Question 1

Despite the need for high-quality data, organizational politics and technical issues often make it a difficult goal to achieve.

Accepted Answer

This statement is true. Organizational politics and technical issues can often create obstacles to obtaining high-quality data.

Question 2

Data in databases are said to be volatile because data is constantly being added or updated by new transactions.

Accepted Answer

Data in databases are considered volatile because they are constantly changing with new transactions being added or existing transactions being updated. This means that the data in a database is not static and can change at any moment, making it volatile.

Question 3

According to your text, the true costs associated with poor data quality are: Cost of repeating analyses + Lost opportunity costs + Cost of unrealized threats

Accepted Answer

The answer of According to your text, the true costs...

Question 4

Data in databases are said to be volatile because of rounding errors or software apps that lack the appropriate precision when making calculations.

Accepted Answer

Data in databases are not volatile because of rounding errors or software apps that lack appropriate precision. Rounding errors and precision issues can occur during calculations or data manipulation, but they do not necessarily make the data in the database volatile. The volatility of data in a database refers to its tendency to change frequently or unexpectedly, often due to external factors such as user input, system updates, or data synchronization.

Question 5

Data warehouses that integrate data from databases across an entire organization are called enterprise data warehouses.

Accepted Answer

Enterprise data warehouses are designed to centralize and integrate data from various sources across an organization to provide a comprehensive view of business operations. This enables businesses to make better decisions based on insights gained from analyzing the integrated data.

Question 6

The principle of diminishing data values suggests that many global financial services institutions need near real time data for peak performance.

Accepted Answer

The principle of diminishing data values states that the incremental value of additional data decreases as more data is collected. Therefore, global financial services institutions require near real time data to ensure optimal performance.

Question 7

Data warehouses are designed as online transaction processing OLTP) systems, meaning that the data can be queried and analyzed much more efficiently than OLAP applications.

Accepted Answer

Data warehouses are designed as online analytical processing (OLAP) systems, not online transaction processing (OLTP) systems. OLAP is specifically designed for complex analysis and data mining, while OLTP is designed for speedy management of transactional data.

Question 8

The data life cycle is a model that illustrates the way in which data moves through an organization.

Accepted Answer

The data life cycle is a widely accepted model that shows how data is created, stored, processed, used and eventually deleted within an organization or system. It is an important concept in data management and helps organizations to identify areas where data can be optimized, secured and maintained throughout its life cycle.

Question 9

Master data management MDM) is a set of processes that aid organizations in integrating data from various sources or enterprise applications to create and maintain a more unified view of a customer, product, or other core data entity that is shared across systems.

Accepted Answer

Master data management (MDM) does indeed involve integrating data from various sources or enterprise applications to create a more unified view of core data entities.

Question 10

Because of data volatility in a database that is constantly being updated with real-time transactions, data must be exported to a data warehouse prior to data mining, use by DSS apps and business intelligence analyses.

Accepted Answer

Data volatility in a transactional database can affect the accuracy of analytics and reports. Exporting data to a data warehouse that supports historical data storage allows for accurate analysis and helps to improve decision making.

Question 11

According to your text, data errors are responsible for increasing the cost of health care by billions of dollars, not to mention, putting lives at risk.

Accepted Answer

The text states that data errors are responsible for increasing the cost of health care by billions of dollars and putting lives at risk.

Question 12

Because of volatility, data from databases are transferred to a data warehouse so that they are ready for quick responses to inquiries.

Accepted Answer

Data in a data warehouse is organized and optimized for fast queries and analysis, making it more suitable for quick responses to inquiries than volatile databases.

Question 13

MDM consolidates data from various data sources into a multi-source data file, which then feeds data back to the applications, thereby creating accurate and consistent data across the enterprise.

Accepted Answer

The answer of MDM consolidates data from various data sources...

Question 14

MDM consolidates data from various data sources into a master reference file, which then feeds data back to the applications, thereby creating accurate and consistent data across the enterprise.

Accepted Answer

This statement accurately describes the purpose and function of Master Data Management (MDM) systems.

Question 15

The principle of 90/90 data use suggests that 90% of the capability to capture, process, format, and distribute data in near real time or faster dissipates within 90 seconds of a transaction occurring.

Accepted Answer

The principle of 90/90 data use does not exist as described; the statement seems to be a misinterpretation or confusion with other principles or rules related to data management, processing, or decision-making.

Question 16

There are three kinds of enterprise data: Transactional data, Master data and Analytical data.

Accepted Answer

This statement is true. Transactional data includes information about specific business transactions, such as sales orders or purchase orders. Master data refers to core data elements that are used across multiple applications and business processes, such as customer or product information. Analytical data is used for business intelligence and analytics purposes, and is often aggregated from transactional and master data sources.

Question 17

The data pathway model illustrates the way in which data moves through an organization.

Accepted Answer

The answer of The data pathway model illustrates the way...

Question 18

In terms of the major functions performed by a DBMS, data maintenance refers to checking and controlling data integrity over time.

Accepted Answer

Data maintenance is one of the major functions of a DBMS which includes ensuring data integrity, consistency, and accuracy over time by performing tasks such as backups, recovery, and security measures.

Question 19

According to your text, the true costs associated with poor data quality are: Value of lost business + Cost to prevent errors + Cost to correct errors.

Accepted Answer

The true costs associated with poor data quality include the value of lost business, the cost to prevent errors, and the cost to correct errors.

Question 20

Master data serves as a layer between transactional data in a database and analytical data in a data warehouse.

Accepted Answer

Master data management involves creating a single source of accurate and consistent data to be used across an organization. This master data layer acts as a bridge between the transactional data stored in different databases and the analytical data stored in data warehouses or other decision-making systems.

Quiz 3: Database, Data Warehouse, and Data Mining