Data Warehouse Models
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Questions and Answers

Which data modeling technique is used for designing a data warehouse?

  • Data modeling (correct)
  • Data mining
  • ER modeling
  • OLAP

    • What is a key characteristic of a data warehouse?

  • Non-volatility (correct)
  • Fast data deletion
  • High storage capacity
  • Volatility

    • What is the primary purpose of a data warehouse?

  • Analyzing data (correct)
  • Storing data
  • Transferring data
  • Recording data

    • What is the difference between normalization and denormalization?

    <p>Normalization divides data into multiple tables, while denormalization combines data into a single table.</p> Signup and view all the answers

    What is the key difference between a data warehouse and a database?

    <p>A data warehouse is designed for analyzing data, while a database is designed for recording data.</p> Signup and view all the answers

    What is the purpose of data loading in a data warehouse?

    <p>To insert new data</p> Signup and view all the answers

    Which processing technique is used in a data warehouse?

    <p>OLAP</p> Signup and view all the answers

    What is a characteristic of data warehouse tables and joins?

    <p>Denormalized and simpler</p> Signup and view all the answers

    What is the primary purpose of a data mart?

    <p>To support business-line specific reporting and analysis</p> Signup and view all the answers

    What is a key characteristic of an enterprise data warehouse?

    <p>It integrates data from all business units</p> Signup and view all the answers

    What is the main advantage of using a virtual data warehouse?

    <p>It allows users to access data as if it was stored in one data warehouse</p> Signup and view all the answers

    What is the primary goal of data integration in a data warehouse?

    <p>To provide a unified view of the organization</p> Signup and view all the answers

    What is a key characteristic of a data warehouse?

    <p>It is subject-oriented, delivering information about a specific subject</p> Signup and view all the answers

    What is the main difference between a data mart and an enterprise data warehouse?

    <p>A data mart is focused on a specific business area, while an enterprise data warehouse spans the entire organization</p> Signup and view all the answers

    Why do external applications or reporting tools typically query data marts instead of enterprise data warehouses?

    <p>Because data marts are more specialized and contain relevant data for a specific business area</p> Signup and view all the answers

    What is a distinct feature of a data warehouse compared to operational systems?

    <p>It is time-variant, storing historical data</p> Signup and view all the answers

    What is the primary purpose of ETL processes in data warehousing?

    <p>To transform and load data into a data warehouse</p> Signup and view all the answers

    What is the characteristic of data in an enterprise data warehouse?

    <p>Data is captured at the lowest level of detail</p> Signup and view all the answers

    What is the purpose of data marts in a data warehouse architecture?

    <p>To provide departmental views of information</p> Signup and view all the answers

    What is the design used in data marts?

    <p>Dimensional design</p> Signup and view all the answers

    What is the process of transforming data into a specific standard format?

    <p>Data transformation</p> Signup and view all the answers

    What is the term used to describe the process of consolidating data from various sources?

    <p>Data integration</p> Signup and view all the answers

    What is the characteristic of an enterprise data warehouse?

    <p>It is a centralized repository of data</p> Signup and view all the answers

    What is the purpose of data analysis applications in a data warehouse architecture?

    <p>To analyze data in a data mart</p> Signup and view all the answers

    Study Notes

    Data Warehouse Models

    • There are three types of data warehouse models:
      • Data mart: used for business-line specific reporting and analysis, aggregating data from a range of source systems relevant to a specific business area.
      • Virtual data warehouse: a set of separate databases that can be queried together, providing access to all the data as if it was stored in one data warehouse.
      • Enterprise data warehouse: contains aggregated data that spans the entire organization, integrating data from all business units.

    Characteristics of Data Warehouse

    • Subject-Oriented: delivers information about a specific subject, rather than a company's current operations.
    • Integrated: integrates data from multiple sources, storing it in a unified manner.
    • Time-variant: stores data with a specific time period, providing information from a historical perspective.
    • Non-volatile: data is permanent, and previous data is not replaced, omitted, or deleted when new data is inserted.

    Data Warehouse vs. Database

    • Data warehouse: serves as an information system containing historical and communicative data from one or several sources, used for analyzing data, subject-oriented, and uses Online Analytical Processing (OLAP).
    • Database: an amalgamation of related data, used for recording data, application-oriented, and uses Online Transactional Processing (OLTP).

    Normalization and Denormalization

    • Normalization: dividing data into multiple tables to reduce data redundancy and inconsistency, achieving data integrity.
    • Denormalization: combining data into a single table to make data retrieval faster.

    Inmon vs. Kimball

    • Inmon's data warehouse architecture: corporate applications (transaction systems) provide data to the data warehouse, which is then divided into multiple data marts based on different department needs.
    • Kimball's approach is not mentioned in the text.

    Functions of Data Warehouse

    • Data cleaning
    • Data integration
    • Data mapping
    • Data extraction
    • Data transformation
    • Data loading
    • Data refreshing

    Inmon's Data Warehouse Architecture

    • Corporate Applications (transaction systems) collect data from business transactions and store it in various forms.
    • ETL (Extract, Transform, Load) process brings data from transaction systems, consolidates and transforms it, and loads it into an enterprise data warehouse (EDW).
    • Enterprise data warehouse is a central element, capturing data at the lowest level of detail, and storing it in a relational database.
    • Data marts are departmental views of information with subject-oriented data, taking data from the enterprise data warehouse, and using dimensional design for analysis.

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    Related Documents

    Inmons-Methodology.pptx

    Description

    This quiz covers different data warehouse models, including data mart, virtual data, and enterprise data warehouse, focusing on their usage and characteristics.

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