Data Warehousing Overview
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Questions and Answers

What is a primary feature of OLTP systems?

  • Ability to store large amounts of historical data
  • Support for complex analytical queries
  • High-level data aggregation
  • Decentralized architecture to avoid single points of failure (correct)

Which of the following is NOT an example of an OLTP system?

  • Online airline ticket booking
  • Data warehousing (correct)
  • Online banking
  • Order entry

How does OLTP typically respond to queries?

  • By conducting elaborate data analyses
  • With time-consuming complex transactions
  • With sub-second response times for simple queries (correct)
  • By returning large sets of historical records

What is one of the main benefits of using the OLTP method?

<p>It simplifies daily transactions for organizations (B)</p> Signup and view all the answers

In what type of architecture does OLTP typically operate?

<p>3-tier architecture (A)</p> Signup and view all the answers

What characterizes a data warehouse as being 'subject-oriented'?

<p>Data is stored by subject instead of by application. (B)</p> Signup and view all the answers

What is the function of metadata in data warehousing?

<p>To document information about the data involved. (C)</p> Signup and view all the answers

How long does a data warehouse typically store data?

<p>5 to 10 years (C)</p> Signup and view all the answers

Which of the following statements about the non-volatile nature of data in a data warehouse is true?

<p>Once data is added, it is retained and not removed. (B)</p> Signup and view all the answers

Which of the following best describes an integrated data warehouse?

<p>It merges data from various sources into a cohesive format. (C)</p> Signup and view all the answers

What is a key purpose of a data warehouse?

<p>To facilitate deep analysis and decision-making. (A)</p> Signup and view all the answers

In data warehousing, why is it important for data to be time-variant?

<p>It provides historical context for the analysis. (C)</p> Signup and view all the answers

Which of the following statements about data marts is true?

<p>Data marts are subject-oriented subsets of the data warehouse. (D)</p> Signup and view all the answers

What is the primary purpose of a data mart?

<p>To provide a flexible and customized subset of data for specific groups (A)</p> Signup and view all the answers

Which operating systems are typically used to implement data marts?

<p>Unix/Linux-based servers and low-cost platforms (C)</p> Signup and view all the answers

How does an enterprise warehouse differ from a data mart?

<p>Enterprise warehouse collects all organizational data, while data marts are specific subsets (A)</p> Signup and view all the answers

Which OLAP server type uses relational or extended-relational DBMS?

<p>ROLAP (D)</p> Signup and view all the answers

What advantage does Hybrid OLAP (HOLAP) have over its counterparts?

<p>It combines the scalability of ROLAP with the speed of MOLAP (A)</p> Signup and view all the answers

Which characteristic is typical of data marts?

<p>They are highly flexible and customized by department (C)</p> Signup and view all the answers

What does OLAP allow users to do with data?

<p>Extract and view business data from various perspectives (B)</p> Signup and view all the answers

Which of the following statements about MOLAP is true?

<p>It may have low storage utilization if the data is sparse (A)</p> Signup and view all the answers

What is the primary function of technical metadata in a data warehouse?

<p>To assist warehouse designers and administrators with information about warehouse data (B)</p> Signup and view all the answers

Which of the following statements accurately describes a data mart?

<p>A data mart is a specific subset of a data warehouse focused on a single business line. (B)</p> Signup and view all the answers

What characterizes the bottom tier of the three-tier data warehouse architecture?

<p>It includes the relational database system for data storage and processing. (A)</p> Signup and view all the answers

How does OLAP differ in its implementations?

<p>Through Relational OLAP (ROLAP) and Multidimensional OLAP (MOLAP) models. (B)</p> Signup and view all the answers

Which of the following best describes the focus of business metadata?

<p>Offers an understandable view of information in the data warehouse. (D)</p> Signup and view all the answers

What is a characteristic of a data warehouse compared to a data mart?

<p>Data warehouses have a larger overall size. (D)</p> Signup and view all the answers

In the context of data warehouses, what is meant by 'virtual warehouse'?

<p>A view over an operational data warehouse. (A)</p> Signup and view all the answers

What is the main advantage of using ETL tools in data warehouses?

<p>To ensure data availability from multiple sources. (A)</p> Signup and view all the answers

Flashcards

What is a data warehouse?

A large collection of business data used to help an organization make decisions. It's designed for analysis and understanding, not for operational tasks.

Subject-Oriented

Data in a data warehouse is organized around specific topics, like sales or customers, rather than individual applications. This makes it easier to analyze specific areas.

Integrated

Data from different sources is combined and integrated into a unified whole within a data warehouse, removing inconsistencies.

Time-Variant

All data in a data warehouse is associated with a specific time period, capturing its historical context. It includes past data, not just current values.

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Non-Volatile

Once data enters the data warehouse, it is not typically updated or deleted in real time. This ensures data stability and consistency for analysis.

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Metadata

Data about data, such as its source, structure, and meaning, is called metadata. It is used to build, maintain, and manage the data warehouse.

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Technical Metadata

Information about the warehouse's structure and design, used by administrators and designers.

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Business Metadata

Information that makes the data in the warehouse easy for users to understand.

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ETL

A software tool that extracts, cleans, transforms, and loads data into a data warehouse.

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Data Mart

A subset of a data warehouse focused on a specific business line or team, like sales or marketing.

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Query Tools

Tools that allow users to interact with and analyze data in a data warehouse.

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Data Warehouse vs Data Mart

Data warehouses store enterprise-wide data, while data marts are focused on departmental needs.

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Three-Tier Data Warehouse Architecture

A three-tiered architecture for data warehouses includes the data warehouse database, the OLAP server for analysis, and the front-end client layer.

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Virtual Warehouse

A virtual warehouse provides a view of operational data, often using data virtualization techniques.

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What is a data mart?

A data mart is a smaller, focused data warehouse. It contains a subset of data from a larger warehouse, specifically valuable to a department or team.

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What are data marts typically built on?

Data marts are typically implemented on low-cost servers, often running on Unix or Linux operating systems.

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What's an enterprise warehouse?

An enterprise warehouse is a comprehensive data repository designed for organizations to store and analyze data from various sources.

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What is OLAP?

Online Analytical Processing (OLAP) is a technique that allows users to analyze data from different perspectives and dimensions.

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What is Relational OLAP (ROLAP)?

Relational OLAP (ROLAP) uses relational databases to manage multidimensional data, offering flexibility and scalability.

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What is Multidimensional OLAP (MOLAP)?

Multidimensional OLAP (MOLAP) stores data in a multidimensional array format, making it efficient for fast analysis.

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What is Hybrid OLAP (HOLAP)?

Hybrid OLAP (HOLAP) combines the features of both ROLAP and MOLAP, offering a balanced approach.

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What are Specialized SQL Servers?

Specialized SQL servers are designed specifically to handle large data volumes and complex queries.

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What are the Characteristics of OLTP Systems?

OLTP systems handle large numbers of users performing short transactions that require quick responses. They emphasize speed and efficiency.

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How do OLTP Systems Ensure Reliability?

OLTP systems aim to avoid single points of failure by being decentralized, meaning data is distributed across multiple servers.

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What is the Transactional Nature of OLTP?

OLTP systems are transaction-oriented, meaning they focus on capturing and managing individual actions and data changes.

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Study Notes

Data

  • Data is information collected through observation, measurement, research, or analysis.
  • Data can include facts, numbers, names, figures, or descriptions of things.
  • Data is often organized into graphs, charts, or tables.

Data Warehousing

  • A data warehouse is a large collection of business data used to aid organizational decision-making.
  • It's a subject-oriented, integrated, time-variant, and non-volatile collection of data used to support management's decision-making process.
  • Subject-oriented: Data is stored by subject, not application; e.g., "sales" is a subject.
  • Integrated: Data from various sources is combined into a coherent whole.
  • Time-variant: Data is identified with a specific time period, including historical data.
  • Non-volatile: Data is not updated or deleted in real-time; data is stable, and new data is added but not removed.

Data Warehousing Components

  • Data warehouse database: The central component where data is stored using RDBMS technology.
  • Metadata: Data about data; used for building, maintaining, and managing the data warehouse.
    • Technical metadata: Contains information on warehouse data for designers and administrators.
    • Business metadata: Provides a user-friendly view of stored information.
  • Extract, transform, load (ETL) tools: Used for searching, replacing, and populating missing data in a warehouse.
  • Data marts: Subsets of the data warehouse focused on specific business lines or teams.

Data Warehouse Models

  • Virtual warehouse: A view of an operational data warehouse, easily built but requiring extra capacity on operational database servers.
  • Data mart: A subset of organization-wide data that is valuable to specific groups within an organization; often implemented on low-cost servers and customized to departments.
  • Enterprise warehouse: Collects all information from the organization, providing enterprise-wide data integration from operational systems and external providers, varying in size (gigabytes to terabytes).

Online Analytical Processing (OLAP)

  • OLAP is a software category that enables analysis of data from multiple databases simultaneously.
  • OLAP enables a variety of views of business data.
  • Types of OLAP servers
    • Relational OLAP (ROLAP): Uses relational databases.
    • Multidimensional OLAP (MOLAP): Uses array-based multidimensional storage.
    • Hybrid OLAP (HOLAP): Combines ROLAP and MOLAP.
    • Specialized SQL servers: Provide advanced query language and query processing for SQL queries.

Online Transaction Processing (OLTP)

  • OLTP is a software category supporting transaction-oriented applications (e.g., order entry, financial transactions, CRM, retail sales).
  • OLTP systems support a large number of users conducting short transactions.
  • OLTP queries are typically simple, requiring sub-second response times and returning relatively few records.
  • Key attributes: concurrency and decentralized design to avoid single points of failure.

Data Warehouse and Data Mart Differences

Feature Data Warehouse Data Mart
View Enterprise-wide Departmental
Implementation Takes more time Less time to implement
Size Larger than 100 TB Smaller than 10 TB
Response Time Slower Faster
Scope Union of all data marts Single business process

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Data Warehousing Unit 1 PDF

Description

This quiz covers the fundamentals of data collection and organization, focusing on data warehousing concepts. Participants will explore key components, including the characteristics of a data warehouse and its role in decision-making processes. Ideal for those looking to deepen their understanding of data management.

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