Business data analytics and decision making
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This module will introduce you to methods used to facilitate data-driven business decision-making. It will equip you with a basic knowledge of 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 quantitative methods used in a business context. The module will apply these methods to datasets typically encountered in business.
You'll study the principles involved in data analysis techniques and reasoning for decision-making in business, marketing, 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.
- Randomness in business data and possible distributions of data.
- Big data.
- Principles of statistical estimation.
- Hypothesis testing and confidence intervals.
- Modelling relationships between variables.
- Linear regression.
- Index numbers.
- Introduction to forecasting.
- 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:
This self-assessment quiz is intended to help you check your understanding of the numerical skills required to study the module material. You will receive feedback on each question and will be directed to links to free OpenLearn materials which will help you to refresh your numerical skills if necessary. Please note you will need a (free) Open University account to access the quiz.
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.