England.  Change location

Business data analytics and decision making

Qualification dates
Start End

This module will introduce you to methods used to facilitate data-driven business decision-making. It will equip you with a basic knowledge of qualitative and quantitative techniques to analyse data and skills to make decisions primarily in a business context. In particular, it will enable you to construct valid arguments, summarise and describe datasets, explore relationships between variables, make hypothesis-driven decisions, and employ basic forecasting techniques. Upon completion of the module, you'll be able to apply the techniques and tools acquired during the module in a professional environment.

What you will study

The aim of this module is to introduce you to core qualitative and quantitative methods used in a business context. The module will apply these methods to datasets encountered in such a context.

You'll study the principles involved in data analysis techniques and reasoning for decision-making in business, accounting and finance. Randomness is a defining characteristic of most datasets encountered in real life, which requires finding the signal in random and noisy data to make justified decisions.

The following topics will be covered by this module:
  • Types and sources of business data.
  • Visualising and exploring data in Microsoft Excel.
  • Descriptive analysis of datasets with one and two variables.
  • Sampling from a population.
  • Basics of probability theory, including random events, continuous and discrete random variables.
  • Randomness in business data: the normal distribution.
  • Introduction to critical thinking, inductive and deductive reasoning.
  • Principles of statistical estimation.
  • Hypothesis tests of means and proportions.
  • Relationships between variables: correlation and covariance.
  • Linear regression.
  • Introduction to forecasting, decomposition of time series.
  • Index numbers such as price indices and economic growth.
  • Using regressions to make forecasts.

The use of Excel spreadsheets will be key to an understanding and application of knowledge. Spreadsheets are used throughout the module as the central tool used by professionals for simple data management and analysis. Real-life datasets will be provided to help you develop professional skills beyond the traditional academic discourse. These skills can be applied more broadly to your professional or personal life.

You will learn

By studying this module, you'll understand how information is identified, collected and explored and then related to problem-solving for decision-making with a range of business data resources and appropriate methodologies. You'll be able to characterise and summarise datasets, explore relationships between variables using statistical techniques to support business decisions, as well as evaluate and develop information, data, and arguments necessary for decision making in ways that show you understand their strengths and limitations.

Entry requirements

Whilst there are no formal entry requirements, this module does require good numerical skills. A basic understanding of Microsoft Excel will also help. We will provide introductory materials to familiarise yourself with this spreadsheet software.

This is an OU level 1 module. OU level 1 modules provide core subject knowledge and study skills needed for both higher education and distance learning to help you progress to modules at OU level 2.

If you have any doubt about the suitability of the module, please speak to an adviser.

Preparatory work

If you would like to prepare for this module, you may find the following introductory resources on OpenLearn helpful:

What's included

You’ll have access to a module website, which includes:

  • a week-by-week study planner
  • module materials, including datasets to practice your analytical skills
  • audio and video content such as animations and screencasts
  • assignment details and submission section
  • online tutorial access.

Computing requirements

You’ll need broadband internet access and a desktop or laptop computer with an up-to-date version of Windows (10 or 11) or macOS Ventura or higher.

Any additional software will be provided or is generally freely available.

To join in spoken conversations in tutorials, we recommend a wired headset (headphones/earphones with a built-in microphone).

Our module websites comply with web standards, and any modern browser is suitable for most activities.

Our OU Study mobile app will operate on all current, supported versions of Android and iOS. It’s not available on Kindle.

It’s also possible to access some module materials on a mobile phone, tablet device or Chromebook. However, as you may be asked to install additional software or use certain applications, you’ll also require a desktop or laptop, as described above.

Teaching and assessment

Support from your tutor

Throughout your module studies, you’ll get help and support from your assigned module tutor. They’ll help you by:

  • marking your assignments (TMAs) and providing detailed feedback for you to improve.
  • guiding you to additional learning resources.
  • providing individual guidance, whether that’s for general study skills or specific module content.
  • facilitating online discussions between your fellow students, in the dedicated module and tutor group forums.
Module tutors also run online tutorials throughout the module. Where possible, recordings of online tutorials will be made available to students. While these tutorials won’t be compulsory for you to complete the module, you’re strongly encouraged to take part.


The assessment details for this module can be found in the facts box.

If you have a disability

The OU strives to make all aspects of study accessible to everyone and this Accessibility Statement outlines what studying B126 involves. You should use this information to inform your study preparations and any discussions with us about how we can meet your needs.

Future availability

Business data analytics and decision making starts once a year – in April. This page describes the module that will start in April 2025. We expect it to start for the last time in April 2031.

Course work includes:

2 Tutor-marked assignments (TMAs)
End-of-module assessment