Unit 33 Data Analysis Design

Unit 33 Data Analysis And Design

Unit 33 Data Analysis And Design,Copyright Statement:
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Unit 33 Data Analysis Design

  1. INTRODUCTION

Unit 33 Data Analysis DesignAn understanding of database tools and technologies is key to many of today’s industries. Database systems are predominant in the world of IT, and continue to demand more complex data structures and interface, as applications get increasingly sophisticated.

Databases provide the infrastructure to many organisations, and they offer support to key business applications and information systems. The most common database model used commercially is the relational one.

The aim of this unit is to provide a knowledge and understanding of database systems including design principles, practical implementation and development skills for both the system designer and software engineer. The importance of structured query languages should be stressed, in terms of how they can be used to manipulate data and how they are used for a variety of tasks including querying and report writing.

On completion of this unit the learner should be able to understand, design, query and implement a database(s). Learners will also have a theoretical insight into the requirement for designing a database that meets a given user or system requirement and that is functional, user friendly and robust. 

Aim:

To provide learners with the knowledge and skills needed to understand, design, query and implement database systems. 

Key Objectives:

  1. Understand data models and database technologies
  2. Be able to design and implement relational database systems
  3. Be able to use manipulation and querying tools
  1. Be able to test and document relational database systems. 

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Indicative content:

1 Understand data models and database technologies 

Data models: Hierarchical; Network; Relational; data manipulation languages; data definition languages; data independence; data redundancy issues; data integrity; schema; e.g. tables fields relationships, views, indexes; conceptual scheme; physical scheme, data dictionary.

Approaches: top down and bottom up; tools and techniques e.g. entity analysis, Entity Relation Diagrams (ERDs), determinacy diagrams, data flow diagrams; entities; attributes and key identifiers; relationship types and enterprise rules; degrees of relationships; functional dependency; first, second and third normal forms New developments: dynamic storage; data mining and data warehousing; web enabled database applications; other developments e.g. multimedia databases, document management systems, digital libraries

2 Be able to design and implement relational database systems 

Designs: data types; entity and referential constraints; conversion of logical database design to a physical implementation; tools and techniques; issues around the degree of normalisation chosen; verification and validity checks; data definition; control mechanisms

Requirements: requirements specification; relational requirements; other requirements e.g. need to integrate with legacy systems, future requirements, timescales, costs. User interface: requirements e.g. functionality, reliability, consistency, performance, menu driven, HCI interface

3 Be able to use manipulation and querying tools

Data manipulation: query languages; visual tools; typical tasks e.g. for database maintenance, inserts, updates and amendments

Queries and reporting: query languages and query by example (QBE); formatting; functions/formulae; report writing tools

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