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The program is designed to provide research led experiential learning in the field of business analytics. It meets the demand of growing employment opportunities created by digital innovation, digital transformation and the emergence of big data and its associated dynamics and analytical challenges. By working on real world companies’ problems, students will apply business analytics knowledge and skills and recommend resolutions to problems. This way, students will develop a ‘Personal Portfolio’ that can be presented to potential employers to showcase their skills and achievements. Read More
The programme plays a crucial role in preparing students for a successful career in the field of data analytics
In this module you will learn about how to use statistical tools and analytical software in Business Analysis. You will learn the necessary skills to make sure that processes run efficiently, particularly with the application of these statistical analytical tools in real business cases by taking into consideration all the face of opportunities and challenges arising from the worldwide reach of business.
You will gain the basic and the essential knowledge in addition to practical analytical skills to think as a professional business analyst, project manager, operations analyst, digital analytics specialist or data analytics consultant in a globalised digital environment. Moreover, you will discover the basic analytical statistical thinking of data analysis in business and put your learning into practice by applying it to real case studies which will help you to gain experience with the recent issues in business and digital market. Business Statistics and Data Analytics work hand-in-hand, because analytics turns data into insights that guide intelligent business decisions. You will learn how to discover and create knowledge from data analysis assem well as data preparation, data visualization, statistical analysis and other advanced analytics tools by using SPSS and applying one of the most famous analytics tools “SAS software” which is known as Analytics Leader. This course will help you in understanding business statistical analysis, develop your data analysis skills and will qualify you to work in organisations and help them to achieve their digital transformation goals.
In this module, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. This module is designed to teach you to handle data programmatically, without being software engineers. By the end of the module, you will be able to use one of the powerful data analysis tools – R – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the module, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
In this module you will learn about a comprehensive range of research methods and business analytics techniques. This will equip you with the knowledge and practical skills necessary for you to conduct research at Masters’ level and prepare you to complete a Master’s Dissertation, Consultancy Project or Management Enquiry. By the end of the module you will know how to apply both quantitative and qualitative data collection and business analysis techniques. In quantitative techniques you will learn about sampling, questionnaire design, statistical inference, and hypothesis testing while qualitative techniques covered will include methods such as interviewing and focus groups. Analysis methods such as content analysis and thematic analysis will also be covered. In addition, you will gain some understanding of research philosophy (positivism and interpretivism) and research ethics and you will be able to write a research proposal to bring these ideas together.
Furthermore, this module will provide clear, critical, and analysis of data, you will also be able to consider the use of analytics implementation skills, where you will be introduced to analytics software such as SPSS. SPSS statistics analysis is one of the powerful solutions that is designed to help businesses and researchers to solve problems by various methods (geospatial analysis, predictive analytics and hypothesis testing).
This module aims at educating you in the field of forecasting and predictive analytics to respond to the job market needs using a variety of methodologies. Your journey shall be a quest to distinguish the "True" signal from a universe of "Noise" through the lenses of forecasting and predictive analytics. To be more specific, this module covers the typical methodological steps of a prediction exercise, statistical modelling, and artificial intelligence methodologies for prediction via applications in different business settings. This modules teaches you fundamental techniques used for predictive analytics: regression, classification, clustering, Bayesian and other machine learning approaches and models. You will learn how to perform forecasting using time-based data to predict future values from a model. You will get practice with classification and use various techniques for clustering and linear regression to solve common business problems; as well as learn techniques for assessing the effectiveness of your solutions.
This module prepares you to develop competitive business strategies by developing key “Hard” skills that are essential in a competitive landscape. In this module you will learn how to use marketing and supply chain analytics to progress your skills on enhancing the functional performance of a modern business. This includes specialised approaches, methods, and techniques that complement your learning with R analytics, SPSS, and SAS in the previous modules. You will be introduced to competitiveness techniques that help you automate, inform, and strategize business processes and enhance the overall value chain. You will practice business analytics in key business areas such as logistics, operations, marketing, and decision support systems. This learning-by-doing (action learning) philosophy will enable you to use “Passive” and “Active” business analytics to enhance your skills for competitiveness and strategizing. Examples of passive analytics software included in this module are KISSmetrics, RetentionGrid, Metrilo, Clicky, and Adobe Marketing Cloud. Each of them will be demonstrated using a practical case study in four functional areas, including procurement/ inbound logistics, operations, marketing, and after sale services.
To strengthen this application of analytics to organisational competitiveness and the pursuit of competitive advantage, you will also participate in a business simulation where you will be exposed to cross-functional business decision making in the pursuit of a competitive business strategy.
A prominent theme throughout this module is to give you experience in contemporary analytics software applications used in the key business functions, and by doing so, this will enhance your employability for graduate-entry analytics roles. In addition to being able to provide critical analysis of data, you will also be able to consider the business implementation and communication skills required. This module emphasises the development of practical skills and techniques required by businesses to help them in strategizing their operations. You will also develop “Soft Skills” relating to communication and conflict resolution as well as enhancing your knowledge of commercialisation and market positioning strategies.
This module engages you in personal and professional development in order that you develop and hone your teamworking, management and leadership skills, capabilities and attributes, and in so doing, enhance your employability. On this module, you will not only prepare for your first job after you graduate but also kickstart your commitment to life-long personal and professional learning. In the first part of the module you will be supported in a self-analysis by a range of activities, including the completion of self-administered tool-kits to demonstrate an increased self-awareness and self-understanding. This will also involve applying theoretical frameworks and researching contemporary literature for a more in-depth understanding of self.
A key outcome of this process is how you will be able to exploit this development in order to lead, and manage, more effectively in your future careers. The second part of the module contains activities which enable you to build on your self-analysis and explore further your strengths, weaknesses and areas for development in the context of your career development plans. You will receive guidance on how to craft professional, postgraduate CVs, LinkeIn profiles, and supporting documentation to meet the needs of employer. Furthermore, you will use your understanding of self to help you to understand the key issues and specific challenges that you face, with your skills profile, in relation to your employability prospects in your target profession/industry/sector. This will also include the development of knowledge into the global graduate market, (including routes such as self-employment and developing your career with an existing employer) drawing upon local, national and international examples.
In this module you will gain an understanding of the academic skills that are required to produce a Masters Dissertation. By the end of the module you will have written a 15000 word Masters dissertation. The areas included are:
A Bachelor’s degree with a minimum 2:2 classification (2.70/4.0 GPA)
If applicant is a graduate from a non-English speaking institution, English proficiency test is required. International English Language Testing System (IELTS) Score: a minimum overall IELTS score of 6.5 with 5.5 in each component.
NOTE: IELTS scores must be less than 2 years old at the time of application.
Application Form - Online
QID and Passport
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Bachelor’s degree transcript
IELTS
(if applicable)
Tuition fee:
Application fee:
Fees can be paid by card at the University premises, online from your applicant login, or via bank transfer. Application fees (QR 300) are non-refundable.
Application open in February
Application deadline in September
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