• adelaide

Data Analytics for Managers

Maximise the data analytics capabilities of your team to solve business problems or achieve business efficiencies.

1,329 enrolled on this course

A person sitting at a desk using a computer
  • Duration

    6 weeks
  • Weekly study

    3 hours
  • Accreditation

    AvailableMore info
The CPD Certification Service

This course has been certified by the CPD Certification Service as conforming to continuing professional development principles. Find out more.

Develop your decision making and management skills informed by data analytics

Data analytics expertise empowers managers to transform their business frameworks and enables them to work effectively with data science teams.

In this six-week course from the University of Adelaide, you’ll develop your knowledge of how data analysts operate in business environments. You’ll learn how to explain data analysis processes, identify trends, and develop data-informed business solutions.

Explore the fundamentals of data science analysis

Many managers lack the confidence to interpret data, depriving them of useful insights and preventing them from developing a competitive edge.

In this course, you’ll be introduced to the basics of data analysis, equipping you with the skills to work alongside your data science team to derive meaning from data and capitalise on the data analytical skills of your workforce.

Deliver business transformation by understanding relationships in data

Using engaging case studies, you’ll learn to apply cutting-edge data processing techniques to solve common business problems and discover new patterns in data.

You’ll explore key terminology, from the k-means clustering algorithm to linear regressions, allowing you to interpret data and predict upcoming business trends.

Discover the power of market basket analysis and network analysis

You’ll learn to analyse transaction data, using the concept of association rules analysis, before moving on to learning the basics of network metrics and analysis.

By the end of this course, you’ll have enhanced your understanding of data analysis and the insights it can deliver within your business environment. Equipped with an understanding of processes used within business data analytics, you’ll be able to work alongside your data analytics team to deliver better strategies and make data-driven decisions.

Download video: standard or HD

Skip to 0 minutes and 9 seconds If you’re a business manager, you’ve probably asked yourself, “what if there was a way to make smarter business decisions”? Fortunately, this course, data analytics for managers will help you develop the skills to answer this question and more. You’ll be able to leverage data to improve your business and work more effectively with data analysts. This course is unique. It presents complex data analysis topics in a practical way that you can easily apply to your business environment, even if you have no prior knowledge of data analytics. So, if you’re interested in finding out more about using data to improve your business and solve common business problems, then enroll in this Data Analytics for Managers course from the University of Adelaide. Now.


  • Week 1

    Introduction to data analytics

    • Getting Started

      This section includes all the information you will need to get started in this course.

    • Introduction to Week 1

      Let's take a look ahead to what we'll be covering this week.

    • What is data analytics?

      Find out how data can be used to make discoveries and predictions and measure success.

    • What are the roles and responsibilities in a data analytics team?

      Find out about the different roles in a data analytics team and the types of analysis they perform.

    • What are the different types of data analytics techniques?

      Only a handful of distinct data analytics techniques are used to solve problems. Find out what they are.

    • What is the data analytics process?

      There is a standard approach to using data analytics to solve problems in every area of business. Find out more about this.

    • Assessment

      Do you know what data analytics is, the main methods used and what data can do for you? Take this test to find out how much you know.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what's coming up next.

  • Week 2

    Discovering new patterns in data to transform your business

    • Introduction to Week 2

      This week you will learn how discovering new patterns in data can help you transform your business.

    • Strategies in using new data patterns to transform your business

      This activity is an introduction to unsupervised data analytical techniques and the important role they can serve in business.

    • What is a cluster? Similarity and distance measures

      In this activity, you will begin your exploration of the clustering procedure and find out how similarity between points in a cluster can be measured.

    • The k-means clustering algorithm

      K-means clustering is one of the most common and useful clustering techniques. In this activity, you will find out how it is done in practice.

    • Optimising your clustering analysis with the elbow method

      In this activity, you will find out how to determine the number of clusters you should be looking for in your data.

    • Limitations of k-means clustering analyses

      Complete this activity to find out the circumstances in which the k-means clustering algorithm is ineffective.

    • Assessment

      Can you evaluate the validity and methodology of a business report that utilises a k-means clustering analysis? Complete this assessment to find out.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what's coming up next.

  • Week 3

    Making predictions using your data to solve business problems

    • Introduction to Week 3

      This week you will learn about the supervised analysis technique of regression analysis.

    • Simple linear and non-linear regressions

      Find out how regression analysis can help you to make predictions to solve business problems.

    • Complex linear and non-linear regressions

      Find out how more complex linear and non-linear regressions can help you make more accurate predictions.

    • Non-linear regression with neural networks

      Find out about neural networks and how they are designed to mimic the learning process of a human brain.

    • Overfitting

      Learn about overfitting and how it can be avoided.

    • Assessment

      Take this test to find out how much you have learned about linear and non-linear regression and neural networks.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what's coming up next.

  • Week 4

    Predicting the category of data points to solve business problems

    • Introduction to Week 4

      Let's take a look ahead to what we'll be covering this week.

    • K-nearest neighbours

      This activity is an introduction to the algorithm of k-nearest neighbours (k-NN for short) which is used to make predictions.

    • Decision trees and random forests

      In this activity you will learn about decision trees and random forests. They are a popular alternative to neural network analysis.

    • Assessment

      What have you learnt about k-nearest neighbours, decision trees and random forests? Complete this assessment to find out.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what's coming up next.

  • Week 5

    The power of shopping basket analysis

    • Introduction to Week 5

      This week you will learn about the power of market basket analysis.

    • Association Rules

      This activity explains association rules. An association rule is a rule that tells us “what goes with what”.

    • The Apriori algorithm

      Several algorithms have been proposed for identifying frequent item sets, but the classic one is the Apriori algorithm of Agrawal and Srikan. Find out more in this activity.

    • Assessment

      Can you explain the uses of association rules analysis? Do you know how to interpret the results and determine if a rule is worth pursuing to redesign an aspect of a business? Complete this assessment to test your knowledge.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what's coming up next.

  • Week 6

    What are your influencers?

    • Introduction to Week 6

      Let's take a look ahead to what we'll be covering this week.

    • Basics of networks

      Find out how the field of graph network analysis provides a standard set of tools for solving business problems and the relational data created by online social media tools allows businesses to design solutions for customers.

    • Network metrics

      Some examples of network metrics are density, centralisation and degree centrality. Continue your learning to find out more about these metrics.

    • Assessment

      Can you uncover data relationships through network analysis? Take this text to find out.

    • Bringing it all together

      Let's reflect on what we've covered this week and take a look at what your next steps might be.

    • What's next?

      Congratulations on making it to the end of the course. We have really enjoyed sharing this learning journey with you. Let's reflect on what we've covered over the past weeks and look at ways for you to carry on learning!

Who is this accredited by?

The CPD Certification Service
The CPD Certification Service:

The CPD Certification Service was established in 1996 and is the leading independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

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...

  • Explain data analytics and how it is practised and applied within a business environment.
  • Evaluate the results of data analysis within a business context.
  • Describe different types of data processing and explain how they solve common business problems.

Who is the course for?

This course is designed for managers who want to improve their knowledge of data analytics. It will help both managers and those in leadership work effectively with data science teams and data analysts to improve business processes, identify trends and interpret data.

This course is suitable for managers who already work with data analysts, as well as those looking to expand their business team to include data analysts.

Whilst the primary audience is those in management roles, this course may also benefit those who collaborate with data analysts who wish to further their understanding of data analytic processes, key terminology and practices.

No prior knowledge or experience of data analytics is required, though you do need an understanding of basic maths terminology such as mean, logarithm, and Pythagoras.

Who will you learn with?

I am a particle astrophysicist and data scientist at the University of Adelaide. I co-lead a University of Adelaide Data Analytics Group that applies data science to industry problems.

I work as a research assistant in the School of Physical Sciences at the University of Adelaide. Much of my work involves simulating and analysing huge amounts of particle physics data.

I am currently a postgraduate student studying Physics at the University of Adelaide. Along with being a data scientist in the past, I have experience in teaching a first year machine learning course.

Who developed the course?

The University of Adelaide

The University of Adelaide is a world-class teaching and research institution. They are committed to developing quality students and lifelong learners who are recognised for their skills, creativity, global outlook and ability to succeed.

  • World ranking

    Top 110Source: QS World University Rankings 2023

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

Want to know more about learning on FutureLearn? Using FutureLearn

Get a taste of this course

Find out what this course is like by previewing some of the course steps before you join:

Do you know someone who'd love this course? Tell them about it...