Excellent course, excellent instructor. THE GOOD: the instructor, Ximena, provided examples throughout of how a concept was applied in the real world, which made it (the concept) easier to grasp. As always, the hands-on approach mixed with the rest of the material really enhanced the learning experience. Illustrations of form, such as the one for an email, was great and more of that should be provided for beginners to take with them and use & develop as part of their own tool kits moving forward. WHAT COULD BE IMPROVED: how questions in quizzes and challenges are worded. I got dinged in a challenge because according to your site I got the answer wrong; however, the question is not clearly worded which led me to answer incorrectly. This is the second time this type of incident has occurred as it happened in the first course, and what's worse is that there's no communication avenue where I can reach out to and raise this concern. I take this course seriously as it is about my career what is affected, so scores and outcomes in marked challenges do matter to me. I still have not heard from the first time I raised my concern which was extremely difficult to connect with someone here on Coursera. Secondly, there should be material relating to the readings that can easily be downloaded for the student's future reference; at the moment I see some documents like forms and glossary, which is great, but nothing relating to the discussions in the videos. Videos are fantastic but notes that supplement these discussions could go a long way. Otherwise, this has been a great course delivered by a fantastic instructor and in a very professional way. Kudos Coursera/Google!

Some questions in the quizes are ambiguous. English could be a barrier because certain terms are a little vague and are associated with different meanings in other languages ("problem", "issue", "manage", "responsible", etc). When digging into certain definitions, there isn't always one correct response or one correct way of saying the same things.

For example, a numeric range can't be properly defined as a quantitative variable because it lacks the quantum. It can be ordered for sure, but it have to be treated like a qualitative variable that can be recoded as a quantitative discrete variable.

I would like also to pinpoint an example of wrong response in the final quiz:

"Using historical data to make informed decisions about how things may be in the future is an example of spotting something unusual". The right response is "False" but in the real world in order to spot something unusual you have to analyze data and if this data is historical then the answer is True. This also applies to a similar question from the same quiz: "Using historical data to make informed decisions about how things may be in the future is an example of making predictions". The right response is "False", but it shouldn't because predictions are built on historical data (otherwise how do you make predictions? data is always historical, as per definition).

In other words, as far as this course is made for both beginners and advanced users, there are some missing concepts that lead to different opinions, especially for an advanced user. Just to pretend I know what I'm saying, I have a Master Degree in statistics.

I've found that a lot of the interview videos tend to be more like filler than providing anything useful. I'd say watch them, but you don't need to take notes on them, and I speed up the audio on those to about 1.25-1.50 where I can still understand it but don't need to take notes on it. Since most of the lecturers/interviewees speak very slowly it really just brings it up to a normal speaking speed.

I've also found that the Qwiklabs is really buggy-- when I try to open the sheet to do the work, instead it just opens up a new copy of the dashboard thing, and it often takes me a minimum of 10 tries to get it to actually open a sheet.

Also, the last quiz before the final course quiz is weird-- there's one question that is about what to do with results that are outside the statistical norm, and the reading they direct you to doesn't actually answer the question they ask about it, at least not as far as I can tell. I had to go and search for the answer on my own, and even then I had to redo that quiz multiple times just to get that one answer correct because the reading was so vague and unhelpful. If you're going to have a question like that on the quiz, you need to be certain that it is answered clearly in the readings or videos.

I'm trying to remain motivated to do this course though.

I had a harder time paying attention to the instructor because her style of reading the script was a little unnatural to me (a bit sing-song-y), where her voice continually had an upward inflection at the end of sentences and some of the emphasis of the words made the word seem unrecognizable for a second and then I'd catch up with the lecture. To me, the effect was the content felt juvenile, since the presentation was that saccharine. To combat this, I read the script most of the time and that helped, but it was the biggest factor of not wanting to continue with this course. She seems qualified and lovely as a person, but I truly hope I'm not instructed by her again.

With regard to the content, some of this was a review and it was still nice to catch some new tips and tricks along the way. I don't always feel the quizzes are testing my knowledge enough. While I get some questions wrong, I feel like the reason is due to not matching an exact phrase to a lesson, rather than not getting it correct because I was proving I know how to make a chart or how to calculate what's being asked. I just hope my good grades aren't reflecting a few memorized definitions, and indicative of my ability to perform the analysis I've been taught.

As with Course 1: Foundations: Data, Data Everywhere, I found this course to be highly informative and easy to follow along. The material presented was taught in a clear manner and the additional source links for further learning were extremely helpful. The instructors are engaging, which makes the videos fun to watch, especially since they are broken down into lengths that are less than 10 minutes. Again, I would say that the learning logs and the discussions seem unnecessary. There is literally zero accountability to complete either. As I continued through this course, I noted that while I was taking the time to complete these assignments, most of my other classmates were not. Answers to questions were "n/a" or just a copy/paste of the actual question being posed to us. Having to find people who were serious about the assignment so that I could actually do my required responses to two classmates answers proved difficult. Other than that, the course was great!

I still love this course! But considering this is the second course of 8, I think it would be more apt to describe what's different here than overall.

Admittedly, this course was more of a struggle for me to get through. To begin with, I think the Learning Logs being based off each other and stemming from having to schedule a lengthy conversation with someone didn't help for someone like me who's trying to get through each of the courses as fast as allowed. I would have preferred more presented scenarios, or at least the first of the chain of 3

And as much as I love Ximena, I believe she was a little stilted in her speaking compared to Tony, which made it harder to engage, coupled with the fact you're given constant videos in the last weak which further made it a struggle to finish.

I still give it 4 stars, because the thoroughness of the course is still greatly appreciated! Thank you all for your hard work!

I think the instructor was really well organized and delivered the material professionally. The material and delivery were clear and well-scripted. Kudos to Coursera for their part in this course so far. In fact, if I was only rating Coursera, I would give this 5 stars. However, Quiklabs does not live up to Coursera's standards as far as I'm concerned. There are disconnects between instructions and how the Quiklab actually behaves. I consider myself an intermediate when it comes to technology, but when I start talking to myself after following directions religiously and still have problems I lose patience and find myself getting annoyed. You might want to focus on a more seamless transition to labs for students.

More questions on the quiz and way more questions on the challenges. The course needs more practical testing as well. What would be nice is if there was case study of some sort at the end of each course to tie everything together. Like a video that incorporates everything we learned.

Also a practical exercise that we can participate and for example complete an SOW or meeting agenda or complete an actual sort, calculation and formatting of data. Then in the scenario, what an ideal completed table looks like to compare to.

The course is great so far, but more practical experience using these skills is needed to go beyond learning the material but ensuring it really sticks and we are absorbing the material.

Overall, I liked this course. I felt that the information and handson experiences were good. I had trouble with clarity at times (I don't remember which part- it might have been some of the sample examples?) However, taking course has challenged me to look at things from a new perspective and really consider how to ask good, SMART, and structured questions that will help me when I begin my journey as a junior data analyst. I did not realize just how much I have learned so far, and I am grateful for this opportunity to learn. Thank you for the time and energy you spent taking time to inform (us, the online students) with all of these valuable insights, and lessons.

Sincerely,

KMc

This course spent a lot of time on very basic people skills and conflict resolution, which is indeed important for any role. However, it left me to wonder how many people really do send scathing emails to management complaining about their work or sidelining coworkers for handing over dirty data, since they included that as a response option on several questions. Basic courtesies and approachability should be taught in high school, well before pursuing a data analyst certificate. Aside from that, it touched on basic Excel functions and formulas, and framing questions to reach the main problem or objective, and keeping balance with shareholder expectations, speed and accuracy.

These courses are very informative and easy to follow along with. I like that the courses are able to be taken at your own pace and can be moved through without having to wait for a specific due date or to move through the courses with a group or class timeframe. I would prefer that the course tests could be taken on a tablet/iPad and not have to be taken on a computer. Also, in all over the videos for this course so far, the speakers "talk with their hands" but do so in an unnatural manner, moving their hand for each word they are speaking. This is very distracting. If ever these videos need to be updated and recreated, please do not have the presenters do this.

Ximena - The instructor for this course was trying to speak clearly and very slowly so that everyone can understand her, which is a great thing to do. However, when Ximena had her own "featured" video, she was talking much more naturally and I felt like this is how the course should've been.

The content of the course in terms of asking questions is great, I imagined and felt situations where some of these questions are going to be useful. However, It is really difficult to do without a dataset or without knowing what an analyst truly does so far. I think I might need to go back to this course after I've finished all of the other courses in this series.

Good course but nothing is perfect. I have found a lot of errors in the subtitles. These errors are inconsequential especially if you pay attention. Someone needs to be employed to go through this course and edit it line by line. The software and people are not perfect, so some words that were said unnecessarily get added. It would be fun if the producers poked fun at the software transcription faults and user error (I understand that an academic institution [generally] does not do this). A possible next course of action is to... fix the subtitles or to dub over the spoken words of the speaker or REDO the videos entirely. Cheers!

I'm giving this course 4 stars. The concepts taught were on point, but I find that clearer examples can be given for some key parts of the course. Some of the explanations and examples are very concise, if it were more elaborate, it can be understood better. For example, Quantitative and Qualitative data are important elements, they have been defined well but to help the learner understand the concept, the examples for each can be more effective. Same with the part about solving problems with questions. The content had to be read a few times to be able to really understand what they were talking about.

Ximena was quite detailed and calm. Although I struggled at the initial part of the course (WEEK 1 & 2). I really enjoyed the week 3 lectures, practicals and guided projects on spreadsheets, functions and formulas in spreadsheets and WEEK 4 lectures and realistic case scenerios on effective communication, conflict management, meetings, balancing stakeholders needs, clear communication and data limitations.

I learnt a lot. I am definitely going to improve my overall communication skills at work with my bosses and team members and also handle conflicts better.

Thank you. I am grateful.

Data driven decision making is an excellent course with one small minor issue: I'm working in the field of data analytics and I take part in this course to discover and learn new things and one thing that is really unrealistic here is that the course assumes that a data analyst can just go talk to a primary stakeholder and circumvent the people they directly report to. I strongly discourage anyone from just going to talk to your primary stakeholder if you encounter an issue, before talking to your manager first. Especially if the primary stakeholder is the CEO.

Learning about the framework for thinking about projects involving data analysis and the types of questions that data analysts need to consider was useful. But for myself, having endured a full business career working for multiple organizations already, there is too much emphasis on the soft skills and diplomacy required for general career success. This course is geared more towards the business novice who is starting their professional career than for someone who wants to learn the pure mechanics of working with data in any analytics environment.

I found this course a little more challenging than the first course, and am expecting the courses to become increasingly more challenging as I continue. Some of the definitions learned could have been included with the weekly glossaries to make Google's concept of open-book learning easier. I found the quizzes challenging and believe that as I continue on to the next course, that concepts have built on each other which should help me move forward. Thank you for your instruction, and I look forward to learning more.

I am really enjoying the course so far, but the one problem that I keep running into is when I play the videos from wed page they won't finish, or the video will start to jump around. The work around that I do is to download the videos. When I download the video, the video won't perform the review questions, and also doesn't mark the video as being completed. So I have to go back to the video web page and move the video to the questions and then to the end so the progress tracker will mark the video as complete.

Some of the concepts are pretty basic, but there is a lot of very useful information. It's easy to breeze past the content you already know and I appreciate that it teaches aspects of the work outside of just technical skills and training. For example this course focuses a lot on how to ask the correct questions and how to deal with communication issues. This is the only data coursework I've seen that somewhat adequately addresses these concepts that make it relevant to the job and not just the academic field.

What I liked:

The class was an excellent introduction to problem-solving and other soft skills. It emphasized the six data analysis phases, which the instructors covered in the first class (Foundations: Data, Data, Everywhere). The repetition is compatible with my learning style, along with the format of this class where I could read, listen, watch, and do hands-on training. 

What could be improved: 

The class jumped around a bit. It was relatively easy, and I finished it quickly. 

I am very grateful to have been able to take this course. My opinions are only oriented to improve it. There are many new concepts presented, which could be improved or deepened (power of data, metrics, structured thinking). It also seems to me that the exercises could be improved, especially the self-reflection ones. Some of them were not clear to me and I did not understand why I did them. Many thanks to the instructors and everyone who worked to develop this course.

The course is very helpful. The only thing that I'd like to recommend is to improve the mobile app. Sometimes, I'm required to take lessons on the phone and the mobile app isn't working well enough to let me take the test on the phone. And if they let me do so, the questions once in a way are displayed in properly such as missing a answering question to select or not showing the whole part of the question propperly.

But I do love the courses here, keep up good works!

Some of the material seemed targeted at students who have never had a job - basic communication & manners - that's not a bad thing but if you're changing careers or looking for job-specific skills, this course will feel unnecessary. Also - a couple of the grading results were subjective and (in my opinion) dependent on the situation - making the grading feel arbitrary. I can easily defend a couple of the answers I missed on the practice quizzes.