema.

Question 5

Which kind of data warehouse is created separately from the enterprise data warehouse by a department and not reliant on it for updates?

Accepted Answer

An independent data mart is created separately from the enterprise data warehouse by a department and is not reliant on it for updates. Sectional data marts are created within the enterprise data warehouse architecture and rely on it for updates, while public data marts are accessible to multiple departments within an organization but may still rely on the enterprise data warehouse for updates. Volatile data marts are temporary and not a type of permanent data warehouse.

Question 6

All of the following are true about in-database processing technology EXCEPT

Accepted Answer

In-database processing technology is different from in-memory storage technology, as in-database processing refers to the ability to run complex analytical queries directly within the database, while in-memory storage technology refers to storing data in RAM for faster access.

Question 7

A Web client that connects to a Web server,which is in turn connected to a BI application server,is reflective of a

Accepted Answer

A three-tier architecture separates the user interface, application logic, and data storage. In this scenario, the web client represents the user interface, the web server represents the application logic, and the BI application server represents the data storage.

Question 8

Oper marts are created when operational data needs to be analyzed

Accepted Answer

Operational marts are used to analyze operational data in a multidimensional way, allowing for a more comprehensive understanding of the data. This enables better decision-making, forecasting, and trend analysis.

Question 9

Which data warehouse architecture uses metadata from existing data warehouses to create a hybrid logical data warehouse comprised of data from the other warehouses?

Accepted Answer

The federated architecture uses metadata from existing data warehouses to create a hybrid logical data warehouse comprised of data from the other warehouses. The other options do not involve leveraging metadata from existing data warehouses in the same way. Independent data marts architecture involves creating standalone data marts for specific business functions, while centralized data warehouse architecture involves a single, centralized repository for all data. Hub-and-spoke architecture involves a central hub data warehouse that connects to multiple smaller data marts or warehouses.

Question 10

Real-time data warehousing can be used to support the highest level of decision making sophistication and power.The major feature that enables this in relation to handling the data is

Accepted Answer

Real-time data warehousing requires processing large volumes of data in a short amount of time. The key challenge in achieving this is the speed of data transfer. Real-time data needs to be captured, processed, and transformed as quickly as possible to ensure that the insights generated are relevant and useful for decision-making. Therefore, the speed of data transfer needs to be high to support real-time data warehousing. Country of origin, nature of data, and source of data are important factors to consider, but they are not the major feature that enables real-time data warehousing.

Question 11

Operational or transaction databases are product oriented,handling transactions that update the database.In contrast,data warehouses are

Accepted Answer

Data warehouses are subject-oriented, meaning they organize data around a specific subject or theme, such as sales or customer behavior. They are also nonvolatile, meaning they are designed for read-only access and do not change frequently like operational databases, which are designed for transaction processing and are product-oriented. Therefore, choice A is the best option.

Question 12

In which stage of extraction,transformation,and load (ETL)into a data warehouse are anomalies detected and corrected?

Accepted Answer

The answer of In which stage of extraction,transformation,and load (ETL)into...

Question 13

Which of the following BEST enables a data warehouse to handle complex queries and scale up to handle many more requests?

Accepted Answer

Parallel processing is the best choice to enable a data warehouse to handle complex queries and scale up to handle many more requests. Parallel processing allows for multiple processors to work together to complete a task, thus speeding up the processing time and enabling the handling of more requests. The other options listed (use of the Web by users as a front-end, Microsoft Windows, and a larger IT staff) do not directly address the need for handling complex queries and scaling up requests.

Question 14

________ is an evolving tool space that promises real-time data integration from a variety of sources,such as relational databases,Web services,and multidimensional databases.

Accepted Answer

Enterprise information integration (EII) is a tool space that promises real-time data integration from various sources, including relational databases, web services, and multidimensional databases. It integrates data on-the-fly from different sources and provides a unified view of the data to the end-users. This approach simplifies the data management process and helps to reduce data redundancy.

Question 15

Which approach to data warehouse integration focuses more on sharing process functionality than data across systems?

Accepted Answer

Enterprise application integration focuses on sharing process functionality across systems, while extraction, transformation, and load (ETL) focuses on moving data between systems. Enterprise information integration combines ETL and application integration approaches to provide a comprehensive view of data across systems. Enterprise function integration is not a recognized approach to data warehouse integration.

Question 16

Data warehouses provide direct and indirect benefits to organizations.Which of the following is an indirect benefit of data warehouses?

Accepted Answer

Improved customer service is an indirect benefit as it results from better decision-making and insights gained from the data warehouse, rather than being a direct feature or function of the data warehouse itself.

Question 17

Which data warehouse architecture uses a normalized relational warehouse that feeds multiple data marts?

Accepted Answer

The hub-and-spoke data warehouse architecture uses a normalized relational warehouse as a central hub that feeds multiple data marts. This architecture helps to maintain consistency and integrity by allowing data to be cleansed and transformed in the hub, before being delivered to individual data marts for analysis. The other options do not specifically involve a normalized relational warehouse as a central hub feeding multiple data marts.

Question 18

What is Six Sigma?

Accepted Answer

Six Sigma is a methodology that focuses on reducing defects in a business process. The goal is to achieve a level of quality where there are no more than 3.4 defects per million opportunities. It involves the use of statistical tools and techniques to identify the root causes of defects and implement improvements to prevent them from occurring in the future.

Question 19

All of the following are benefits of hosted data warehouses EXCEPT

Accepted Answer

The other three choices are benefits of hosted data warehouses, but greater control of data may not necessarily be one. Hosted data warehouses may have limitations on customization, flexibility, and access control, which could lead to less control of data for the organization.

Question 20

A large storage location that can hold vast quantities of data (mostly unstructured)in its native/raw format for future/potential analytics consumption is referred to as a(n)

Accepted Answer

A data lake is a large storage repository that allows organizations to store all kinds of data, structured and unstructured, in its native/raw format at any scale. It is a central repository that can hold big data, IoT data, social media data, and much more. Data lakes provide a cost-effective and efficient way to store and analyze data without schema definitions or data transformation. The data lake concept enables data scientists, business analysts, and developers to analyze the data as needed and develop insights from it.

Quiz 3: Descriptive Analytics II: Business Intelligence and Data Warehousing