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Big Data: from Data to Decisions

Get a practical insight into big data analytics, and popular tools and frameworks for collecting, storing and managing data.

38,900 enrolled on this course

  • Duration

    2 weeks

  • Weekly study

    2 hours
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Data Analytics · Decision-making
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Data is everywhere and can be obtained from many different sources. Digital data can be obtained from social media, images, audio recordings and sensors, and electronic data is quite often available as real-time data streams.

Many of these datasets have the potential to provide solutions to important problems, and advice in making decisions in health, science, sociology, engineering, business, information technology, and government.

However, the size, complexity, quality and diversity of these datasets often make them difficult to process and analyse using standard statistical methods, software or equipment.

Take a unique, multi-faceted approach to big data

For this reason, we use new technological or methodological solutions. Join us for this free online course and we’ll share these with you using our unique, multi-faceted approach to big data. We’ll show you how you can meet the demand for analytics in your field.

After a brief introduction to big data and an overview of some of the statistical and mathematical approaches for analysing it, we’ll explore real-world case studies. These will demonstrate the power of big data and, most importantly, the process of getting from data to decisions.

Then we’ll give you an overview of some of the tools you can use for storing and managing large datasets.

Continue learning with the Big Data Analytics program

This course is one of four in the Big Data Analytics program on FutureLearn from the ARC Centre of Excellence for Mathematical and Statistical Frontiers at Queensland University of Technology (QUT).

The program enables you to understand how big data is collected and managed, before exploring statistical inference, machine learning, mathematical modelling and data visualisation.

When you complete all four courses and buy a Certificate of Achievement for each, you will earn a FutureLearn Award as proof of completing the program of study.

Skip to 0 minutes and 6 seconds Hi everyone and welcome to our Big Data Analytics collection of courses. My name is Kerrie Mengersen. In every minute of 2014 there were more than 204 million email messages sent, more than 2 million queries searched on Google, and more than 48 hours of new YouTube videos uploaded to the web. This is only per minute – can you imagine how much these values will increase per month, or per year? This is a significant increase in information, and over the years it’s only going to increase even more. From looking at these numbers it’s obvious we need fast and effective solutions for managing, storing and analysing all this data. This is where our Big Data Analytics collection of courses comes in.

Skip to 1 minute and 5 seconds In this first course we provide an introduction to the world of Big Data and look at how Big Data is applied to solve problems in different fields including health, environment and industry. We’ll also showcase different tools for Big Data management. The entire list of tools available for Big Data management is extensive; here we select a few of the most well-known and important tools and show you how to best apply them. We are excited and we hope you are too.

What topics will you cover?

  • Introduction to big data, its applications and the job roles involved
  • Types of data and its sources
  • The big data lifecycle
  • The role of analysis and how big data is used to inform decision making
  • Common issues in big data analytics
  • Methods for collecting, storing, managing and processing big data
  • The big data ecosystem, its common tools, frameworks and platforms including Hadoop Distributed File System (HDFS), MapReduce, Apache Pig and Apache Spark

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Identify big data application areas
  • Explore big data frameworks
  • Demonstrate an integrated approach to big data
  • Explore effectively in a team working with big data experts

Who is the course for?

Our course is open to anyone with an interest in big data and is essential if you’re looking to add big data analytics to your skill set. A basic knowledge of software engineering, statistics and mathematics will help you gain the most from this learning experience.

Practical exercises

The course includes optional, practical exercises designed to help you become familiar with some of the current tools used in big data analytics. If you would like to try the exercises you will need the appropriate software.

Follow our step by step instructions to install Cloudera and download our exercise files to your Cloudera QuickStart VM desktop.

Who will you learn with?

Tomasz Bednarz

I'm A/Professor (QUT & UNSW) and Team Leader (CSIRO/Data61), active in big data visualisation and analytics, computational and simulation sciences, computer graphics and interactive techniques.

Kerrie Mengersen

I’m a Professor at QUT and a Deputy Director of ACEMS. My interests are in statistical modelling and analysis, computational and simulation sciences and big data analytics.

Phil Gough

I am a designer, digital artist, and PhD candidate. My research and creative practice bridges art, science, creative code, big data, emerging technologies, and the everyday user.

Samuel Rathmanner

Hi, I am a Computer Scientist from the Australian National University with a particular interest in machine learning and artificial intelligence.

Matthew Sutton

I am a PhD student with research interests in genomics, operations research, big data and machine learning.

Anthony (Ace) Ebert

I'm a statistics PhD student at QUT. I'm interested in Bayesian analysis and Queueing theory. I script in R.

Who developed the course?

Queensland University of Technology

QUT is a leading Australian university ranked in the top 1% of universities worldwide by the 2019 Times Higher Education World University Rankings. Located in Brisbane, it attracts over 50,000 students.

  • Established

    1989

  • Location

    Brisbane, Australia

  • World ranking

    Top 180Source: Times Higher Education World University Rankings 2019

Endorsers and supporters

content provided by

ARC Centre of Excellence for Mathematical and Statistical Frontiers

Learning on FutureLearn

Your learning, your rules

  • Courses are split into weeks, activities, and steps to help you keep track of your learning
  • Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
  • Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

  • Experience the power of social learning, and get inspired by an international network of learners
  • Share ideas with your peers and course educators on every step of the course
  • Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

  • As you work through the course, use notifications and the Progress page to guide your learning
  • Whenever you’re ready, mark each step as complete, you’re in control
  • Complete 90% of course steps and all of the assessments to earn your certificate

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