Skip main navigation

Welcome to the Course

.

Welcome to the Successful Data Analysis for Modern Industries course. Data analysis is never really done in a vacuum — not professionally, anyway. Analysing data takes place in the context of industry pressures, considerations of environment, considerations of data ecosystems, and what’s happening in the real world.

This course is designed to help you understand the larger context that any organisation or industry must contend with while doing the work of a data analyst. By the end of this course, you should be familiar with how data analysis is applied in different industries and where the future of data analysis and careers in data analysis is heading.

Course Content

Data Economics and Ecosystems – under this topic, we’ll unpack the economic and organisational factors behind data analysis in a variety of industries. We’ll see why data is a resource that needs to be cared for and analysed like any other resource.

Data Analysis for Business – in this activity, we’ll learn how business analysts use financial and marketing data to yield actionable insights, and how these insights, in turn, lead to tangible business improvements.

Data Analysis for Education – here, we’ll explore the ways in which educational institutions track and utilise data about student enrollment, graduation rates, course and instructor ratings, degree types, demographics, and financial aid.

Data Analysis for Healthcare – in this section, we’ll find out how analysts in the healthcare industry track patient experience, doctor quality, care quality, throughput in hospitals, inventory, costs, profit, and more.

Data Analysis for Social Good – to manage non-profit or government organisations with social impact, many types of data are required. This industry tracks large economic indicators, factors of happiness, food or donation programs, health indicators, and a wide variety of other factors.

Data Analysis Careers – finally, we’ll uncover what types of careers are available in the current data analytics world, as well as some of the jobs that might be available in the future.

Who Is This Course For?

This course is aimed at aspiring analysts in any industry, as well as managers who need to learn data analytics, data scientists, engineers, software developers, AI engineers, and more.

Course Schedule

This course is set up in a self-paced format. You can listen to the lectures and attempt the quizzes at your pace. You should aim to complete this course in 10 hours. It should take you around 5 hours a week for 2 weeks to complete.

Course Prerequisites

Learners require a basic excel proficiency, fundamental math and statistics background, and data visualisation fluency.

Course Subscription

Your CloudSwyft Online Hands-On Lab Session for this FutureLearn ExpertTrack course is free to use for 2 hours for your first 7 days with us on this learning journey!

Subscribe now (if you have not already) for this ExpertTrack and you will get an additional 12 Lab hour credits for this course for 1 month along with your certificate of completion. You will get 12 hours more for another month of subscription thereafter!

This article is from the free online

Successful Data Analysis for Modern Industries

Created by
FutureLearn - Learning For Life

Our purpose is to transform access to education.

We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.

We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.

Learn more about how FutureLearn is transforming access to education