Develop the skills you need to analyse, interpret and communicate data with confidence and
impact within your organisation

Data Analysis for Management

About This Course

The demand for Data Scientists exceeding the supply is a severe problem in the data-driven world we are living in today. As a result, most organizations are willing to pay high salaries for professionals with appropriate Data Science skills. Guided by SkillEnable and LSE experts, this 8-week course will provide you with the knowledge and practical skills while increasing your ability to analyse and interpret data within your organisation.

During the course, you will develop an understanding of how data-driven models can inform management and decision-making strategies, learn how to extract business information from data, and predict future trends.

This course emphasizes the method used to learn data skills by presenting in Tableau, the industry-leading intelligence software and statistics. By using Tableau, you will have the opportunity to apply the tools and techniques you are learning, and discover how they can be used to generate significant data and visual effects.

Key Details​​

Programme Type:

Online Certificate Course



Start Date:

23RD March 2022


8 weeks


7-10 hours per week


Department of Management

How will you learn

Every course is broken down into manageable, weekly modules, designed to accelerate your learning process through diverse learning activities:


  • Work through your downloadable and online instructional material.

  • Interact with your peers and learning facilitators through weekly class-wide forums and reviewed small group discussions.

  • Enjoy a wide range of interactive content, including video lectures, infographics, live polls, and more.

  • Investigate rich, real-world case studies.

  • Apply what you learn each week to quizzes and ongoing project submissions, culminating in a capstone project demonstrating your enhanced ability to analyse, summarise, and report on insights extracted from data, for more effective business decision-making.

Data Analysis for Management Course Trailer

What does This Course Cover

This online management certificate data analysis course equips you with the skills needed to make data-driven decisions, which gives you and your organisation the opportunity to compete in any industry.

Throughout this course, you will learn to check the reliability of the data, extract the details of strategic business, and use modeling to predict future trends. Guided by SkillEnable experts, you will develop the ability to visualise data which you will be able to communicate clearly to all participants and gain insights into how data-driven models can improve your business decision-making ability.

This course culminates in the completion of the capstone project, which demonstrates your ability to use data to get information to inform business strategy. You will also have the opportunity to network with like-minded and professional industry leaders, and grow your global business community, while earning a SkillEnable certificate in collaboration with the London School of Economics and Political Sciences.

SkillEnable is collaborating with The London School of Economics and Political Science to create a new class of learning experience – one that is intimate, and personalised for both freshers as well as working professionals.

A Powerful Collaboration

About The London School of Economics and Political Science (LSE)

The London School of Economics and Political Science (LSE) is a leading dedicated social science university. LSE was founded in 1895 with the aim of understanding the causes of things for the “betterment of society”. LSE seeks to make research and teaching practical and relevant to the real world. The School counts 18 Nobel Prize winners and 37 world leaders amongst its alumni and staff. LSE has students from over 160 countries, and over 100 languages are spoken on campus.

About LSE Online Certificates

LSE is dedicated to addressing global issues through research and education, and is the most international of all British universities. By offering online certificate courses designed by expert LSE faculty members, the School aims to make its state-of-the-art social sciences research and insights available to a wider global audience. The supported, interactive online learning model allows participants to study from anywhere in the world, at times of their convenience, while still interacting with peers and teaching staff alike.

Module Details

You’ll be welcomed to the course and begin connecting with fellow participants, while exploring the navigation and tools of your Online Campus. Be alerted to key milestones in the learning path, and review how your results will be calculated and distributed.

You’ll be required to complete your participant profile, confirm your certificate delivery address, and submit a digital copy of your passport/identity document.

Please note that module titles and their contents are subject to change during course development.

Week 1-3

Outline the challenges of decision-making under uncertainty, using business case examples:

  • Recall some common dilemmas managers encounter

  • Highlight how data-driven models can impact managerial decision-making

  • Discuss managerial decision-making through the use of cross-sector illustrative applications

  • Identify problems with uncertain outcomes that require the use of data-driven models and the quantification of uncertainty

  • Identify the requirements of the project to be completed at the end of the course

Week 1-3

Harness data visualisation to bring data to life, and employ descriptive statistics to summarise important data points.

  • Define common principles of data reduction.

  • Calculate components of data reduction.

  • Recognise how Tableau is used in data visualisation.

  • Apply the essential functions of Tableau to summarise and illustrate a data set.

Week 4-6

Construct and use probability distributions for making decisions.

  • Identify how to quantify probabilities.

  • Interpret simple probability distributions.

  • Determine updated probabilistic beliefs in light of new information.

  • Contrast the likelihood of different scenarios to inform decisions by quantifying the risk of particular outcomes.

Week 7-9

Appreciate the reliability and validity of data, and analyse estimation error.

  • Recognise the value of considering the reliability and validity of data.

  • Discuss the impact of unreliable and invalid data on business decisions

  • Calculate and interpret estimation error.

  • Estimate population characteristics while considering sample size.

Week 10-12

Test theories or claims through statistical significance.

  • Recognise the consequences of type I and type II errors.

  • Identify the binary nature of decisions in hypothesis testing.

  • Discuss statistical proof and the inferences drawn from a statistical test.

  • Outline the impact of effect size and sample size on statistical significance.

  • Calculate the statistical significance of a test.

  • Analyse the calculated statistical significance of a test to draw conclusions.

Week 13-15

Model causality using regression analysis to explain the variation in dependent variables of interest.

  • Recognise the fundamentals of regression analysis.

  • Discuss the complexity of linearity and its suitability to analysing data.

  • Identify some of the challenges and assumptions associated with regression analysis.

  • Execute a regression analysis.

  • Analyse the results from a regression analysis to conclude what drives the variation in variables.

Week 16-18

Challenges and uses of producing forecasts of the future.

  • Identify the purpose and application of time series forecasting.

  • Distinguish the time series components of trends, seasonality, cycles, and black swans.

  • Predict future time series.

  • Assess prediction performance.

Week 19-21

Consolidate course topics through a capstone project.

  • Identify the dos and don'ts of presenting and reporting key insights extracted from data

  • Apply presentation and reporting techniques

  • Investigate the key insights of a given data set

  • Produce a presentation communicating key insights extracted from data

  • Develop a summary report communicating key insights extracted from data

  • Identify opportunities available to improve quantitative skills

  • Recognise what you have achieved during this course

Week 21-24

This Course Is For You If You Want To

Who You Will Learn From

This subject matter expert from London School of Economics will guide you along with a variety of industry professionals.


View Profile

Dr James Abdey gained his PhD in statistics at LSE, and has taught at LSE since 2008. He teaches the Department of Statistics’ undergraduate courses in mathematical statistics and quantitative methods, as well as elective courses in market research. His research interests include market research techniques and forensic statistics – the interplay of statistics and the law. Dr Abdey has extensive experience developing learning resources for LSE’s distance learning and summer school programmes in economics, mathematics, and statistics, and regularly teaches in Central Asia, Eastern Europe, and the Far East. Outside of academia, he has also worked on various quantitative-based consultancy projects in areas including the art market, and the World Gold Council, and has given seminars at the UK parliament.



Tuition fee:  ₹1,51,666

Upon successful completion of the course, you will receive an LSE certificate of competence.



Advance Your Career


Be data-focused and improve your ability to analyze, interpret, and communicate data effectively.

Improve Your Business


Make wise and informed decisions, and be able to communicate these with confidence, impact, and trust.

Leverage Insights


Learn data analysis techniques that can be used to get important information, inform business strategy, and predict future trends.

Validate Your Skills


Obtain a certificate from LSE, which officially validates your business management data analysis information.