Dmw-quiz-1-a

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| By Sumit Srivastava
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Sumit Srivastava
Community Contributor
Quizzes Created: 1 | Total Attempts: 352
| Attempts: 353
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  • 1/15 Questions

    The source of all data warehouse data is the____________.

    • Operational environment.
    • Informal environment.
    • Formal environment.
    • Technology environment.
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About This Quiz

DMW-QUIZ-1-A assesses understanding of data warehousing concepts, focusing on operational metadata, star schema, data sources, and data types. It evaluates knowledge crucial for effective data management and analytics.

Data Warehousing Quizzes & Trivia

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  • 2. 

    ________________defines the structure of the data held in operational databases .

    • User-level metadata.

    • Transaction Data

    • Operational metadata.

    • Data mining metadata.

    Correct Answer
    A. Operational metadata.
    Explanation
    Operational metadata refers to the information that defines the structure of data stored in operational databases. It provides details about the organization, format, and relationships of the data, allowing for efficient storage, retrieval, and manipulation of the data. This type of metadata is essential for the proper functioning of operational databases and ensuring data integrity and consistency. User-level metadata, transaction data, and data mining metadata do not specifically pertain to the structure of data in operational databases.

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  • 3. 

    Sequencing of the mappings from a set of low-level concepts to higher-level concepts is known as

    • Data mart

    • Data warehouse

    • Star schema

    • Concept Hierarchy

    Correct Answer
    A. Concept Hierarchy
    Explanation
    Concept Hierarchy is the correct answer because it refers to the sequencing of mappings from low-level concepts to higher-level concepts. This means organizing and structuring data in a hierarchical manner, where more general concepts are at the top and more specific concepts are at the bottom. It helps in understanding the relationships and dependencies between different concepts, allowing for easier analysis and navigation of data.

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  • 4. 

    Data Cleaning is used to

    • Detect errors in data and rectifies

    • Propagates updates from the data sources to the warehouse

    • Converts data from legacy formats to warehouse format

    • Gather data from Multiple, heterogeneous resources

    Correct Answer
    A. Detect errors in data and rectifies
    Explanation
    Data Cleaning is the process of identifying and correcting errors, inconsistencies, and inaccuracies in data. It involves various techniques and methods to detect and rectify these errors, such as removing duplicate entries, handling missing values, standardizing data formats, and resolving inconsistencies. The goal of data cleaning is to improve data quality and ensure that the data is accurate, complete, and reliable for analysis and decision-making purposes.

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  • 5. 

    Relation between mean, median and mode

    • Mean- mode = 2(mean-median)

    • Mean- median = 3(mean-mode)

    • Mean- mode = 3(mean-median)

    • Mean- median = 2(mean-mode)

    Correct Answer
    A. Mean- mode = 3(mean-median)
    Explanation
    The given equation, mean - mode = 3(mean - median), indicates that the difference between the mean and the mode is three times the difference between the mean and the median. This relationship suggests that the mode is closer to the mean than the median is. In other words, the mode is more representative of the central tendency of the data compared to the median.

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  • 6. 

    For Quick Searching …………………………………indexing is used in OLAP cube

    • Bitmap

    • Joint Bitmap

    • Composite join Indices

    • None of the above

    Correct Answer
    A. Bitmap
    Explanation
    Bitmap indexing is used in OLAP cube for quick searching. It is a data structure that uses bitmaps to represent the presence or absence of rows in a table. This indexing technique is particularly useful for low cardinality data, where there are a limited number of distinct values in a column. By using bitmaps, it allows for efficient filtering and aggregation operations in OLAP cubes, enabling faster query processing and analysis. Joint bitmap, composite join indices, and none of the above are not relevant to the given statement.

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  • 7. 

    OLAP is

    • Informational Processing

    • Lots of Scans

    • Summarized & Consolidated

    • All of the above

    Correct Answer
    A. All of the above
    Explanation
    OLAP stands for Online Analytical Processing, which is a technology used for analyzing and processing large amounts of data. It involves informational processing, as it focuses on extracting valuable information from data. It also involves lots of scans, as it scans through the data to find patterns and relationships. Additionally, OLAP is known for its ability to summarize and consolidate data, providing a high-level view of the information. Therefore, the correct answer is "All of the above" as all the given options accurately describe OLAP.

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  • 8. 

    Data warehouse has

    • 4-Tiers

    • 3-Tiers

    • 2-Tiers

    • N-Tiers

    Correct Answer
    A. 3-Tiers
    Explanation
    A data warehouse typically consists of three tiers: the bottom tier is the data storage layer, where the actual data is stored; the middle tier is the data integration layer, where data from various sources is collected, transformed, and loaded into the warehouse; and the top tier is the data access layer, where users can query and analyze the data. This three-tier architecture allows for efficient data storage, integration, and retrieval, making it a popular choice for data warehousing implementations.

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  • 9. 

    Data are extracted using application program interfaces are known as

    • Hubs

    • Processcors

    • Switches

    • Gateways

    Correct Answer
    A. Gateways
    Explanation
    When data is extracted using application program interfaces (APIs), the devices that facilitate the communication between different networks or systems are known as gateways. Gateways act as intermediaries, translating data from one format to another to enable seamless communication and integration between different systems. They can be used to connect networks with different protocols or to enable communication between different software applications. Therefore, gateways are the correct answer in this context.

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  • 10. 

    The star schema is composed of __________ fact table.

    • 1

    • 2

    • 3

    • 4

    Correct Answer
    A. 1
    Explanation
    The star schema is composed of one fact table. In a star schema, the fact table contains the measurable data or the numerical values that are being analyzed or reported on. It is surrounded by multiple dimension tables, which provide context and additional details about the data in the fact table. The fact table is at the center of the star schema and is connected to the dimension tables through foreign key relationships. This structure allows for efficient and simplified querying and analysis of data.

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  • 11. 

    ……………………………perfroms selection on One Dimensions of the Given Cube

    • Pivot

    • SLICE

    • DICE

    • Drill-Down

    Correct Answer
    A. SLICE
    Explanation
    The correct answer is SLICE. In the context of data analysis and multidimensional cubes, slicing refers to the process of selecting a specific portion or subset of data along one dimension. This allows analysts to focus on a specific aspect or category of the data, while disregarding the other dimensions. Therefore, slicing performs selection on one dimension of the given cube.

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  • 12. 

    Data to be modeled is multiple dimensions in

    • Data Cube

    • Data Mart

    • Data Model

    • Dimension table

    Correct Answer
    A. Data Cube
    Explanation
    A data cube is a multidimensional representation of data that allows for efficient analysis and querying. It is used to model data that has multiple dimensions, such as time, geography, and product. A data cube organizes data into a structure that enables users to easily slice, dice, and drill down into the data to gain insights and make informed decisions. It is commonly used in data warehousing and business intelligence applications to support complex analytical queries.

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  • 13. 

    Data warehouse contains_____________data that is never found in the operational environment.

    • Normalized.

    • Informational.

    • Summary.

    • Denormalized.

    Correct Answer
    A. Summary.
    Explanation
    A data warehouse contains summary data that is not typically found in the operational environment. This means that the data in the warehouse is aggregated, organized, and presented in a way that allows for easy analysis and reporting. The purpose of a data warehouse is to provide a consolidated view of data from different sources, making it easier for users to make informed decisions based on the summarized information. In contrast, operational environments contain detailed and transactional data that is used for day-to-day operations.

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  • 14. 

    To Store and Manage warehouse data we use ……………..OLAP

    • HOLAP

    • MOLAP

    • ROLAP

    • SQL Servers

    Correct Answer
    A. ROLAP
    Explanation
    ROLAP stands for Relational Online Analytical Processing. It is a type of OLAP (Online Analytical Processing) that stores and manages warehouse data using a relational database management system. ROLAP allows users to access and analyze data from multiple dimensions and hierarchies, providing a flexible and scalable solution for data analysis. Unlike MOLAP and HOLAP, ROLAP does not require pre-aggregation of data and can directly query the relational database. SQL Servers, on the other hand, are a type of database management system that can be used to implement ROLAP or other OLAP solutions.

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  • 15. 

    The model is kept in the normalized form in ……………….Schema

    • Fact Constellation

    • Snow Flake

    • Star schema

    • None of the above

    Correct Answer
    A. Snow Flake
    Explanation
    The model is kept in the normalized form in a Snow Flake Schema. In a Snow Flake Schema, the dimension tables are further normalized by splitting them into multiple tables. This helps in reducing data redundancy and improving data integrity. The normalized form allows for efficient data storage and retrieval, making it easier to maintain and update the model.

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  • Current Version
  • Mar 21, 2023
    Quiz Edited by
    ProProfs Editorial Team
  • Jan 28, 2018
    Quiz Created by
    Sumit Srivastava
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