Data Integration Concepts and Interoperability

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Questions and Answers

What is a primary disadvantage of real-time updates in distributed systems?

  • Higher maintenance costs
  • Latency in query responses (correct)
  • Easier integration of base systems
  • Increased flexibility of applications

How do applications typically access local bases in application-level integration?

  • By storing data on a central server
  • Employing batch processing methods
  • Through direct database connections
  • Using APIs or middleware (correct)

What challenge associated with multiple database systems involves differences in data structure?

  • Performance issues related to latency
  • Inefficient data transformation
  • Complexity of user interfaces
  • Heterogeneity of schemas (correct)

What is a significant advantage of having multiple local databases in an integrated system?

<p>Increased scalability (B)</p> Signup and view all the answers

Which disadvantage is specifically related to application-level integration?

<p>Redundancy of effort in implementing integration logic (D)</p> Signup and view all the answers

What does the autonomy of local databases hinder in a federated system?

<p>Integration of data across systems (A)</p> Signup and view all the answers

What is one potential consequence of high computational costs in distributed queries?

<p>Strain on system resources (A)</p> Signup and view all the answers

What is a primary benefit of using existing infrastructures in multiple database systems?

<p>Cost savings through resource efficiency (B)</p> Signup and view all the answers

What does the Global Conceptual Schema (GCS) represent?

<p>A unified view that integrates local conceptual schemas (B)</p> Signup and view all the answers

Which of the following is a characteristic of Data Integration?

<p>Creating a centralized or logically unified system (D)</p> Signup and view all the answers

What is the primary difference between physical and logical data integration?

<p>Physical integration centralizes data storage, while logical keeps data in local systems. (C)</p> Signup and view all the answers

Why is coordination necessary for data integration?

<p>To ensure different systems can cooperate and share data (C)</p> Signup and view all the answers

What role do mediators play in a federated database system?

<p>They translate global schema queries to local databases (C)</p> Signup and view all the answers

What is the main advantage of a federated database system?

<p>Complete independence of local databases (C)</p> Signup and view all the answers

Interoperability allows different systems to do what?

<p>Interact without needing to unify their data models (D)</p> Signup and view all the answers

What is an example of a physical data integration method?

<p>Employing a data warehouse for centralized storage (D)</p> Signup and view all the answers

Flashcards

Local Conceptual Schema (LCS)

Represents the local schema of each individual database, serving as a blueprint for its specific structure and data.

Global Conceptual Schema (GCS)

A unified schema that combines all the Local Conceptual Schemas (LCSs), offering a comprehensive view of all the data across different databases.

Integration of Data

The need to combine data from various sources, often with different formats and structures, into a single, unified system.

Heterogeneity

Different databases may use distinct data models (like relational or NoSQL), file formats, and structures, making it difficult to directly combine data.

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Coordination

The integration allows various systems to cooperate and share data, creating a cohesive flow of information.

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Global Analysis

Organizations with databases spread across different departments need to consolidate information for thorough analysis.

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Data Integration

The process of merging data from different sources into a centralized or logically unified system.

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Interoperability

The ability for different systems to interact and exchange information without needing to be physically unified.

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Real-Time Update in Federated Database System

A method of integrating multiple databases where queries are executed directly on the local databases, offering real-time updates and reflecting the most recent data.

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Latency in Federated Database Systems

The time delay between sending a query and receiving results in a federated database system due to communication between distributed systems.

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Connectivity in Federated Database Systems

The dependence on a reliable connection between local databases and the federated system for queries and data exchange.

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Application-Level Integration

An approach where integration logic is implemented directly within the applications that consume the data.

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APIs or Middleware for Application-Level Integration

APIs or middleware that enable applications to access local databases in application-level integration.

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Local Transformation in Application Level Integration

The process of each application independently combining and processing data retrieved from local databases according to its custom rules.

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Heterogeneity of Data Schemes

Differences in data semantics, structure, and data types across local databases.

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Autonomy in Local Databases

Local databases having full control over their data, potentially creating integration challenges.

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Study Notes

Data Integration

  • Concepts and Need for Systems with Multiple Databases
    • Local Conceptual Schema (LCS): Represents the local schemas of each database.
    • Global Conceptual Schema (GCS): Unified schema integrating LCSs, providing a combined view.
    • Need for Integration: Driven by heterogeneity (different models and formats), coordination (for system cooperation and data sharing), and global analysis (for deeper insights across departmental data).

Data Integration vs. Interoperability

  • Data Integration: Process of combining data from disparate sources into a unified system. Creates a global view, consolidating heterogeneous data for consistent access.
    • Types:
      • Physical Integration: Data extracted, transformed, and stored in a central repository (e.g., data warehouses, data lakes).
      • Logical Integration: Data remains in local systems but accessed and combined in real-time through a federated system (e.g., mediation systems with wrappers for translation).
  • Interoperability: Systems can interact without full unification. Uses middleware for translating and processing queries directly on local databases.

Integration Approaches

  • Federation: Local databases remain autonomous, integration is virtual and real-time. GCS defines the global view.

    • Mechanism:
      • Mediators: Translate global schema queries to local databases, combining results for a unified view.
      • Wrappers: Adapt local databases for interaction with the federated system.
    • Advantages: Local autonomy, real-time updates.
    • Disadvantages: Potential latency, reliance on reliable connections.

  • Application-Level Integration: Integration logic implemented directly in consuming applications. Applications interact with local databases individually, combining data as needed.

    • Mechanism:
      • APIs or Middleware: Applications use APIs or middleware to access local databases.
      • Local Transformation: Each application implements its data combination and processing rules.
    • Advantages: Flexibility, easy implementation compared to federation.
    • Disadvantages: Potential redundancy in integration logic, scalability issues.

Challenges and Advantages of Multi-Database Systems

  • Challenges: Heterogeneity of schemas (semantic, structural, and data type differences), autonomy (local databases have full control), and performance (distributed queries can have latency).
  • Advantages: Flexibility (updating local systems without affecting the GCS), scalability (adding new databases), and resource economy (leveraging existing infrastructures).

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