Big Data Analytics

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.

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.

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.

Many people have big data but only some people know what to do with it. Why? Well, the big problem is that the data is big—the size, complexity and diversity of datasets increases every day. This means we need new solutions for analysing data.

This course equips you for working with these solutions by introducing you to selected statistical and machine learning techniques used for analysing large datasets and extracting information. We also expose you to three software packages so you can develop your coding skills by completing practical exercises.

You will enjoy this course most and benefit from the learning experience if you have a basic understanding of statistics and mathematics at a university undergraduate level.

You will be using the following free tools. Please review the product websites below to ensure your system meets the minimum requirements:

R and R Studio Desktop (open source edition)

You will complete practical exercises using R Studio, so you’ll need to be familiar enough with R to:

• install a package
• import data
• read and run starter code
• develop a solution or read through a solution and gain understanding from it.

NOTE: You must first have a working installation of R to use R Studio.

H2O Flow
H2O Flow can be used as a stand-alone package for big data analytics or can be used in conjunction with R. This package will allow you to tackle larger problems that you might encounter in your own work.

WEKA
WEKA is a popular workbench for machine learning and statistical analysis. It comprises a very wide range of tools that are suitable for big data analysis.

Knowing R, H2O Flow and WEKA will give you a powerful, flexible and scalable set of tools to manipulate and analyse big data.

Learn how mathematics underpins big data analysis and develop your skills.

Mathematics is everywhere, and with the rise of big data it becomes a useful tool when extracting information and analysing large datasets. We begin by explaining how maths underpins many of the tools that are used to manage and analyse big data. We show how very different applied problems can have common mathematical aims, and therefore can be addressed using similar mathematical tools. We then introduce three such tools, based on a linear algebra framework: eigenvalues and eigenvectors for ranking; graph Laplacian for clustering; and singular value decomposition for data compression.

This course is designed for anyone looking to add mathematical methods for data analytics to their skill set. We provide a multi-layered approach, so you can learn about the methods even if you don’t have a strong maths background, but we provide further information for those with a sound knowledge of undergraduate mathematics. We will assume basic MATLAB (or other) programming skills for some of the practical exercises.

MathWorks will provide you with free access to MATLAB Online for the duration of the course so you can complete the programming exercises. Please visit MATLAB Online to ensure your system meets the minimum requirements.