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).

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.

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.

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.

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.

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.

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

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.

It is well structured, it comes from practice and there are very competent speakers.

But there is a lot of self-marketing for PWC sometimes it feels more like an PWC ad, but teaching you something. And it's too superficial. I miss i.a. explanations and samples of the types of analysis (regression, factor, mutivariant, ...) and I miss more detailled explanations and show cases from the tools like QlikView, Tableau, ...

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.

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.

The course gives deep insights into the importance of Data and Data analytics in the world of Business decisions and strategy. However, the course is extremely theoretical and doesn't involve a lot of practical exposure. At times, it just seems as a PR exercise by PWC.

Interesting overview of PWC's methodology of data-driven decision making. I found the descriptions of the processes and the tools utilized to be very superficial. I also found the guidance and grading rubric for the final 'peer-reviewed' project to be weak and unclear.

The last 2 weeks of the course were great. I really enjoyed the simulation and the project. It would have been great to have had some more practical work earlier in the course as the first 2 weeks read somewhat like an advertisement for PWC data consultancy.

I enjoyed this introductionary course to data and analytics. Thanks for the provided knowledge and materials PWC. Personally I found the level of difficulty too easy for an academic. I would also prefer less promotion about PWC in many of the video's.

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.

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.

The material was alright, and the instruction was eaay to digest. The final assignment was underdocumented wuch that the standards of the submission were very unclear, and the expectations on the rubric came out of left field.

Good stuff in general, but from my personal point of view: a little bit too much of general info around what data is and can be used for (I know much of it already). I think, however, that the course is great for beginners.

Is too much of an overview. I'd like if they could make the course much bigger and actually practice what was learned more and go more in depth. I'm gonna forget the information in a month for sure.

Some interesting information in this course. Good overview of data and decision making. I like the breakdown of the data-decision making model.

The Course is a bit too promotional of PWC.

The course talks about topics on a very abstract level and I expected it be comprehensive and detailed. As far as the delivery is concerned, I found it pretty nice and captivating.

Very high level. Lots of helpful information for those new to the data analytics space. I had hoped it would dive into more hands on learning of what to do once you have the data.

I wish they would not sell pwc so much in their presentations. It is too distracting.

Also you don't get certificates. The assignments aren't reviewed on time so beware.

I would call this more of a webinar, but a good overview of data analyst, and the core skills needed, I believe there should be more guide lines for the final project.