Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title ADVANCED DATABASE SYSTEMS
Code CKIT536
Coordinator Mr K Dures
Computer Science
K.Dures@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2021-22 Level 7 FHEQ Whole Session 15

Aims

1. To develop the knowledge and skills required to design and implement modern database systems.     2. To provide students with an in depth and critical understanding of commercial database development and management best practices.   3. To provide students with the necessary knowledge to allow them to be able to compare and contrast the established relational database paradigm with emerging alternative approaches so that they can make informed choices when considering database provision.   4. To provide students with a deep and comprehensive understanding of advanced database technologies, including (but not limited to) advanced transaction management, emerging data models, advanced resiliency techniques and security protocols for securing data especially in the cloud.


Learning Outcomes

(LO1) Demonstrate a comprehensive understanding of transaction management, concurrency control and recovery.

(LO2) Critically evaluate alternative designs for databases and data warehouses.

(LO3) Design database systems using advanced modelling tools and techniques.

(LO4) Demonstrate a comprehensive understanding of big data and the modelling techniques used to manage them.

(LO5) Critically appraise database technologies to satisfy business requirements for an enterprise system.

(LO6) Evaluate database characteristics for optimal database performance and resilience.

(LO7) Analyse the security requirements for database systems.

(S1) Communication skills

(S2) IT skills

(S3) Communication and collaboration online participating in digital networks for learning and research

(S4) Problem solving/critical thinking/creativity

(S5) Team (group) working respecting others, co-operating, negotiating / persuading, awareness of interdependence with others


Syllabus

 

Week 1: An evaluation of modern database systems : Comparison of relational, document, column and graph databases in the context of typical use cases including OLTP, OLAP, big data, business intelligence, semantic searching; relational algebra versus relational calculus in the context of data access and different database technologies.   Week 2: Database Systems Architecture : Data governance; database technology neutrality (loose coupling); data movement (batch to near real-time); master data management; data as a service (DBCloud); security (dealt with in more detail in a later week); n-tier client/server architectures; micro service data architecture.   Week 3: Applying data models : Translating business requirements into appropriate data models such as Entity Relationship and Relational Data Models; normalisation; keys; integrity; indexes; data dictionaries; emerging data models (Big Data, NoSQL) and the impact on normalisation; focus Considerations for non-relati onal databases (e.g. document, columnar, graph databases).   Week 4: Transactional Databases : ACID; transaction management; concurrency; recovery; considerations for distributed databases; streaming and event processing data; considerations for non-relational databases (e.g. document database).   Week 5: Design Modelling techniques using Data Analytics : Large Data:   architecture; data marts; multidimensional modelling (schema comparison); Star schema; business Intelligence tools and approaches; statistical analysis tools   Week 6: Managing Data : Characteristics of Big Data; NoSQL and NewSQL database types; data quality, data cleaning, data compression. Hybrid solutions (relational and non-relational); data ingest approaches; schema-on-read; data virtualisation approaches   Week 7: Database performance and resilience : Virtualisation; parallelism; clustering; load balancing; appliances v commodity computing; cloud computing; SQL tuning / optimisati on; caching; volumetrics; partitioning; sharding.   Week 8: Security : Role-based access controls and management; business impact assessment; encryption in transit and at rest; data retention policy; network segregation; data deletion policy; security specific to cloud-based systems; authentication and authorisation; backup policy; disaster recovery; audit; patching; data handling and movement processes.


Teaching and Learning Strategies

Teaching Method 1 - online Learning
Description: Weekly seminar supported by asynchronous discussion in a virtual classroom environment facilitated by an online instructor.
Attendance Recorded: Yes
Notes: Number of hours per week that students are expected to attend the virtual classroom so as to participate in discussion, dedicated to group work and individual is 7.5


Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours           60

60
Timetable (if known)              
Private Study 90
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
             
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Group Project: Design a Database system Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Weeks 4-7  Four weeks.    25       
Programming: Enterprise database system architecture Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 8  One week         
Report: Analysis of benefits and limitations of distributed systems Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 6  One week: 350-500 wo         
Practical assignment: Online Analytical Processing (OLAP) Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 5  One week         
Moot/debate: 7 weekly discussion question moot/debate Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Whole session  Weekly Discussion Qu    40       
Case study analysis: Transaction analysis, evaluation and comparison Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 4  One week: 350-500 wo         
Report: Enterprise systems that provide data as a service. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 2  One week: 350-500 wo         
Practical assignment: Application of relational algebra and calculus Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 1  One week         
Design output: Data models for relational and non-relational solutions Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :Week 3  One week         

Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.