Software Engineering & Big Data Modelling

Περιγραφή Μαθήματος - Περιεχόμενο Μαθήματος: 

Course Aim
The course aims to present the principles, techniques, and methods for professional and systematic software development. The Unified Modeling Language (UML), CASE tools like Visual Paradigm and programming languages like Python and JAVA, will be used in the context of this course. Furthermore, the course shows how to handle the volume, speed and variety of big data of SQL and noSQL databases. It also looks at issues related to data management and data quality. In order for students to deepen in Software engineering and big data modelling, several software examples will be examined during the course lectures.
After completing the course the student will have the necessary knowledge to:

  • Be able to design software,
  • Use CASE tools for analyzing and designing software,
  • Be able to administer the software development,
  • Be able to use language modeling systems,
  • Be able to implement professional software,
  • Identify different data items,
  • Select a data model that matches its data characteristics,
  • Apply techniques for managing flow data,
  • Know differences between a traditional database management system and a large data management system,
  • Recognize why there are so many data management systems.

Indicative Course Syllabus
Software creation and management

  • System description languages - Unified Modelling Language (UML)
  • Designing software

Requirements analysis
Software design engineering
Software design trade-offs
Software implementation planning
  Software design techniques

  • Software development process management

Software development methods
  Rapid application development
  Agile software development
  Capability Maturity Model
  Waterfall model
  Spiral model
  Design patterns
Risk management

  • Software development techniques

Software prototyping
Object oriented development
  Software product lines
Error handling and recovery

  • Big Data Modeling

Introduction to Big Data Modelling
  Introduction to Data Models (Structures, Operations & Constraints)
  Introduction to Relational Data Models and Semi-structured Data Models
  XML versus JSON on the Internet
  Exploring the Relational Data Model of Comma Separated Values (CSV)
  Exploring the Semi-structured Data Model of JSON data
  Vector Space Model, Graph Data Model, Other Data Models
Working With Data Models
  Data Model vs. Data Format
  Data Streams
  Data Lakes
  Streaming data applications
  Exploring Streaming Sensor Data
Big Data Management: The "M" in DBMS
  DBMS-based and non-DBMS-based Approaches to Big Data
  From DBMS to BDMS

  1. Ian Sommerville, “Software Engineering” (8th edition), Addison-Wesley, May 25, 2006
  2. Pfleeger Shari Lawrence, “Τεχνολογία λογισμικού Θεωρία και Πράξη”, Α' & Β’ ΤΟΜΟΣ, Κλειδάριθμος, 2003
  3. Grady Booch, James Rumbaugh, “The Unified Modeling Language User Guide”, (2nd Edition), Pearson Education Limited, 2005
  4. Grady Booch, Robert A. Maksimchuk, J. Newkirk, “Object Oriented Analysis and Design with Applications”, Pearson Education Limited, 2007
  5. Martin Fowler, “UML Distilled: A Brief Guide to the Standard Object Modeling Language” (3rd Edition) (The Addison-Wesley Object Technology Series) (Paperback), Pearson Education Limited, 2003
  6. Alan Dennis, “Systems Analysis & Design with UML”, 2nd Edition with Visio 2007 Set, John Wiley and Sons Ltd, 2008
  7. Ivar Jacobson, Grady Booch, James Rumbaugh: “The Unified Software Development Process”, Addison-Wesley, 1999
  8. Ivar Jacobson, Magnus Christerson, Patrik Jonsson, Gunnar Oevergaard: “Object-Oriented Software Engineering (A use case Driven Approach)”, Addison-Wesley, 1995
  9. Rational Rose Home Page: index.jtmpl
  10. Object Management Group – UML:
  11. The Carnegie Mellon Software Engineering Home: http:// /sei-home.html
  12. RabbitMQ in Action: Distributed Messaging for Everyone, Manning Pubs Co Series, Alvaro Videla, Jason J. W. Williams, Manning Publications Company, 2012, ISBN 1935182978, 9781935182979
  13. Evan Stubbs, Big data, big innovation: enabling competitive differentiation through business analytics, 2018 ISBN 978-1-118-72464-4
  14. Pete Warden, Big Data Glossary, 2011, O’Reilly, ISBN: 978-1-449-31459-0
Ακαδημαϊκός Υπεύθυνος: 
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Βιδάκης Νικόλαος
Vidakis Nikolaos
(+30) 2810 379892
nv's picture
Βιδάκης Νικόλαος
Vidakis Nikolaos
(+30) 2810 379892

Papadourakis George Professor,

Address: Department of Electrical and Computer Engineering, School of Engineering, Hellenic Mediterranean University Heraklion, Crete,
P.O Box: 71500
Tel: 2810-379170, Fax: 2810-379717

Tel: 2810-379708, 379776