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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

    4 weeks
  • Weekly study

    2 hours

Many datasets can provide solutions to important problems and inform decisions. However, the size, complexity, quality and diversity of these datasets make them difficult to process and analyse. Join us and we’ll share new technological or methodological solutions you can use to meet the demand for analytics in your field.

We will introduce big data and some of the statistical and mathematical approaches for analysing it. Then we explore the power of big data and the process of getting from data to decisions before you use some of the tools available for storing and managing large datasets.

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
  • Develop an awareness of how to participate 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.

What software or tools do you need?

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 to install Cloudera, an open source platform for data management and analytics. We will email you detailed instructions explaining how to access a trial version and set up a virtual machine before the course starts.

Who will you learn with?

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.

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.

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

  • 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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