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Structured tools and techniques of Data analysis

 Structured analysis and design (SAD) is a methodology used to develop information systems. It utilizes a collection of tools and techniques that facilitate a logical and systematic approach to understanding the system's needs, designing its architecture, and implementing it.

Here are some of the structured tools and techniques used for data analysis in SAD:

  • Data Flow Diagrams (DFDs): These graphical representations depict the flow of data through a system. DFDs illustrate the system's processes, external entities that interact with the system, and the data that flows between them.

    Image of Data Flow Diagram (DFD)Opens in a new windowblog.hubspot.com

  • Entity-Relationship Diagrams (ERDs): ERDs visually represent the entities (data objects) within a system, the attributes of those entities, and the relationships between them. ERDs are particularly useful for modeling data in relational databases.

    Image of EntityRelationship Diagrams (ERD)Opens in a new windowen.wikipedia.org

  • Data Dictionary: This is a centralized repository that defines and documents all the data elements used within a system. The data dictionary provides a consistent and clear understanding of the data's meaning, usage, and format.

  • Decision Trees and Decision Tables: Decision trees are flowcharts that illustrate the sequence of decisions and alternatives made within a system based on certain conditions. Decision tables, on the other hand, systematically document these decisions and alternatives in a tabular format, making it easier to analyze complex decision-making logic.

    Image of Decision TableOpens in a new window
    en.wikipedia.org

These structured tools and techniques are beneficial for data analysis in SAD because they:

  • Enhance communication and collaboration: By providing visual representations of data flow, entities, and decision logic, structured tools promote clear communication and collaboration between system analysts, designers, and developers.

  • Improve data quality: The process of creating data models and documenting data elements in a data dictionary helps ensure data consistency, accuracy, and completeness.

  • Facilitate system design: Structured data analysis tools provide a foundation for designing the system's architecture, including data storage, processing, and retrieval mechanisms.

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