Dear teachers, These’re a couple of obstacles I found along the way: 1. In reference to the syntax symbols, I find it very difficult to know before hand when I have to introduce one between ‘___’   or “___”. Would you be clearer on that explanation? 2. Optional: upload the store transactions dataset to BigQuery: I could not cut and paste Step 11, for some reason (I tried several times). 3. Why must some functions be written in parentheses and some other not? DISTINCT, for example, doesn’t have parentheses, while CAST does. Could you please explain those basic concepts of the SQL syntax?

4. In one of the videos, “Documenting results and the cleaning process”, you jump from Pivot Tables and other spreadsheet features like Find and Replace, to Big Query without telling, which makes it difficult to follow along. I'm doing my best, but sometimes, especially in reference to the SQL syntax learning, I'm not achieving my goals, and feel very frustrated.

several practical exercices don't actually bring the expected results. I struggled more with using bigquery than i spent time actually learning SQL. I think the most troublesome part was creating tables (creating datasets was not a problem) : there was always a problem and it took me a long time to solve most of it (it's kind of okay now). I'll probably have to find more information somewhere else to catch up. The teacher is good and so is the pace but the practice is not as efficient as the one I had with the spreadsheets. I may also add that it would be great in the future to allow Coursera students to get access to some functions in the sandbox like updating or deleting in SQL, just so we get a chance to try it. To summarize : good teacher, good content but BigQuery is definitely not as user-friendly as R.

This course is structured poorly. More reading materials are needed for SQL. Also, content and materials for inidviduals with no prior experience in progrmaing are necessary, because the right foundation is key for proper understanding and mastering of whatever is taught.

another consideration is the stagerred and overlapping topics among different courses is really confusing.

It is much better to make courses more especialized. For example, one for basics, one for spreadsheets, one for SQL, one for CV and findng the right job instead of talking a little about each topic in each course, which is really impractical and confusing if not provoking.

After reviewing various resume best practices, I found that highlighting quantifiable achievements is key to making a resume stand out. For example, instead of just listing tasks, emphasizing how those tasks led to measurable improvements or outcomes can provide clear evidence of your impact. This can include numbers like increased efficiency, revenue growth, or improved customer satisfaction. For instance, instead of saying "Managed data analysis," I would say "Managed data analysis that led to a 20% reduction in reporting time."

Overall, not too bad. It covers a lot of data cleaning principles, but BigQuery setup can be tedious, and there's some confusion about the free account descriptions. They also crank up the SQL learning curve at times from beginner to advanced, but I can see why they do it. SQL students returning to this form of work could breeze through it, but newer students may struggle a bit like I did. The principles discussed are all still very informative, interesting and important. So stay strong, dive in, absorb what you can.

I wish they seprated the resume and job search topics from cleaning up data. they were drastically different but very useful and needed. I also wish there was a little more details about the differenece of not enough data and using little data. The final quiz questions were harder to answer because they seemed similar, but the outcomes were possibley different.

I learned more from this course than the others. It was a good course and covered what I need to learn with lots of practice opportunities. So I liked it! While this course had the most important content of any so far, it was not well laid out. I flagged some lessons and gave feedback. You might get some feedback from people as they go through it.

Thanks!

I learned everything I needed to know in this module in more from using Excel for fifteen minutes and watching one linkedin course. This module lacks in substance and material, and is missing a module test. I'm on module 4 of 6, which means two modules have been left completely untouched, and I've already been awarded the certificate for completion?

There was a lot repeating and redundancy in the class. Also, several of the quizzes didn't test for relevant or important knowledge. They tested for items that never showed up in the class, showed up later in the class (and thus students could never have been expected to know that yet), or tested more about useless jargon than important concepts.

this is a great course, i'm enjoying learning data analytics and hopefully the near future i'll be able to work as an entry level data analysis. i just with the course had real time experts to help students navigate some on the SQL probelems. that would be a benefit for us that aren't famaliar with data analytics, SQL, Kaggle etc.,

The course was well presented overall. However, there were a few places where I felt lost. Most of the SQL commands presented I could not run in the BigQuery Sandbox. After upgrading to a "trial account" I was able to perform the commands without issue. I think this should be mentioned in the videos.

It's an OK course. I learned a few tricks in spreadsheets, and heard great tips from experts in the field. However, I didn't really enjoy setting up BigQuery account. It felt sometimes that the lecturer isn't using the same version, and just setting up an account wasn't so smooth.

Week 3, 'Transforming Data' first (Optional) exercise Reading: Upload the store transactions dataset into BigQuery.

This doesn't work. Error messages. Unable to parse data around Date and Time. Tried three times.

I suggest you fix the bug and adjust the material.

The process data from dirty to clean was good but the last piece re going through the resume and interview process was wasteful for me. I've been working since I was 16 and just retired. Maybe that should be placed somewhere else and optional.

Week 3 was amazing - a lot of new skills in SQL. Everything else was completely useless - I have seen no point in going through tones of definitions and passed the test even without reading the materials.

I appreciate the positive gained by Google opportunities, but if the full package including the videos, will be granted to a learner, the course utility would have been better.

I would have liked if this course utilized the side by side demo, I think that hands on experience but being guided through the process would have been a lot more helpful .

SQL training needs to improve, a lot of the students do not have experience, and the free version of google is extremely limited, so it does not allow to properly learn.

Regarding SQL I found resources from another website straighter forward and easier to learn like with SQLite. And explanations are good but feels too much stretched

The course on the whole was good but I'm concerned about SQL. I don't feel confident that I learned what was necessary to equip me with the necessary SQL skills.

Very basic teaching, it was too much theory about stuff which doesn't make me better at my Job as a data analyst, should've been more hands-on on SQL spreadsheet

Teacher only used Google Sheets with examples and projects which was not helpful since I use MS Excel for all my work so I was not able to transfer the skills.

Some nice bits and pieces but the sections on CV writing distracted from the main focus of the course. Would be better as something completely separate.

The quizzes should be a more hands-on experience. More room for critical thinking and putting it into practice. Less about regurgitating terminology.

I would like to learn about the functions and tools of spreadsheets, SQL, and Tabulea. This course is a kind of introduction to the main concepts.