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Avis et commentaires pour d'étudiants pour Data-driven Decision Making par PwC

4.6
étoiles
4,270 évaluations
778 avis

À propos du cours

Welcome to Data-driven Decision Making. In this course you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017....

Meilleurs avis

CE

May 10, 2018

Great high-level introduction into what big data is, how data & analytics is impacting business decision making, and how PwC uses data & analytics to improve the quality of work delivered to clients.

AF

Aug 16, 2018

This is a great course in data and analytics for the every day professional. It gives great insight into how data and analytics can support decision making. The mode of delivery of the course is e

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676 - 700 sur 747 Avis pour Data-driven Decision Making

par Andres R

Dec 15, 2016

Great for beginners!

par Dali S

Mar 08, 2018

Good intro course.

par Yasha P

Mar 31, 2017

was an excellent c

par Jorge C

Mar 01, 2017

Muy recomendable

par Seth S M A

Mar 30, 2017

Great insight.

par Lee Y T J

Oct 12, 2017

useful course

par Marcus V

Apr 06, 2017

Great course.

par Alwaleed A M A

Nov 24, 2018

great intro!

par Nick B

Nov 27, 2017

Good basics

par PRABHAT K

Sep 24, 2017

Good

par Sanket S

Dec 20, 2016

Lear

par Rajvi V

Jun 11, 2018

G

par Richard B

Apr 09, 2018

The course content is predominantly high-level and unspecific and gives an brief overview of data analysis tools that would only be new in case of no prior knowledge in the spheres involving data analysis. I would suggest devoting more content in the course to specific types of data, as well as specific data analytics frameworks and techniques.

The final project was rather ambiguous as there were little to no guidelines with respect to how to complete it. The case study required to provide detailed answers regarding the analysis, however, the sample cases did not provide much detail that would be adequate to answer some of the test questions (e.g. questions regarding achieved insights, insight-based recommendations etc.).

par Anais W

May 02, 2018

This course is a good introduction to how companies analyze and visualize data. I didn't always feel like the course material gave me a real understanding of the topics and the tests don't have versions or any explanation of incorrect answers--but you can take them many times--so they can sometimes be more of a guessing game than effective tests of knowledge or understanding. This course would be improved by more meaningful discussion topics (I sometimes skipped these because they didn't feel meaningful), more practice questions or simulations, and more refined case studies (with perhaps some guiding multiple choice before the open-ended final assignment).

par Esther

Dec 14, 2018

i would not recommend this course to people who have more than 3 years of experience in finance or data analysis, it is too much theory that are based on "Commonsense" and is not practical. However, I would think it will be helpful for college students or people who have no idea about data analysis at all and this will be a good starting point.

Another comment is: since PWC is a professional services firm, they are very different in presenting the materials vs a real college professor---for me, it is a bit too "professional" and lack the atmosphere of a study group.

par Jessica P

Dec 28, 2016

This course does a good job overall of framing the importance and challenges of working with big data, and certainly inspired me to want to learn more. However, I think the material could be organized better, and the lectures are not nearly the same quality as the universities' courses...not to mention too heavy on the PWC pitches. The quizzes and assignments don't necessarily correlate well with the lessons, and the assignments are structured poorly. Based on my experience, I would not recommend a PWC course to serious learners.

par Calvin R

Oct 03, 2016

The course is extremely helpful and the content is good. However, it is hard sometimes to follow the Principals/Directors teaching the course. Additionally, it would have been fantastic if a lot of time was spent on giving examples, practical work demonstrated and a thorough structure of how it was done.

Maybe, all this will be coming in the future courses. But for beginners, it is hard to understand and catch interest on the topic if not discussed with detailed examples and not merely giving highlights on the examples.

par James D S

Jan 24, 2018

Most of the useful content is during the last week of the course, when you work on a project. However, concepts such as creating a hypothesis/es are not fully introduced and may be confusing for those who do not already have some training in scientific method or statistical method (e.g., knowing what a null hypothesis is). The simulation was also not useful, and contains a lot of jargon. Most of the content in the first part of the course is blue sky jargon discourse about Big Data, and can probably be skipped.

par Aniket P

Jul 28, 2018

This course cover the concepts and aspects of analysis very well.However,regarding the final week assignment I feel that,it can be an overwhelming challenge for those who do not have any business related background.I am an Engineering graduate and hence couldn't understand some of concepts related to making business decisions,as they were not taught in the course.Other than that the overall Data Analytics industry and careers exposure were pretty well explained and informed.

par Pavel C

Aug 19, 2019

I personally found this course a good start for those new into the data-driven world, although there are three potential points for development

a) as most of the IT-related stuff it is getting outdated very quickly so this should be taken into consideration when talking about tools and systems

b) not enough information on data visualization principles which are VERY important (more than data themselves)

c) I'd also link this course to other courses e.g. on machine learning

par Mike Y W

Nov 12, 2018

This is a fairly high-level look into data and analytics, and mainly approaches this topic from a business angle albeit it would have been nice to go a little more into the analytic side of things before getting into the deep end in the second course in this specialization. The quizzes were overly easy, and the simulation final was really cool. The final peer assessment wasn't challenging enough relative to my expectations.

par Aynara

Feb 20, 2018

Very general overview, not really teaching specific techniques or approaches. It gives names of analyis tools and methods, so you know what to google, - i find that useful. However, it's mostly general and rather superficial information about how important is data and that companies should collect and analyze data, visualize results and take decisions based on the analysis.

par Anuj M

Nov 30, 2016

A good foundation course. I believe the information regarding tools and techniques could've been presented in a better manner by working on live files and displaying it. It was monotonous. Apart from the rest, the final course case studies were brilliant and helped us to collaborate our understanding of the course.

par Guy G

Jan 09, 2017

Overall, this is a good course. It provides many handy tools, frameworks, techniques for data-driven decision making process. It does improve my decision making skill. However, the course is quite short and doesn't have much in-depth content.

par Jason W

Oct 14, 2017

I know it is an introductory course, but there was not much that I feel like i learned from this course other than a bunch of vocabulary words. I hope that there is more technical instruction in the following courses in this sequence.