Introduction to Data Analytics in Hospitality and Tourism

On this Introduction to Data Analytics in Hospitality and Tourism short course you will learn how to use different analytical techniques and tools to analyse databases from the hospitality and tourism sector.

You will gain practical analytical skills for decision making which you will be able to use directly in any organisation. You can expect to be involved in practical analytical discussion with professional guest experts in business analytics, data analytics, digital analytics and data science.

NB There are no upcoming dates for this short course, but new dates may be added in due course. We can also run our short courses 'on demand' for organisations who would like to use them as part of staff development. Contact us for more details about costs and how to arrange a bespoke delivery of this course.

Why QMU?

We offer practical analytical skills to use in the hospitality and tourism sector
Our staff have analytical experience in various businesses
We have connections with different businesses and there will be many opportunities to meet data experts and international guest speakers in business analytics, data analytics and data science

Who is this course for?

This course is suitable for people working with the hospitality and tourism sector who are interested in using data analytics to support making better business decisions. The course is intended for beginners in business analytics and those who would like to improve and develop their analytical skills.

Introduction to Data Analytics in Hospitality and Tourism: The course in brief

What will I learn on the course?

On this course you will learn about best practices for using the analytical tool R for analyses that would be useful in the hospitality and tourism sector. You will discover how to understand different data, create tables, and find information from big databases, as well as how to use basic statistics and multivariate analytical techniques.

Specifically, you will learn how to:

create and manipulate R data structures
import data from external sources
clean and transform data
create sophisticated functions
use statistical functions and present findings using R graphics

By the end of the course what will I be able to do?

On completion of the course, you’ll be able to:

Use aggregative functions, indexing and other more sophisticated functions.
Use basic plotting techniques with R to further analyse organizational data and to present your analytic findings to management.
Understand how to apply descriptive, distribution, regression and correlation (including multiple regression), t-tests, ANOVA and categorical data analysis (including chi-squared).
Understand the basics of procedural programming – variables, control structures and writing simple functions.
Clean, transform and sample data.

How will I be taught?

How is the course delivered?

The course will be run online.

Teaching will be in the form of seminars interspersed with practical exercises to test and expand analytical knowledge. You will be involved in practical exercises to ensure an understanding of analytical approaches.

How long does the course last for and how much time will I need to spend on it each week?

You will attend the course every week for five weeks. The course will be delivered online and will include set readings, the development of practical skills, live and pre-recorded sessions with the course tutor, guided learning exercises, and preparation for your assignments.

Does the course have an assessment and if so, what sort of assessment will it be?

To complete this course you will be required to produce a 3500-word report based on big data that uses analytical techniques with R to answer a business question.

Who will be teaching me?

The course will be delivered by senior lecturer from the Queen Margaret Business School who has international business and academic experience in business analytics, business statistics, and marketing.

What equipment will I need for this course?

You will require access to a computer or laptop, Internet connectivity, a webcam and Microsoft Excel. You will need to be able to download the free analytical software R.

Student support/access to facilities

For the duration of your course you will be able to make use of our on-campus learning resource centre as well as access to our full range of online resources, including e-books and academic journals.

You will also have limited, mainly online access to Student Services support. Students with particular support requirements can contact the Disability Service.

As you will be studying with us for less than a full academic year you will not be provided with a personal academic tutor (PAT). However, any queries regarding your studies should be directed to the staff member leading the delivery of your course.

Introduction to Data Analytics in Hospitality and Tourism: Entry requirements, fees and application information

Entry requirements

The course is delivered at SCQF Level 9, which is equivalent to the third year of a four-year undergraduate degree in Scotland. Each applicant must decide if the level of study is suitable for them.

Applicants for SCQF Level 9 study would usually have completed further or higher education up to or above the level of an HND. Alternatively, they would have relevant professional experience that supports study at this level. Applicants that have previously studied outside the UK should check that their qualification has been taught at a suitable level to prepare them for studying a course at this level.

You do not need to provide proof of your previous qualifications.

English Language requirements: This course is taught and assessed in English. Applicants do not need to provide proof of their English Language skills when applying for this course, but all applicants should consider whether they have sufficient English competence to study at this level. Applicants for this level of study would usually be able to demonstrate a level of English equivalent to IELTS 6.5 overall, with no component score below 6.0.

Fees

Fees: £865