Information and Data - 2024 entry
MODULE TITLE | Information and Data | CREDIT VALUE | 15 |
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MODULE CODE | ECM1420DA | MODULE CONVENER | Dave Dann (Coordinator) |
DURATION: TERM | 1 | 2 | 3 |
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DURATION: WEEKS | 0 | 11 | 0 |
Number of Students Taking Module (anticipated) | 100 |
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***DEGREE APPRENTICESHIP STUDENTS ONLY***
This module provides you with an introduction to the core concepts in data and information management. It is centred on the core skills of identifying organisational information requirements, modelling using conceptual data modelling techniques and converting the conceptual data models into relational data models, and then implementing and utilising a relational database using an industry standard database management system.
The module will also include coverage of basic database administration tasks and key concepts of data quality and data security. In addition to developing database applications, you will learn how large-scale packaged systems are highly dependent on the use of database management systems.
The aim of this module is to ensure that you have a good understanding of data, information and systems used to manage data and information. In particular, you should be able to demonstrate the following competences:
- Identify organisational information requirements and can model data solutions using conceptual data modelling techniques.
- Be able to implement a database solution using an industry standard database management system (DBMS).
- Be able to perform database administration tasks and be cognisant of the key concepts of data quality and data security.
- Be able to manage data effectively and undertake data analysis.
On successful completion of this module you should be able to:
Module Specific Skills and Knowledge
1. Apply data analysis and data modelling techniques, to design data structures based on business requirements
2. Use at least one conceptual data modelling technique (such as entity-relationship modelling) to capture the information requirements for an enterprise domain
3. Implement a database system using a mainstream database product such as Oracle or SQL
4. Translate object and data models into appropriate database schemas within design constraints
5. Evaluate potential data solutions to meet requirements
6. Design high-quality relational databases
7. Use the data definition, data manipulation, and data control language components of SQL in the context of one widely used implementation of the language
8. Perform simple database administration tasks
Discipline Specific Skills and Knowledge
9. Understand the role of databases and database management systems in managing organisational data and information
10. Understand the historical development of database management systems and logical data models
11. Understand the basics of how data is physically stored and accessed
12. Understand the fundamentals of the basic file organisation techniques
13. Understand the purpose and principles of normalizing a relational database structure
14. Understand the concept of database transaction and apply it appropriately to an application context
15. Understand the basic mechanisms for accessing relational databases from various types of application development environments
16. Understand the role of databases and database management systems in the context of enterprise systems
17. Understand the key principles of data security and identify data security risk and violations in data management system design
18. Understand the core concepts of data quality and their application in an organisational context
19. Understand what is meant by data warehousing and data mining
Personal and Key Transferable / Employment Skills and Knowledge
20. Communicate orally and in writing
21. Think analytically and critically
22. Organise your own work
23. Work to a deadline
24. Make decisions
Introduction to data and information management (3 weeks)
• File organisation and data structures
• Structured and unstructured data
o HTML, CSV, XML, JSON
• Data quality; audit and compliance
• Databases and database management systems
o Historical development
o Role of DBMS in managing organisation data and enterprise systems
o Conceptual, logical and physical data models
o Relational and NoSQL databases; big data
• Data integration
• Data warehousing; data mining; business intelligence; data analytics
• Evaluating potential data solutions to meet requirements
• Introduction to data security principles
• Identifying data security risks and violations in data management system design
Conceptual data modelling (3 weeks)
• Capturing information requirements for an enterprise domain
• Entity-relationship diagrams
• Object modelling with UML class diagrams
• Data normalisation
Database design and implementation (2 weeks)
• Logical and physical data models
• Translating object and data models into database schemas
• Database implementation using Oracle or SQL Server
• Cloud data storage
• Indexing and performance
SQL (3 weeks)
• Data definition language
• Data manipulation language
• Database transactions
• Accessing databases from application development environments
• Simple database administration
o Data control language
Scheduled Learning & Teaching Activities | 22 | Guided Independent Study | 128 | Placement / Study Abroad | 0 |
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Category | Hours of study time | Description |
Scheduled learning and teaching activities | 18 | Online learning activity, including virtual workshops, synchronous and asynchronous virtual lectures and other e-learning. |
Scheduled learning and teaching activities | 2 | Lectures |
Scheduled learning and teaching activities | 2 | Group workshops |
Guided independent study | 128 | Coursework, exam preparation and self-study |
Form of Assessment | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Contribution to class discussion | N/A | 1-24 | Verbal |
Coursework | 50 | Written Exams | 50 | Practical Exams | 0 |
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Form of Assessment | % of Credit | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Data modelling and design exercise | 50 | 2000 words | 1-4, 6-8, 13,20-24 | Written |
Written exam | 50 | 1.5 hours | 1-24 | Written |
Original Form of Assessment | Form of Re-assessment | ILOs Re-assessed | Time Scale for Re-assessment |
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Data modelling and database design exercise (50%) | Data modelling and design exercise (2000 words) | 1-4, 6-8, 13,20-24 | Completed over summer with a deadline in August |
Written exam (50%) | Written exam (1.5 hours) | 1-24 | Referral/deferral period |
Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be deferred in the assessment. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.
Referral – if you have failed the module overall (i.e. a final overall module mark of less than 40%) you may be required to sit a referral. The mark given for a re-assessment taken as a result of referral will be capped at 40%.
information that you are expected to consult. Further guidance will be provided by the Module Convener
ELE: https://ele.exeter.ac.uk/
Reading list for this module:
Type | Author | Title | Edition | Publisher | Year | ISBN |
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Set | Gordon, K | Principles of Data Management | 2nd | BCS | 2013 | ISBN-13: 978-1780 |
CREDIT VALUE | 15 | ECTS VALUE | 7.5 |
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PRE-REQUISITE MODULES | None |
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CO-REQUISITE MODULES | None |
NQF LEVEL (FHEQ) | 4 | AVAILABLE AS DISTANCE LEARNING | No |
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ORIGIN DATE | Thursday 14th March 2024 | LAST REVISION DATE | Thursday 14th March 2024 |
KEY WORDS SEARCH | Information, data |
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Please note that all modules are subject to change, please get in touch if you have any questions about this module.