Question 1

An operational database is not a good candidate for high-level management reporting because it is not equipped to ________.
A) handle complex queries for strategic planning
B) support what-if type questioning
C) manipulate information related to business performance
D) return high-quality information

Accepted Answer

The answer of An operational database is not a good...

Question 2

________ refers to collections of data that are so enormous in size, so varied in content, and so fast to accumulate that they are difficult to store and analyze using traditional approaches.
A) Big data
B) Data cube
C) Meta data
D) Shard

Accepted Answer

Big data refers to the challenges of processing and analyzing large and complex datasets that are too big for traditional data processing tools and techniques. The term "big data" is used to describe data sets that are too large or complex for traditional data processing tools to handle. It typically involves massive amounts of data that is generated in real-time, such as social media data, sensor data, or machine-generated data from IoT devices.

Question 3

Julian, a database administrator, prepares data to be loaded to a data warehouse. He checks the zip code field against a reference database of zip codes to ensure that it conforms to standards. The zip codes that aren't in the standard format are reformatted. This process is called ________.
A) extraction
B) transformation
C) loading
D) normalization

Accepted Answer

The process described in the scenario is an example of data transformation, where the zip codes that don't meet the standard format are reformatted to match the expected format. Extraction refers to the process of pulling data from a source system, loading involves moving data into a target system, and normalization involves restructuring a database to eliminate redundancy and improve efficiency.

Question 4

When building a warehouse, the process of reformatting data so that it conforms to set standards is called ________.
A) extraction
B) transformation
C) loading
D) normalization

Accepted Answer

The process of reformatting data to conform to set standards is called data transformation. This is part of the ETL (Extract, Transform, Load) process used in building data warehouses. Extraction refers to the process of gathering data from various sources, loading involves uploading the data into the warehouse, and normalization involves organizing the data into a standardized format to minimize redundancy and improve efficiency.

Question 5

________ uses statistical techniques to explore a data warehouse and hunt for hidden patterns and relationships that are undetectable in routine reports.
A) Data mining
B) Data extracting
C) Data modeling
D) Data normalizing

Accepted Answer

Data mining is the process of applying advanced statistical techniques to analyze large datasets to identify patterns and relationships that go beyond simple analysis. This process is useful in uncovering hidden insights that can be used to make informed decisions. Data extracting, modeling, and normalizing are all steps in the process of preparing and organizing data for analysis, but they do not involve the advanced statistical techniques used in data mining.

Question 6

Which of the following database architectures relies on a cooperating collection of existing databases?
A) data mining
B) data cubes
C) virtual federated warehouse
D) data warehouse appliance

Accepted Answer

The virtual federated warehouse architecture relies on a cooperating collection of existing databases, meaning that data is gathered from multiple sources and accessed through a virtual interface. This architecture allows for a flexible and customizable approach to data management, as different sources and types of data can be incorporated as needed. Data mining and data cubes refer to specific methods of analyzing and organizing data within a database, while a data warehouse appliance is a specialized hardware device used for data storage and retrieval.

Question 7

A person who ensures that people adhere to the definitions for the master data in their organizational units is called a(n) ________.
A) data steward
B) database administrator
C) information systems educator
D) management analyst

Accepted Answer

A data steward is responsible for ensuring that people adhere to the definitions for the master data in their organizational units, including data quality, consistency, and security. Database administrators focus on managing and maintaining the technical aspects of databases, while information systems educators teach people how to use technology effectively. Management analysts typically focus on analyzing and improving business processes. Therefore, the best choice for this role is a data steward.

Question 8

Database architecture that has multidimensional data grouped in logical dimensions, such as sales by product, city, region, and country, is called ________.
A) data cubes
B) operational database
C) data warehouse appliance
D) data mining

Accepted Answer

Multidimensional data that is grouped in logical dimensions is commonly referred to as data cubes. Therefore, the correct choice is A. Operational database (B) refers to the database that is responsible for day-to-day operations of an organization. Data warehouse appliance (C) is a pre-configured hardware and software bundle optimized for fast and easy deployment of a data warehouse. Data mining (D) is the process of discovering patterns and insights from large datasets.

Question 9

A central data repository containing information drawn from multiple sources that can be used for analysis, intelligence gathering, and strategic planning is called a ________.
A) data warehouse
B) data dictionary
C) data model
D) database shard

Accepted Answer

A data warehouse is a central repository that integrates data from various sources and provides a unified view for querying and analysis. It is designed to support business intelligence and decision-making activities by providing a consistent, reliable, and scalable source of data. A data dictionary is a database that provides metadata about the structure, content, and usage of other databases or data sources. A data model is a conceptual representation of data objects, their attributes, relationships, and rules. A database shard is a horizontal partition of a database that is split across multiple servers or nodes.

Question 10

Which of the following is a disadvantage of using shadow systems?
A) Shadow systems are difficult to create, deploy, and maintain.
B) Shadow systems cannot be developed by individuals or departments to handle specific information requirements.
C) Shadow systems contain information that is not consistent with the corporate database.
D) Shadow systems require extensive IT support and documentation.

Accepted Answer

Shadow systems are created outside of the company's official systems and processes, and as a result, it is unlikely that the data contained in the shadow systems will be consistent with the data contained in the corporate database. This can cause confusion and mistakes, as different versions of the same data may exist in two different systems.

Question 11

Retrieval is very fast through data cubes because ________.
A) data cubes use a separate server which is tuned for fast retrieval and reporting
B) data cubes group data in logical dimensions, such as sales by product, city, region, and country
C) data cubes represent information in the form of objects, using object-oriented programming languages to access them
D) data cubes organize data by attaching XML tags to them

Accepted Answer

Data cubes group data in logical dimensions, allowing for fast retrieval and analysis of data based on specific criteria. Each dimension can be easily accessed and analyzed, allowing for efficient and quick data retrieval.

Question 12

A company maintains a centralized repository of information from internal sources, competitor information, census reports, and metadata from documents and multimedia. This is known as a ________.
A) data dictionary
B) data model
C) data warehouse
D) database shard

Accepted Answer

The described repository is a data warehouse, which is a centralized repository of integrated data from various sources used for business intelligence and analytical purposes. A data dictionary is a complementary tool that provides metadata about the data stored in the warehouse. A data model is a schematic representation of the relationships between data entities. A database shard is a subset of a larger database that is split and distributed across multiple nodes for scalability and availability.

Question 13

Which of the following is used to spot trends, identify patterns, generate reports for compliance purposes, do research, and plan strategies?
A) data warehouse
B) operational database
C) data dictionary
D) transaction database

Accepted Answer

A data warehouse is a large repository of data that is specifically designed to support business intelligence activities such as trend analysis, pattern identification, report generation, and strategic planning. An operational database (B) is used to support day-to-day business operations such as transaction processing. A data dictionary (C) is a collection of metadata that describes the data elements in a database, and a transaction database (D) is a type of operational database that is specifically designed to support transaction processing.

Question 14

In Aster Limited, the HR department did not include interns as employees in their database, while the finance department included them. Such inconsistencies can be avoided through ________.
A) shadow system
B) normalization
C) database schema
D) master data management

Accepted Answer

Master data management involves ensuring that all data within an organization is consistent, accurate, and up-to-date. This can help to avoid inconsistencies such as the one described in the scenario, where one department considers interns as employees while another does not. By implementing a master data management system, all departments can access and update the same data, reducing the risk of inconsistencies and errors.

Question 15

________ is a prepackaged data warehouse solution offered by vendors that includes the hardware and software, maintenance, and support.
A) Virtual federated appliance
B) Shadow systems
C) Relational database
D) Data warehouse appliance

Accepted Answer

A prepackaged data warehouse solution that includes hardware, software, maintenance, and support is commonly known as a data warehouse appliance.

Question 16

Which of the following is a good master data management strategy?
A) upgrading technology
B) creating shadow systems
C) creating a database schema
D) focusing on key areas

Accepted Answer

Focusing on key areas is a good strategy in master data management as it helps organizations prioritize the management of their most critical data elements, leading to better data governance and improved data quality. Upgrading technology and creating a database schema may be necessary components of a master data management strategy, but they are not sufficient on their own. Creating shadow systems is not recommended as it can create data silos and excessive complexity in data management.

Question 17

The process of retrieving data from multiple sources to be loaded into a data warehouse is called ________.
A) extraction
B) transformation
C) loading
D) normalization

Accepted Answer

Extraction refers to the process of retrieving data from multiple sources, such as databases, files, or applications. Transformation involves preparing the data for loading into the data warehouse, such as cleaning, filtering, and aggregating. Loading is the process of actually loading the transformed and processed data into the data warehouse. Normalization is a technique for organizing data in a relational database to minimize redundancy and ensure data integrity.

Question 18

Trekking blindly into terabytes of data to sniff out meaningless relationships that occur just by accident is called ________.
A) data mining
B) data drudging
C) data modeling
D) normalizing

Accepted Answer

The answer of Trekking blindly into terabytes of data to...

Question 19

An approach that attempts to achieve consistent and uniform definitions for entities and their attributes across all business units is called ________.
A) normalization
B) master data management
C) data modeling
D) database mirroring

Accepted Answer

Master data management is a methodology that aims to provide a uniform definition of all master data entities (such as customers, products, employees) and their attributes across all business units and systems in an organization. This is achieved through a set of processes, policies, standards, and technologies that ensure data consistency, accuracy, and completeness, and enable effective data governance and stewardship. Normalization, data modeling, and database mirroring are related but distinct concepts that address different aspects of database design and management.

Question 20

Which of the following technologies is better equipped than relational databases to handle big data?
A) MySQL
B) Hadoop
C) ETL
D) SQL Server

Accepted Answer

Hadoop is designed specifically to handle big data and can process and store massive amounts of data across multiple servers. While relational databases like MySQL and SQL Server can handle large amounts of data, they may struggle with the scale and complexity of big data. ETL (Extract, Transform, Load) is a process used to move data from one system to another and is not a technology in itself.

Quiz 4: Databases and DataWarehouses

An operational database is not a good candidate for high-level management reporting because it is not equipped to ________.

________ refers to collections of data that are so enormous in size, so varied in content, and so fast to accumulate that they are difficult to store and analyze using traditional approaches.

Julian, a database administrator, prepares data to be loaded to a data warehouse. He checks the zip code field against a reference database of zip codes to ensure that it conforms to standards. The zip codes that aren't in the standard format are reformatted. This process is called ________.

When building a warehouse, the process of reformatting data so that it conforms to set standards is called ________.

________ uses statistical techniques to explore a data warehouse and hunt for hidden patterns and relationships that are undetectable in routine reports.

Which of the following database architectures relies on a cooperating collection of existing databases?

A person who ensures that people adhere to the definitions for the master data in their organizational units is called a(n) ________.

Database architecture that has multidimensional data grouped in logical dimensions, such as sales by product, city, region, and country, is called ________.

A central data repository containing information drawn from multiple sources that can be used for analysis, intelligence gathering, and strategic planning is called a ________.

Which of the following is a disadvantage of using shadow systems?

Retrieval is very fast through data cubes because ________.

A company maintains a centralized repository of information from internal sources, competitor information, census reports, and metadata from documents and multimedia. This is known as a ________.

Which of the following is used to spot trends, identify patterns, generate reports for compliance purposes, do research, and plan strategies?

In Aster Limited, the HR department did not include interns as employees in their database, while the finance department included them. Such inconsistencies can be avoided through ________.

________ is a prepackaged data warehouse solution offered by vendors that includes the hardware and software, maintenance, and support.

Which of the following is a good master data management strategy?

The process of retrieving data from multiple sources to be loaded into a data warehouse is called ________.

Trekking blindly into terabytes of data to sniff out meaningless relationships that occur just by accident is called ________.

An approach that attempts to achieve consistent and uniform definitions for entities and their attributes across all business units is called ________.

Which of the following technologies is better equipped than relational databases to handle big data?