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Masters Degrees (Data Warehousing)

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The programme is designed to provide in-depth knowledge and skills within the field of computing. The course is aimed at students who already have a first degree in computing, have some existing software engineering skills, and wish to deepen their knowledge. Read more
The programme is designed to provide in-depth knowledge and skills within the field of computing. The course is aimed at students who already have a first degree in computing, have some existing software engineering skills, and wish to deepen their knowledge. This programme will have a strong focus on how data can be exploited within an organisation and will emphasise the communication of that data to a target audience.

Graduates would undertake a range of tasks associated with IT in organisations, and develop sophisticated solutions to IT problems.

Course Overview

The main themes of the programme are:
-Web based application development
-Database development, deployment and integration
-Project and team management in the computing sector

This programme will equip students with those skills at a high academic level and also crucially enable them to practically implement their knowledge because of the ‘hands-on’ emphasis of the programme.

Each of these themed areas is itself an area of significant international strategic importance and will enable students to gain important and valuable skills.

The Web based application development theme reviews current trends and technologies. Complex challenges faced by web developers are investigated in detail.

The Database development, deployment and integration theme covers the important areas of Data Warehousing and Data Analysis both of which are cited as important skills that are in great demand by businesses.

The final theme, Project and team management will concentrate on developing the skills of project management and systems analysis, both of which are in great demand by employers.

Modules

Part 1:
-Data Warehousing (20 credits)
-Distributed Web Apps (20 credits)
-Leadership and Management (20 credits)
-Managing Information Systems and Projects (20 credits)
-Research Methods and Data Analysis (20 credits)
-Web Technologies for e-Commerce (20 credits)

Part 2:
-Major Project (60 credits)

Key Features

This MSc provides significant technical content which will inform the management decision making process. In this context major organisations such as Tesco, Sainsbury and Amazon have been making significant investment into data warehousing and data mining technologies.

To effectively use this technology requires a large number of people to apply and manage the technology. The price of the technology has reduced significantly since the inception of data warehousing with Microsoft and Oracle supplying the appropriate add-on tools to their database management system products. These factors allow smaller organisations to gain a competitive advantage by utilising the large pool of transactional data that in some cases has been stored for many years.

In an industrial context, students may be required to manage teams of developers in small to large scale projects. To efficiently manage such projects, they will require a significant technical understanding of the issues arising to be able to appreciate the complexity of the tasks to be undertaken.

Indeed, in an SME this role is often fulfilled by a senior member of the development staff with both development and management duties. As either a developer or manager, the graduate would be expected to demonstrate their initiative and be able to use their research skills to rapidly adapt to the demands of new technology.

Assessment

Student works are assessed through combination of course works, lab based practical exams and written exam. The final mark for some modules may include one or more pieces of course work set and completed during the module. Project work is assessed by a written report and oral presentation. Part 2 of the MSc programme requires the student to research and prepare an individual project/dissertation of a substantial nature.

University students who are unable to successfully complete all aspects of the Part 1 may be eligible for a Postgraduate Diploma (120 credits) or Postgraduate Certificate (60 credits).

Career Opportunities

Students on this programme develop a broad range of technical skills and will study a number of topics related to information systems. The programme covers the three themes of Web based application development, Database development, deployment and integration, and Project and Team management in the computing sector.

A significant emphasis is placed on database management and the implementation of applications for manipulating information including both database systems and web applications. Additionally, graduates would be able to lead teams and manage projects.

It is expected that graduates would seek positions such as:
-Project manager (within the Computing field)
-Data analyst
-Database administrator
-Application developer
-Web developer

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Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. Read more

Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. This is one of the first MSc programmes in the UK covering these leading-edge technologies. The programme provides students with the deeper knowledge, advanced skills and understanding that will allow them to contribute to the development and design of big data systems as well as distributed/internet-enabled decision support application software systems, using appropriate technologies, architectures and techniques (e.g. data analytics, business intelligence, NoSQL, data mining, data warehousing, distributed data management and technologies, Hadoop, etc.).

Additionally, the programme enables students to understand and assess the security and legal implications of e-commerce applications and provides students with appropriate knowledge of business and commerce relevant to transacting business on the internet. The courses take a software engineering approach to the construction of applications and focus on modern software engineering methods, tools and techniques that enable an integrated life-cycle software development view.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

Full time

Year 1

Students are required to study the following compulsory courses.

Students are required to choose 15 credits from this list of options.

Students are required to choose 15 credits from this list of options.

Part time

Year 1

Students are required to study the following compulsory courses.

Year 2

Students are required to study the following compulsory courses.

Students are required to choose 15 credits from this list of options.

Students are required to choose 15 credits from this list of options.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Careers

Graduates from this programme can pursue careers as data scientists, database designers and administrators, consultants, senior team members, programmers, analysts.



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There is an enormous and increasing amount of data that is collected. Examples include not just traditional data such as sales transactions, but location data (GPS), interactions between people on social network, measurements of sleep patterns, medication being taken, state of health, and much much more. Read more

There is an enormous and increasing amount of data that is collected. Examples include not just traditional data such as sales transactions, but location data (GPS), interactions between people on social network, measurements of sleep patterns, medication being taken, state of health, and much much more.

A key challenge is then to make use of this wealth of data. How can we manage this data, and analyse it to exploit useful information that can guide decision making?

This emerging area goes under the name “Data Science”. There is growing demand for people, “Data Scientists”, who have the skills to manage and analyse enormous amounts of data using a range of techniques such as data mining, statistical techniques, and machine learning.

Data Scientist has been called the “Sexiest job of the 21st century”, and the unique combination of technical skills (stats, data management) and business understanding has been said to make Data Scientists “highly sought after and highly paid”.

Master of Business Data Science (MBusDataSc)

The MBusDataSc primary focus is to equip you to become a practitioner, allowing you to meet the needs of industry, and solve the data problems of the world. However, there will also be an alternative path that will focus on preparing students for research in the area (e.g. going on to do a masters by research or PhD).

The proposed degree is inherently multidisciplinary, featuring Information Science and Marketing, which gives the degree a strong business focus; as well as contributions from Computer Science and from Statistics.

Once you have completed the MBusDataSc you will have developed an advanced knowledge of data science. You will understand how data analysis can be used in business, including being able to identify opportunities to use data, be aware of ethical and privacy issues and possible mitigations, and be able to select appropriate means of presenting the results of analysis. You will be able to select and apply techniques to manage and analyse large collections of data.

Degree Structure

The programme of study shall consist of seven 20 point taught papers together with a 40 point applied project or research project. Papers are either taught in semester one, semester two or are full-year papers. 

You must complete:

INFO 424 - Adaptive Business Intelligence  

COSC 430 - Advanced Database Topics

INFO 411 - Machine Learning and Data Mining

MART 448 - Advanced Business Analytics  

INFO 420 - Statistical Techniques for Data Science

INFO 408 - Management of large scale data

BSNS 401 - The Environment of Business & Economics

Plus one of the following project papers

BSNS 501 - Applied Project  

or

BSNS 580 - Research Project (for students who may wish to progress to PhD study)

Graduate Profile

The University of Otago coursework masters programmes provide you with an opportunity to specialise in advanced study with a focus on either applied practical or academic research.

Graduates of the MBusDataSc will gain skills in three areas: those relating to the business and organisational context, those relating to computing technologies for managing data, and those relating to data analysis techniques.

As a graduate of the MBusDataSc you should be able to:

  1. Understand where data analysis is used in business
  2. Identify opportunities to use data to improve decision making in a business context
  3. Be aware of ethical and privacy implications, concerns, and approaches to mitigating these, including the ability to identify potential areas of concern, and recommend appropriate mitigation actions
  4. Use appropriate means of communicating the results of analysis in graphical form
  5. Develop and maintain databases, including familiarity with performance management for large databases
  6. Have knowledge of a range of data storage and manipulation technologies (such as relational databases, NoSQL, XML), and the ability to select an appropriate technology for a given context and need
  7. Use high performance computing tools (including cloud computing) to manage and analyse data
  8. Be familiar with a range of data analysis approaches (e.g. statistical techniques, data mining, data warehousing), and be able to to select and apply these techniques to suit the context
  9. Develop an appreciation of the concept of ethics from multicultural perspectives, including Māori development aspirations and also an international business environment


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During this programme, students study, employ and reflect on the principles underpinning computer science. The programme is designed for individuals wishing to pursue careers as computer science professionals. Read more

During this programme, students study, employ and reflect on the principles underpinning computer science. The programme is designed for individuals wishing to pursue careers as computer science professionals.

From organisational culture and human-computer interaction to web services and distributed computing on virtualised and cloud based systems, this programme leads students to reflect on the choice of methods and tools. It will provide practical experience in the analysis and understanding of problems, systems and structures through the study of realistic case studies. The student will be equipped to deal with the intense demands of modern software development, critically evaluate and employ appropriate concepts and principles to build solutions of commercial, industrial or research value.

Students may choose options focusing on cyber security and forensics, data warehousing and business intelligence or user-centered web engineering and software engineering management.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

The availability of some courses is subject to satisfying constraints that may come into effect in the year of entry.

Full time

Year 1

Students are required to study the following compulsory courses.

Students are required to choose 15 credits from this list of options.

Students are required to choose 30 credits from this list of options.

Part time

Year 1

Students are required to study the following compulsory courses.

Students are required to choose 30 credits from this list of options.

Year 2

Students are required to study the following compulsory courses.

Students are required to choose 15 credits from this list of options.

Students are required to choose 15 credits from this list of options.

Students are required to choose 30 credits from this list of options.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. Please contact the BCS for further information. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Careers

Graduates from this programme are equipped for employment in industry, commerce or education with a proficiency in the key theoretical and practical areas in computer science, including their application to modern software systems development.



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Course content. Please note that this course will not start until September 2019. We have designed this MSc course in consultation with industry partners. Read more

Course content

Please note that this course will not start until September 2019.

We have designed this MSc course in consultation with industry partners.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to those looking for a career in helping businesses to make better decisions.

The course will be of specific interest to :

  • A mathematics graduate wishing to use your skills in a vocational business based environment
  • A computer science graduate wishing to follow a vocational route
  • Individuals currently working in Business and looking to grow their career through gaining Data Science and Business Analytics skills

We have developed a number of modules to make up this MSc:

  • Business Intelligence Foundation
  • Managing Data and Data Warehousing
  • Data Exploration and Analysis
  • Statistics and Operational Research
  • Operations Management and Performance Improvement (option)
  • Data Visualisation and Presentation (option)
  • Business Decision Making (option)

The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects.

You will be assigned a Personal Tutor from the start of your course who will work with you throughout your studies to help you achieve your academic best. 

The knowledge we provide you with in these areas will give you all of the essential know-how on methods, tools and techniques to deliver in your career in Business Intelligence.

The modules will be focused on the practical application of theoretical concepts using a range of contemporary enterprise management knowledge systems.

The project work we have imbedded within the course has been chosen and developed based on real-world scenarios across a range of industry and government sectors and is specifically designed to:

  • Provide an essential link between your theoretical learning and real-world challenges
  • Create an environment where you decide the methods and tools best suited to the challenge based on what you have learnt
  • Recreate some of the challenges facing industry today and those very similar to what you will encounter in the workplace
  • Be adaptable to reflect new methods / tools and scenarios in this fast developing discipline
  • Be able upon completion of the projects to reference your experience in working with such challenges

Our facilities

You will undertake your workshops in training rooms that are bang up-to-date with design features, touch screen electronic white boards and high speed wifi; housed across three stunning Georgian mansions.

All of our current students love the learning environment, the culture, camaraderie and the fact that tutors know them by name so they are more than just a ‘face in the crowd’. 

You will have access to the very best IT facilities in order to support your studies.

These range from computer labs to access to cloud analytics from the leading providers.

We will use software from the academic programs of the major enterprise I.T. vendors such as IBM and SAP as well as commonly used open source programs and frameworks. 

From September 2018, many of the teaching sessions will take place in the purpose-built Engineering and Digital Technology building in the Bognor Regis campus.

What's more, you have lots of other facilities on this dedicated university campus including latest books, journals and online data in a truly modern library, an IT centre, a student zone complete with Costa Coffee, a gym and much more.

Where this can take you

The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations. On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace.

Indicative modules

  • Business Intelligence Foundation (20 Credits)
  • Managing Data and Data Warehousing (20 Credits)
  • Data Exploration and Analysis (20 Credits)
  • Statistics and Operational Research (20 Credits)
  • Operations Management and Performance Improvement (option) (20 Credits)
  • Data Visualisation and Presentation (option) (20 Credits)
  • Business Decision Making (option) (20 Credits)
  • Dissertation/Project (60 Credits)

Teaching and assessment

Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following: 

  • We place a lot of emphasis on course work related activity.
  • Opportunities to work with organisations on current commercial/business problems and projects. These experiences are used to provide the basis for assessments that enable you to apply your learning within authentic commercial situations.


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Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains. Read more
Technologies based on the intelligent use of data are leading to great changes in our everyday life. Data Science and Engineering refers to the know-how and competence required to effectively manage and analyse the massive amount of data available in a wide range of domains.

We offer a two-year Master of Science in Computer Science centered on this emerging field. The backbone of the program is constituted by three core units on advanced data management, machine learning, and high performance computing. Leveraging on the expertise of our faculty, the rest of the program is organised in four tracks, Business Intelligence, Health & Life Sciences, Pervasive Computing, and Visual Computing, each providing a solid grounding in data science and engineering as well as a firm grasp of the domain of interest.

By blending standard classes with recitations and lab sessions our program ensures that each student masters the theoretical foundations and acquires hands-on experience in each subject. In most units credit is obtained by working on a final project. Additional credit is also gained through short-term internship in the industry or in a research lab. The master thesis is worth 25% of the total credit.

TRACKS

• Business Intelligence. This track builds on first hand knowledge of business management and fundamentals of data warehousing, and focuses on data mining, graph analytics, information visualisation, and issues related to data protection and privacy.
• Health & Life Sciences. Starting from core knowledge of signal and image processing, bioinformatics and computational biology, this track covers methods for biomedical image reconstruction, computational neuroengineering, well-being technologies and data protection and privacy.
• Pervasive Computing. Security and ubiquitous computing set the scene for this track which deals with data semantics, large scale software engineering, graph analytics and data protection and privacy.
• Visual Computing. This track lays the basics of signal & image processing and of computer graphics & augmented reality, and covers human computer interaction, computational vision, data visualisation, and computer games.

PROSPECTIVE CAREER

Senior expert in Data Science and Engineering. You will be at the forefront of the high-tech job market since all big companies are investing on data driven approaches for decision making and planning. The Business Intelligence area is highly regarded by consulting companies and large enterprises, while the Health and Life Sciences track is mainly oriented toward biomedical industry and research institutes. Both the Pervasive and the Visual Computing tracks are close to the interests of software companies. For all tracks a job in a start-up company or a career on your own are always in order.

Senior computer scientist.. By personalizing your plan of study you can keep open all the highly qualified job options in software companies.

Further graduate studies.. In all cases, you will be fully qualified to pursue your graduate studies toward a PhD in Computer Science.

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This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more

This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Course structure

The following modules are indicative of what you will study on this course.

Core modules

Option modules

Professional accreditation

This programme is accredited by BCS, The Chartered Institute for IT, for fully meeting the further learning educational requirement for Chartered IT Professional (CITP) status and for partially satisfying the underpinning knowledge requirements set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC) and the Science Council for Chartered or Incorporated Engineer (CEng or IEng) status. Note that there are additional requirements, including work experience, to achieve full CITP, CEng, or IEng status. Graduates of this accredited degree will also be eligible for professional membership of BCS (MBCS).

The BCS accreditation is an indicator of the programme’s quality to students and employers; it is also an important benchmark of the programme’s standard in providing high quality computing education, and commitment to developing future IT professionals that have the potential to achieve Chartered status. The programme is also likely to be recognised by other countries that are signatories to international accords.

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analysts, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (e.g. GlaxoSmithKline, British Airways, Santander and Unilever), public sector organisations (e.g. the NHS and primary care trusts), retail head offices, the BBC, the Civil Service, and the host of banks, brokers and regulators that make up the City, along with all the specialist support consultancies in IT and market research and forecasting, all of whom use data for the full range of decision making.

Work placements

Our Work Placement Teams are based in your Faculty Registry Office and can help you find a suitable placement, as well as support you in making applications, writing CVs and improving your interview technique.

More details on work placements can be found on our Work placements page.



Read less
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more

This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Course structure

The following modules are indicative of what you will study on this course.

Core modules

Option modules

Professional accreditation

This programme is accredited by BCS, The Chartered Institute for IT, for fully meeting the further learning educational requirement for Chartered IT Professional (CITP) status and for partially satisfying the underpinning knowledge requirements set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC) and the Science Council for Chartered or Incorporated Engineer (CEng or IEng) status. Note that there are additional requirements, including work experience, to achieve full CITP, CEng, or IEng status. Graduates of this accredited degree will also be eligible for professional membership of BCS (MBCS).

The BCS accreditation is an indicator of the programme’s quality to students and employers; it is also an important benchmark of the programme’s standard in providing high quality computing education, and commitment to developing future IT professionals that have the potential to achieve Chartered status. The programme is also likely to be recognised by other countries that are signatories to international accords.

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analysts, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (e.g. GlaxoSmithKline, British Airways, Santander and Unilever), public sector organisations (e.g. the NHS and primary care trusts), retail head offices, the BBC, the Civil Service, and the host of banks, brokers and regulators that make up the City, along with all the specialist support consultancies in IT and market research and forecasting, all of whom use data for the full range of decision making.

Work placements

Our Work Placement Teams are based in your Faculty Registry Office and can help you find a suitable placement, as well as support you in making applications, writing CVs and improving your interview technique.

More details on work placements can be found on our Work placements page.



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This course produces specialist Data Scientists who can design and implement computer-analytics and visualisation solutions for industry. Read more

This course produces specialist Data Scientists who can design and implement computer-analytics and visualisation solutions for industry. With an emphasis on Big Data, you will gain an understanding of the needs of businesses and how to manage requirements in this emerging international area of focus for companies, governments and economies.

The course focuses on Big Data, traditional and unconventional data management, including acquisition, storage, warehousing, analytics and visualisation tools and techniques. You’ll put these skills into practice in our state-of-the-art facilities.

Importantly, the course satisfies industry’s demand for Data Scientists who have the ability to relate key performance indicators, and contribute to business decision-making at a high level – giving you an advantage in the job market.

What you will study

Throughout the course, content is complemented by practical work, allowing you to support your theoretical knowledge with practical experience in data storage, mining, warehousing, visualisation and analysis as well as transferrable skills.

The individual project provides an opportunity for applying specialist knowledge together with analytic, problem-solving, managerial and communication skills to a particular area of interest within data science. Working with the full support and guidance of an allocated Project Supervisor, you will propose, plan, specify, develop, evaluate, and present a substantial project.

Teaching and assessment

You will be taught through a mixture of lectures, tutorials, labs. You will be invited to attend talks presented by highly-experienced researchers, speakers from industry, and members of the BCS (British Computer Society) on a wide range of industry-related topics. You will also be supported through our online virtual learning environment where you can access a wide variety of resources and other support materials.

Part-time September start students

  • A) Part-time September start students who would like to work on their project during the summer start their project in May of their second year and complete in December of their third year. (Approximately 28 months)
  • B) Part-time September start students who would like to avoid working on their project during the summer start their project in September of their third year and complete in May that year.  (Approximately 33 months)

Part-time January start students

  • C) Part-time January start students who would like to work on their project during the summer will start their project in January of their third year complete their project in August that year. (Approximately 32 months)
  • D) Part-time January start students who would like to avoid working on their project during the summer will start their project in January of their third year, have a break during the summer semester and continue their project September-December that year. (Approximately 36 months)

ACTIVITY SUMMARY

  • Lectures - 30 students per group, 24 hours over two months
  • Tutorial - 30 students per group, 24 hours over two months

INDEPENDENT STUDY

A significant portion of this courses is underpinned by independent learning, and you will be expected to be responsible for managing your coursework, reading and other learning activities appropriately.

STAFF DELIVERING ON THIS COURSE

Our staff members feature in the annual Support and Teaching staff with Appreciation and Recognition (STAR) awards voted by the students and organised by RGU:Union. Recently we have been awarded two Lecturer of the Year awards and an award for Continued Excellence.

Many of our academic staff are Fellows or Senior Fellows of the Higher Education Academy or are working towards this accolade. This is a professional recognition of practice, impact and leadership of teaching and learning.

Staff on this course could also include: visiting lecturers, visiting Distinguished Researchers, library staff and industry experts and postgraduate researchers.

ASSESSMENT

Typically students are assessed each year:

Year 1

  • 4 written exams, typically for 3-4 hours
  • 2 reports
  • 1 dissertation (final year project)
  • 1 oral assessment
  • 8 practical skills assessment
  • 1 group critique

Placements

Students who perform particularly well during their first semester of studies will be invited to apply for any long-term placement opportunities (40-45 weeks) found by the Placement Office. Alternatively, you can seek your own long placement or a short placement. Note that permission to undertake a placement is at the discretion of the School and students who optionally go on placement also need to pay a £1000 fee.

Job prospects 

The opportunity to exploit Big Data is recognised world-wide, and it is included in government economic strategies. The UK Government and Scottish Governments highlight it as an emerging opportunity for growth. The course prepares you for a career in Data Science or in Big Data. Job openings include: Data Scientist, Data Analyst, Data Visualisation Specialist, Data Manager, Database Designer/Manager, Data Mining Expert and Big Data Scientist. The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school.

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups, so graduates can seek employment locally. RGU is also involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies, and you may benefit from the university’s links with some of these companies when it comes to securing placements or employment.

Please visit the website to find out how to apply.



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Business Intelligence is basically about concepts and methods to improve business decision making by using fact-based support systems. Read more

Business Intelligence is basically about concepts and methods to improve business decision making by using fact-based support systems. Business Intelligence as a discipline is made up of several related activities, including data mining, analytical processing and business process improvement.

Expectations for MSc Economics and Business Adminstration - Business Intelligence

The programme provides you with in-depth knowledge of methods for analysing data to support decision-making and for improving business processes on the basis of business analytics. Furthermore, the programme provides you with an in-depth knowledge about:

  • Methods for analysing data to support decision making
  • How to improve business processes on the basis of business analytics

Get more details about the programme here >>

The courses of the programme will provide you with analytical skills to identify new business opportunities or identify inefficient business processes. The teaching form of the program encourages student participation and this in combination with the final thesis work will provide you with self-management and communication skills.

PROGRAMME STRUCTURE AND COURSES

1st semester: Prerequisite courses

During your first semester you follow the prerequisite courses that form the methodological and academic basis for the further study programme.

The course Business Analytics gives the student a set of tools and models that are essential for the design and evaluation of empirical investigations that can support decisions in the business intelligence area. Moreover, the course will cover major research tools including research design, experiments,response models and forecasting.

IS Development & Implementation in a Business Context introduces a range of methods and techniques that can be used to understand, plan and execute the processes in which information systems are developed, implemented, evaluated and modified to enable the student to participate in the development, acquisition and implementation of information systems.

Data Warehousing provides the student with knowledge about the wide variety of database management systems available for a data warehouse solution and how to choose a solution that is relevant for the business intelligence project in question.

SAS and SQL for Business Analytics provides the student with skills to conduct proper data analysis using some of the most flexible environments available. Focus will be on data management and data manipulation with the purpose to prepare for a statistical analysis.

2nd semester: Specialisation courses

During the second semester you follow the specialisation courses of the programme.

Data Mining for Business Decisions teaches students how to work with large data-sets and how relationships in such data can be detected with the purpose to transform data into knowledge. Business applications cover a broad range from marketing to accounting, logistics and supply chain management.

In Advanced Market Research the focus is on analytical customer relationship management. The course is devoted to customer base analysis and predictive modelling with a primary focus on customer lifetime value and customer retention.

Supply Chain Management aims to provide an introduction and a framework of the design and operations of performance management in contemporary supply chains.

Project Management aims to introduce the contents of general project management competences and provide the students with skills to manage a BI project.

3rd semester: Electives at Aarhus BSS or abroad

In the third semester you can choose elective courses within your areas of interest. The courses can either be taken at the school during the semester, at the Summer University or at one of our more than 300 partner universities abroad. You can also participate in internship programmes either in Denmark or abroad.

4th semester: Final thesis

The fourth semester is devoted to the final thesis. You may choose the topic of the thesis freely and get a chance to concentrate on and specialise in a specific field of interest. The thesis may be written in collaboration with another student or it may be the result of your individual effort. When the thesis has been submitted, it is defended before the academic advisor as well as an external examiner.

Student testimonials from Aarhus BSS - Aarhus University >>



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This is a conversion course aimed at graduates with a first degree in a non-computing discipline who want to gain employment in the lucrative IT industry. Read more

This is a conversion course aimed at graduates with a first degree in a non-computing discipline who want to gain employment in the lucrative IT industry.

You begin by studying key computing topics including

  • introduction to databases and big data
  • computer programming and web development
  • introduction to technology and computer hardware
  • IT project management and modern development methods

These modules provide the background knowledge you need to develop more advanced skills later in the course. They allow you to become familiar with the major technologies and concepts that underpin the modern computing industry.

Your learning at this stage has a practical focus and you are encouraged to take part in technical development work.

You go on to study a specialist topic in more depth with the choice of • databases • big data • web and cloud technologies. These areas are very current within the computing industry and in high demand of qualified IT personnel.

You then take an industrial expertise module where you have the opportunity to engage in live projects for real clients. This gives you experience working in a team to identify client needs, plan projects and produce working solutions.

You may be able to study abroad as part of the Erasmus programme.

During the final part of the course you complete an individual project which is the equivalent of a dissertation. To prepare you for this project, you first take a module on research skills and principles. You gain an understanding of research methods and learn how to manage a project of this kind.

As well as submitting project materials, you also deliver an assessed presentation describing your work to an audience.

Course structure

Core modules

  • databases and big data
  • web and multimedia programming
  • technology and networking
  • project management methods
  • industrial expertise
  • research skills and principles
  • product development project

Optional modules

You choose one from

Databases

This covers • logical database design • data warehousing • big data and distributed systems.

Web and cloud technologies

This covers • cloud technologies • cloud applications • mobile applications.

Big data

This covers • big data and distributed systems • data quality • business intelligence in action.

Assessment

  • individual assignments
  • group work
  • practical projects
  • reports
  • presentations

Employability

This course prepares you for a career in the software industry. You graduate with the skills and knowledge to work in areas such as • database development • web application development • big data • software consultancy. The course offers flexibility by being able to adopt the latest technologies and standards to reflect what is being used in industry.

Our computing graduates have found employment in companies such as Sky, PlusNet and Sumo Digital in roles ranging from software tester to senior architect.



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This course provides an opportunity for candidates wishing to formalise their existing IT experience with a qualification, and for graduates of non-computing disciplines to develop the specialist skills suitable to transition into an exciting career in computing with a specialism in business intelligence. Read more

This course provides an opportunity for candidates wishing to formalise their existing IT experience with a qualification, and for graduates of non-computing disciplines to develop the specialist skills suitable to transition into an exciting career in computing with a specialism in business intelligence.

The course will provide you with the core computing and business intelligence knowledge and skills required to work within a technical IT environment. Throughout the course, content is complemented by practical work, undertaken in state-of-the-art facilities, using tools and techniques to allow you to match software solutions to the needs of businesses. This practical element will enhance your theoretical understanding by developing real-world problem-solving skills; enhancing your employability as a graduate.

What you will study

You will develop skills in business intelligence, data science, software development, database systems, and web programming, as well as the research and development skills required to undertake a sustained piece of data science or software development project work. You will learn to use modern software tools and business intelligence environments, allowing you to match these to the needs of commerce and industry using appropriate development methodology to provide high-quality solutions.

STAGE 1

  • Object Oriented Programming
  • Data Management
  • Data Warehousing
  • IT Infrastructure and service management

STAGE 2

  • Data Visualisation and Analysis
  • Data Science Development
  • Intranet Systems Development
  • Software Project Engineering

STAGE 3

  • MSc Project Investigation
  • MSc Project

Teaching and assessment

You will be taught through a mixture of lectures, tutorials, labs and external speakers, supported through our online virtual learning environment affording access to a wide variety of resources and support materials.

Part-time September start students

  • A) Part-time September start students who would like to work on their project during the summer start their project in May of their second year and complete in December of their third year. (Approximately 28 months)
  • B) Part-time September start students who would like to avoid working on their project during the summer start their project in September of their third year and complete in May that year.  (Approximately 33 months)

Part-time January start students

  • C) Part-time January start students who would like to work on their project during the summer will start their project in January of their third year complete their project in August that year. (Approximately 32 months)
  • D) Part-time January start students who would like to avoid working on their project during the summer will start their project in January of their third year, have a break during the summer semester and continue their project September-December that year. (Approximately 36 months)

ACTIVITY SUMMARY

Lectures

  • 25 students per group for 7 hours per week (Semester 1)
  • 25 students per group for 6 hours per week (Semester 2)

Project Supervision

  • 1 student for 1 hour per week (Semester 3)

Practical class or workshop

  • 25 students per group for 10 hours per week (Semester 1)
  • 25 students per group for 9 hour per week (Semester 2)

Independent Study

  • 23 hours per week (Semester 1)
  • 25 hours per week (Semester 1)
  • 39 hours per week (Semester 3) 

INDEPENDENT STUDY

A significant portion of this courses is underpinned by independent learning, and you will be expected to be responsible for managing your coursework, reading and other learning activities appropriately.

STAFF DELIVERING ON THIS COURSE

Our staff members feature in the annual Support and Teaching staff with Appreciation and Recognition (STAR) awards voted by the students and organised by RGU:Union. Recently we have been awarded two Lecturer of the Year awards and an award for Continued Excellence.

Many of our academic staff are Fellows or Senior Fellows of the Higher Education Academy or are working towards this accolade. This is a professional recognition of practice, impact and leadership of teaching and learning.

Staff on this course could also include: visiting lecturers, visiting Distinguished Researchers, library staff and industry experts and postgraduate researchers.

ASSESSMENT

Typically students are assessed:

  • 5 written exams, typically for 3 hours per exam
  • 1 written assignments, including essays
  • 2 report
  • 2 dissertation
  • 2 project outputs
  • 2 oral assessment
  • 7 practical skills assessment
  • 1 group critique

Placements

Students have the option to seek a short placement. However, permission to undertake a placement is at the discretion of the School and is not guaranteed.

Job prospects 

As a graduate of this course you could go on to work in a wide variety of IT careers, for example, a Network Manager, Network Administrator, Software Engineers, Applications Developer, Business Analyst, Database Developer and Web Developer. You could also go on to pursue a career in research or academia. 

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups.

The university is involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies.

The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school.

Please visit the website to find out how to apply.



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The programme offers an opportunity for professionals in health care and related disciplines to develop the knowledge, understanding and competencies necessary to function more effectively in addition to mastering the advanced use of information technology skills in health care settings. Read more

The programme offers an opportunity for professionals in health care and related disciplines to develop the knowledge, understanding and competencies necessary to function more effectively in addition to mastering the advanced use of information technology skills in health care settings.

Programme Aims

The programme is the first of its kind in Hong Kong. It aims to equip health care professionals and students from health-related disciplines, information technology, engineering or related backgrounds with advanced information technology skills for health care settings. The course contents will address the needs of health care providers and allow for the introduction, re-orientation and/or conversion to a field that is of direct relevance to the student's place of employment.

Mode and Duration of Study

This is a credit-based mixed mode programme with a normal duration of study of 1 year for full-time study and 3 years for part-time study. The maximum duration of study is 6 years.

Programme Structure

Students need to complete 30 credits comprising 4 compulsory, 2 core and 1 elective subjects plus a dissertation (or students can choose another 3 core/elective subjects of the programme to replace the dissertation).

Taught Subjects

Compulsory subjects

  • Electronic Patient Records
  • Epistemology
  • Information Technology in Health Care
  • Professional Development in Health Informatics

Core subjects

  • Applied Biosignal Processing
  • Business Intelligence and Data Mining
  • Computer Programming for Healthcare
  • Data Mining and Data Warehousing Applications
  • Digital Imaging and PACS
  • Epidemiology
  • Intelligent Information Systems
  • Knowledge Management for Clinical Applications
  • Project Management

Elective subjects

  • Bioinformatics in Health Sciences
  • Database Systems and Management
  • Information Security: Technologies and Systems
  • Information System Development with Object-Oriented Methods
  • Internet Computing and Applications
  • Methods and Tools for Knowledge Management Systems
  • Research Methods and Data Analysis
  • Virtual Reality in Health Care

The list of elective subjects is not exhaustive. 

Dissertation

  • Dissertation


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In the MEngSc Information Technology in Architecture, Engineering, and Construction (Bauinformatik) you will learn how to apply computer science technologies to sustainable design, facilities management, energy management, and construction management. Read more
In the MEngSc Information Technology in Architecture, Engineering, and Construction (Bauinformatik) you will learn how to apply computer science technologies to sustainable design, facilities management, energy management, and construction management.

The course is designed for professionals as well as young graduates from all computer science and engineering disciplines who want to improve their knowledge of customising information and communication technologies to support the design, commissioning and operation of civil engineering systems.

The course addresses the increasing need for engineers and architects with advanced knowledge and skills in the application of information and communication technologies to support sustainable design and operation of buildings and energy systems, facilities management, virtual construction, building information modelling (BIM) and structural engineering.

Lecturers are broadcast through the web, and can be attended either in UCC or from a remote location. Experts from six European universities contribute their knowledge to the course.

Visit the website: http://www.ucc.ie/en/ckr29/

Course Details

You will get hands-on experience in planning, customising, and maintaining state-of-the-art software systems for the needs of the AEC and FM sectors with an emphasis on complex engineering systems such as smart buildings. The course consists of four pillars:

- the acquisition of new knowledge and practical skills in selected engineering disciplines
- the acquisition of knowledge and skills in selected areas of computer science
- the application of the newly-acquired knowledge in two projects
- the development and submission of a minor research thesis.

In the first teaching period students acquire knowledge of:

- Smart Buildings, Facilities and Energy Management
- Software Engineering
- Knowledge Management or Computer Mediated Communication.
- Building Information Modelling (BIM), Data Warehousing, and E-business
- Virtual Construction, Automation in Construction or Finite Element Analysis (electives)

The two projects focus on:

- Software Engineering
- Information Technology for Energy Systems in Buildings.

The course is based on the principle of research-led teaching, ie. project work will be based on practical examples. Researchers and PhD students from UCC will be involved in mentoring and supervising assignments and projects. On completion of the course, you will be extremely attractive to employers who need engineering with a strong IT-background, working in the following areas:

- civil and energy-engineering consultancy
- facilities management
- energy service provision (ESCO)
- construction management
- building operations
- software engineering
- project management.

You will develop skills in:

- applying information modelling
- software engineering
- data processing
- data analysis techniques
- facilities and energy management
- structural analysis
- project and supply chain management in construction.

Format

The course can be taken on a full-time (one year) or part-time (two year) basis with an option to complete at postgraduate diploma level. Lectures are broadcast using web-technology and can be attended either in UCC, in your home, or at your workplace. The majority of lectures are scheduled outside normal working hours. Block seminars consisting of full-day events are available once a month during academic periods. The course requires the completion of two projects, but can be combined with a work placement. A minor thesis contribution begins when all taught modules are completed successfully and involves four months of research work.

Assessment

Modules focusing on the acquisition of new knowledge are assessed by written exams (60%), in combination with continuous assessment (assignments – 40%). Modules focusing on skills-development or knowledge transfer are assessed through the submission of reports or essays in combination with presentations. Projects are usually organised in groups. They are assessed through continuous assessment (team meetings, status review meetings) and a final report complemented by a final presentation. You must pass each module (40%) and achieve an average grade of 50% across all taught modules in order to be eligible to progress with the master’s thesis.

Careers

Recent publications report that a shortage of engineers has been identified by professional bodies across the European Union. In the UK and Germany alone, it is predicted that approximately 2,500 engineering positions need to be filled on an annual basis over the next five years (2012 to 2016). It is expected that employable candidates have an excellent background in how to efficiently exploit IT tools in order to execute engineering tasks in the most efficient but also in an interdisciplinary way. This course addresses the need for interdisciplinary expertise and skills in engineering, energy management and computer science.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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The Information management pathway addresses both the technical challenges of information capture and usage from big data, and the need for its effective and efficient management and analysis within business, scientific, educational, entertainment and organisational contexts. Read more

The Information management pathway addresses both the technical challenges of information capture and usage from big data, and the need for its effective and efficient management and analysis within business, scientific, educational, entertainment and organisational contexts. This MSc pathway will examine the entire information management life cycle, including data strategy, management, design and warehousing, data analytics and information governance. In addition to the need to work with huge volumes of data, the pathway will also address multi-modality, including un- and semi-structured data, image and video data, spatial and temporal data, etc.

The pathway consists of two (compulsory) units from the Data Engineering and IT governance ACS theme, three additional compulsory units on various aspects of information management, and one optional unit covering various application areas (such as decision support, text mining, optimisation).

The pathway is taught in collaboration with Manchester Business School (MBS). As such, the programme benefits from the offerings of both schools. MBS is the largest campus-based business and management school in the UK offering world-leading business education informed by leading edge theory and practice. Similarly, the School of Computer Science is renowned as a world-class centre of excellence in computing teaching and research.

Special features

IBM has announced that Prof. John Keane from the School of Computer Science at The University of Manchester is one of the winners of its2013 Big Data and Analytics Faculty Awards. He joins 13 other researchers from around the world who will bring together their innovative research for the benefit of curricular development. The award will support technical case studies investigating the design and implementation of big data problems to enhance the postgraduate module in Data Engineering which is central to the Information Management pathway of the Advanced Computer Science and IT management MSc at Manchester.

Course unit details

The (full time version of the) course lasts 12 months, and starts in September. The students take the following core course units:

-   Data Engineering (COMP60711)

-   Machine learning and Data Mining (COMP61011)

-   Information and knowledge management (BMAN71652)

-   IT Governance (COMP60721)

-   IS Strategy and Enterprise Systems (BMAN60111)

and one course unit from the following three:

-   Decision Behaviour, Analysis and Support (BMAN61102)

-   Text mining (COMP61332)

-   Optimization for learning, planning and problem-solving (COMP61143).

In addition, students follow Research Methods and Professional Skills (COMP60990), which includes academic and professional literacy, ethics, testing, usability, careers, etc. and work on their MSc project. The project is assessed in two parts, through the Project Progress Report (which counts for 85% of the 30 credits for COMP60990) and the Dissertation (60 credits). To continue towards the project for MSc award, students need to pass the taught component (90 credits). 

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

IBM is supportive of the Information Management pathway. The programme fits with some of IBM's core business objectives and also that of some of our clients. (Martyn Spink, University of Manchester Relationship Manager, IBM UK Limited).

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.



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