Business Analytics: Decision-Making Using Data

Leverage data-driven tools to optimise business outcomes

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Course Dates

STARTS ON

29 February 2024

Course Duration

DURATION

11 weeks, online
4–6 hours per week

Course Fee

PROGRAMME FEE

£1,680 and get £175 off with a referral

Course Information Flexible payment available
Course Fee

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Emeritus is collaborating with Cambridge Judge Business School Executive Education to help you build future-ready skills. Enrol before and get up to 4% tuition assistance to set yourself up for professional success.​

Application Details

Tuition assistance is live as per below schedule. The full programme fee is £1,750 as of the start date.

programme fee

£1,680

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Why enrol in the Business Analytics programme?

Business Analytics: Decision-Making Using Data is an 11-week online programme brought to you by Cambridge Judge Business School Executive Education. This hands-on, interactive programme will enable you to:

  • Design experiments to answer questions about the success or failure of a hypothetical change made in an organisation.
  • Describe sets of data using descriptive statistics and visual analyses.
  • Make business decisions using different tools and techniques for big data.
  • Identify organisational and behavioural biases that affect decision-making, and develop strategies for overcoming them.
  • Identify important legal and ethical concepts, and apply them to different organisational problems.

Drawing on faculty expertise, case studies and peer interactions, you will gain the skills to turn your organisation’s data into a strategic asset that drives more informed decisions and better business outcomes.

22%

Only two in ten (22%) believe they have the necessary skills in their organisation to deliver strong value from data.

Source: DataIQ

42%

Less than half (42%) of respondents felt that the benefits of using data were clearly understood within their organisation.

Source: DataIQ

19X

Businesses that base decisions on data are 19 times more likely to be profitable.

Source: McKinsey

Proven results

See how our learners saw them grow
65%
Made successful career transitions
67%
Applied learning to their jobs
97%
Created more impact at work

What you will learn

This programme does not require coding. To help you understand the unique opportunities and challenges of business analytics, this online programme concentrates on areas designed to advance your use of analytics to drive greater success.

Module 1:

Decision biases

Learn the importance of data-driven decision-making in the modern world. Understand how to frame a problem, and identify the main hazards that prevent us from making optimal decisions.

Module 2:

Descriptive analytics

Obtain data through techniques that include data mining and web scraping, and make it usable through data cleaning. Explore various application programming interfaces, which help applications and databases (or other services) communicate with each other.

Module 3:

Big data opportunities

This module provides an overview of big data, noting both the opportunities and challenges. Explore the four Vs of big data: volume, variety, velocity and veracity — and how these attributes are used to extract value to make important business decisions.

Module 4:

Experimentation

Learn the importance of experimentation in drawing meaningful conclusions from big data. Explore various standards of experimentation with A/B testing, randomised controls and correlations.

Module 5:

Predictive analytics I — Machine learning

Predicting the future with more confidence becomes a reality as you explore various supervised machine learning algorithms, such as regression, decision trees and support vector machines.

Module 6:

Predictive analytics II — Neural networks

Gain an understanding of how neural networks learn through training and how predictions are made. Learn how to choose the right network architecture for making business predictions, and assess whether you require a neural network at all.

Module 7:

Prescriptive analytics I

Create an action plan for your business by linking predictive analytics data with your business model and objectives using value driver trees. Use decision trees to run simulations to predict profits for various scenarios and levels of uncertainty.

Module 8:

Prescriptive analytics II — Behavioural economic biases

Focus on risk aversion by examining the frame through which you view the problem. Learn the significance of defining collective objectives, constraints and decision criteria to avoid biases and overcome decision traps in the decision-making process.

Module 9:

Ethics/Legal and organisational issues I

Learn about the challenges in implementing data obtained from your various analytics projects and how to overcome them by setting up the appropriate infrastructure within your organisation.

Module 10:

Ethics/Legal and organisational issues II

Understand the legal issues associated with big data, and reflect upon the ethical considerations of predicting customers' personalities using their online profiles to send them targeted advertisements.

Module 1:

Decision biases

Learn the importance of data-driven decision-making in the modern world. Understand how to frame a problem, and identify the main hazards that prevent us from making optimal decisions.

Module 6:

Predictive analytics II — Neural networks

Gain an understanding of how neural networks learn through training and how predictions are made. Learn how to choose the right network architecture for making business predictions, and assess whether you require a neural network at all.

Module 2:

Descriptive analytics

Obtain data through techniques that include data mining and web scraping, and make it usable through data cleaning. Explore various application programming interfaces, which help applications and databases (or other services) communicate with each other.

Module 7:

Prescriptive analytics I

Create an action plan for your business by linking predictive analytics data with your business model and objectives using value driver trees. Use decision trees to run simulations to predict profits for various scenarios and levels of uncertainty.

Module 3:

Big data opportunities

This module provides an overview of big data, noting both the opportunities and challenges. Explore the four Vs of big data: volume, variety, velocity and veracity — and how these attributes are used to extract value to make important business decisions.

Module 8:

Prescriptive analytics II — Behavioural economic biases

Focus on risk aversion by examining the frame through which you view the problem. Learn the significance of defining collective objectives, constraints and decision criteria to avoid biases and overcome decision traps in the decision-making process.

Module 4:

Experimentation

Learn the importance of experimentation in drawing meaningful conclusions from big data. Explore various standards of experimentation with A/B testing, randomised controls and correlations.

Module 9:

Ethics/Legal and organisational issues I

Learn about the challenges in implementing data obtained from your various analytics projects and how to overcome them by setting up the appropriate infrastructure within your organisation.

Module 5:

Predictive analytics I — Machine learning

Predicting the future with more confidence becomes a reality as you explore various supervised machine learning algorithms, such as regression, decision trees and support vector machines.

Module 10:

Ethics/Legal and organisational issues II

Understand the legal issues associated with big data, and reflect upon the ethical considerations of predicting customers' personalities using their online profiles to send them targeted advertisements.

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Case studies

Image displaying a silver hotel reception call bell to portray the Hotel Industry.

Hotel industry

How does a hotel booking platform test whether advertising on its website works?

Netflix use its competition to improve their search and recommendation algorithms

Netflix

How did Netflix use its competition to improve their search and recommendation algorithms?

Art

Art

How do you use neural networks to train computers to replicate the styles of different artists?

London Time

London Time

How many fashion watches should London Time order before the selling season begins?

Cambridge Breakthrough Science (Biotech Company)

How will they decide which two of the four promising drugs should be developed further?

UPS

How did UPS’ ORION initiative allow them to save an estimated $300-$400 million and a reduction of 100 million miles driven?

Our students

The 11-week Business Analytics: Decision-Making Using Data is designed for managers across all functions, seniority levels, industries and geographies who are interested in learning the tools and analytical approaches to become data-driven leaders.

Geography

  • Europe — 50%
  • Asia — 22%
  • North America — 18%
  • Africa — 6%
  • South America — 4%


Experience

  • < 5 years — 12%
  • 5–9 years — 19%
  • 10–14 years — 23%
  • 15–19 years — 20%
  • 20+ years — 26%



Industries

  • Financial services — 16%
  • IT products and services — 12%
  • Consulting — 8%
  • Healthcare — 8%
  • Education — 6%
  • Other — 50%

How you will learn

Video lectures

Video lectures

Recorded video lectures are conducted by programme faculty. These lectures are dynamic, engaging and designed to reinforce learning.

Workbook activity

Workbook activity

Each assignment attempted in the workbook activity is reviewed and graded by programme leaders who are experts from the industries.

Live office hours

Live office hours

Learners will engage with faculty in live sessions to develop the components of an innovation strategy for their organisations.

Peer networking

Peer networking

Engage with other data analytics professionals from a wide range of backgrounds and industries, and leave the programme with an enduring professional network you can connect with to exchange ideas and share opportunities.

Dedicated programme team support

Dedicated programme team support

A learning team will provide ongoing personalised support and check on your progress throughout the programme.

Case studies

Case studies

The programme features a blend of case studies, organisational scenarios and insights in addition to other relevant industry examples.

Faculty

Profile picture of course faculty Dr Nektarios (Aris) Oraiopoulos

Professor Nektarios (Aris) Oraiopoulos

Professor in Operations & Technology Management, Director of the MPhil in Strategy, Marketing & Operations Programme, PhD (Georgia Institute of Technology), BEng (National Technical University of Athens)

David’s research uses big data to understand psychology. He published papers using social media data from millions of consenting individuals to show that the computer can predict a user’s personality as accurately as their spouse can... More info

Profile picture of course faculty Dr David Stillwell

David Stillwell

Professor of Computational Social Science, Academic Director of the Psychometrics Centre, BSc, MSc, PhD (University of Nottingham)

David’s research uses big data to understand psychology. He published papers using social media data from millions of consenting individuals to show that the computer can predict a user’s personality as accurately as their spouse can.... More info

Testimonials

Zahi El Haiby

"The theory put into practice is very strong in this programme, and the programme is based on research, real use cases and experiences."

— Zahi El Haiby, Consultant, Delivery Associates

Deepak Joshi

"The course material is customised and rich, and the short videos make even big concepts clear…it was great learning from such a global, diverse and experienced cohort of 248!"

— Deepak Joshi, Deputy Vice-President, Renault Nissan Technology and Business Centre India

Elijah Lutwama

"The best part of the programme was seeing real-life examples of how and where data is used in decision making…I finally understand the term “machine learning” and the limits and possibilities of data-driven decision making."

— Elijah Lutwama, Head of Finance, ASARECA

Cui Heng Cao

"I appreciated the lesson on psychological and behavioural influence on analysis and decision making. I also enjoyed all the business cases examples—they were highly relatable–as well as understanding the critical role of the ‘interpreter’ between business and data scientists."

— Cui Heng Cao, Business Architect, Cisco Systems, Inc.

Paul Watson

"The big thing for me was understanding analytics-based decisions that other companies are making in their business. This course pulled it all together and it will help guide me in my next venture."

— Paul Watson, Business Intelligence, FT

Certificate

Certificate

Upon successful completion of the programme, participants will be awarded a digital certificate of completion by Cambridge Judge Business School Executive Education.

Please note that this programme can be incorporated into the completion of the Cambridge General Management Certificate of Achievement (GMCA). It will be credited as an 'in-person' two-day programme for the purpose of meeting the GMCA requirements. If you require more details on the GMCA and wish to speak to our advisers, please contact executive.education@jbs.cam.ac.uk.

Note: After successful completion of the online programme, your verified digital certificate will be emailed to you in the name you used when registering for the programme. All certificate images are for illustrative purposes only and may be subject to change at the discretion of Cambridge Judge Business School Executive Education.

Past Participants Reviews

4.3

COLLINS ODIWUOR
Business Process Analyst/Business Analyst, KCB BANK KENYA LTD
April 2022
I'm new to data analytics, so every bit of the programme has been extremely interesting as it kept giving me a new perspective. What I loved most was when we used systems and applications like machine learning, tensor flows and decision trees to dissect data and decipher more meaning from it.
Javier García
Senior Translator, Asociacion Chilena de Seguridad
April 2022
I think that the modules structure was quite nice. It made sense to have these lessons in the particular order that was given.
Serdal Korkut AVCI
February 2022
Lots of details about how data is managed to create decisions. We partly know some of these but explanation through real-life examples and consequences helps to understand better. Also, the ethics of using data and to what extent is critical to understand in implementation.
Stephen Scott
Solutions Architect, Private
November 2021
The webinar and office hours were great because this is the only time we have interaction with the staff.

FAQs

  • How do I know if this programme is right for me?

    After reviewing the information on the programme landing page, we recommend you submit the short form above to gain access to the programme brochure, which includes more in-depth information. If you still have questions about whether this programme is a good fit for you, please email learner.success@emeritus.org, and a dedicated programme adviser will follow up with you very shortly.


    Are there any prerequisites for this programme?

    Some programmes do have prerequisites, particularly the more technical ones. This information will be noted on the programme landing page, as well as in the programme brochure. If you are uncertain about programme prerequisites and your capabilities, please email us at the ID mentioned above.


    Note that, unless otherwise stated on the programme web page, all programmes are taught in English, and proficiency in English is required.


    What is the typical class profile?

    More than 50 per cent of our participants are from outside the United States. Class profiles vary from one cohort to the next, but generally, our online certificates draw a highly diverse audience in terms of professional experience, industry and geography—leading to a very rich peer learning and networking experience.


    What other dates will this programme be offered in the future?

    Check back at this programme web page or email us to inquire if future programme dates or the timeline for future offerings have been confirmed yet.

  • How much time is required each week?

    Each programme includes an estimated learner effort per week. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page.



    How will my time be spent?

    We have designed this programme to fit into your current working life as efficiently as possible. Time will be spent among a variety of activities, including:



    • Engaging with recorded video lectures from faculty
    • Attending webinars and office hours, as per the specific programme schedule
    • Reading or engaging with examples of core topics
    • Completing knowledge checks/quizzes and required activities
    • Engaging in moderated discussion groups with your peers
    • Completing your final project, if required

    The programme is designed to be highly interactive while also allowing time for self-reflection and to demonstrate an understanding of the core topics through various active learning exercises. Please email us if you need further clarification on programme activities.



    What is it like to learn online with the learning collaborator, Emeritus?

    More than 300,000 learners across 200 countries have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 per cent of the respondents of a recent survey across all our programmes said that their learning outcomes were met or exceeded.

    All the contents of the course would be made available to students at the commencement of the course. However, to ensure the programme delivers the desired learning outcomes the students may appoint Emeritus to manage the delivery of the programme in a cohort-based manner the cost of which is already included in the overall course fee of the course.

    A dedicated programme support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues or anything else that may affect your learning experience.


    How do I interact with other programme participants?

    Peer learning adds substantially to the overall learning experience and is an important part of the programme. You can connect and communicate with other participants through our learning platform.

  • What are the requirements to earn the certificate?

    Each programme includes an estimated learner effort per week, so you can gauge what will be required before you enrol. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page. All programmes are designed to fit into your working life.

    This programme is scored as a pass or no-pass. Participants must complete the required activities to pass and obtain the certificate of completion. Some programmes include a final project submission or other assignments to obtain passing status. This information will be noted in the programme brochure. Please email us if you need further clarification on any specific programme requirements.


    What type of certificate will I receive?

    Upon successful completion of the programme, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools or potential employers. You can use it on your cover letter or resume and/or display it on your LinkedIn profile.

    The digital certificate will be sent approximately two weeks after the programme, once grading is complete.


    Can I get the hard copy of the certificate?

    No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social networking platforms, such as LinkedIn, Facebook and Twitter.


    Do I receive alumni status after completing this programme?

    No, there is no alumni status granted for this programme. In some cases, there are credits that count towards a higher level of certification. This information will be clearly noted in the programme brochure.


    How long will I have access to the learning materials?

    You will have access to the online learning platform and all the videos and programme materials for 12 months following the programme start date. Access to the learning platform is restricted to registered participants per the terms of agreement.

  • What equipment or technical requirements are there for this programme?

    Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files and transcripts.


    Do I need to be online to access the programme content?

    Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access programme content from a desktop, laptop, tablet or mobile device.

    Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you can view them later.

  • Can I still register if the registration deadline has passed?

    Yes, you can register up until seven days past the published start date of the programme without missing any of the core programme material or learnings.


    What is the programme fee and what forms of payment do you accept?

    The programme fee is noted at the top of this programme web page and usually referenced in the programme brochure as well.

    • Flexible payment options are available (see details below as well as at the top of this programme web page next to FEE).
    • Tuition assistance is available for participants who qualify. Please email learner.success@emeritus.org.

    What if I don’t have a credit card? Is there another method of payment accepted?

    Yes, you can do the bank remittance in the program currency via wire transfer or debit card. Please contact your programme adviser or email us for details.


    I was not able to use the discount code provided. Can you help?

    Yes! Please email us with the details of the programme you are interested in, and we will assist you.


    How can I obtain an invoice for payment?

    Please email us your invoicing requirements and the specific programme you’re interested in enrolling in.


    Is there an option to make flexible payments for this programme?

    Yes, the flexible payment option allows a participant to pay the programme fee in instalments. This option is made available on the payment page and should be selected before submitting the payment.


    How can I obtain a W9 form?

    Please connect with us via email for assistance.

  • What is the policy on refunds and withdrawals?

    You may request a full refund within seven days of your payment or 14 days after the published start date of the programme, whichever comes later. If your enrolment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to admissions@emeritus.org.



    What is the policy on deferrals?

    After the published start date of the programme, you have until the midpoint of the programme to request to defer to a future cohort of the same programme. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrolment and are subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period, and the limit of one deferral per enrolment remains. All deferral requests should be sent to admissions@emeritus.org.

Didn't find what you were looking for? Write to us at learner.success@emeritus.org or Schedule a call with one of our Academic Advisers or call us at +44 203 479 4043 (UK) / +1 315 819 0707(US) / +65 3163 8580 (SG)

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