I loved the course and I have learned a lot. The content is good along with the explanations in the video. However, I think there could have been more problems to use SQL and formulas and functions in the final course challenge. But, overall great experience.

Great course to start with the beginnings or basics in data analytics. Learned a lot in this course, thanks to google and coursera for this one. Data driven decision making is an art and I absolutely enjoyed being a part in this course.

I just loved attending this course. It made me very happy and discover that I know some skills that are high valued in the market nowadays. Thank you so much Coursera and Google for this opportunity!!!! 8:-)

It was a great course it really inspired me a lot to search about processes and steps to become data analyst this course is well designed to set up my journey as a data analyst and a good overview .

Very helpful and easy to understand. This course well suited for beginners and even for the intermediate ones to refresh and giving fundamental knowledge for a Data Analyst. Thank you Google!

This course was a great start to the journey of data analysis. Instructor was awesome and I could easily relate to him and enjoyed his expressive style of teaching. Strongly recommond it.

Excellent starting point, straightforward and clear information. The only thing I consider to need some polishing is the Qwiklabs part. Overall a great experience, thanks for everything!

The course was very detailed and the instructor very engaging which made the subject matter fun to learn and easy to understand.

This course gave me a good idea of what to expect out of data analysis. I'm looking forward to the other courses in this program.

A very good foundational course if you are keen on a career in data analytics. Thank you and GOD bless!

I enjoyed the course and learned a lot of basic important concepts.

so great to learn the key ascpects

GOOD COURSE FOR STARTERS

To me this course is filled with inspiration, rather than with knowledge or skills. It is focused on getting you interested in the world of data analysis, and I feel it is targeted to young graduates, not to people with even just a few years of professional experience, wanting to learn something new to advance their current careers. Many of the videos got me frustrated by the amount of pep talk, which made me feel like I am being manipulated or at least not taken seriously.

The course provides opportunities to test yourself, to repeat and reflect on the material, which is helpful. I missed more opportunities for practical excercises.

Overall I think it may be good for people who are hesitating and do not know, if data analysis is something for them. It is a waste of time, for the ones who are actually looking for some practical knowledge.

Some of the questions were odd or I believe them to be incorrect. One of the final exam questions used 04000 as a zip code but the leading zero should probably be requested as text for '04000' in the where statement but this was counted as incorrect. Question 6 in one of the weeks asked what SELECT * did. it says it selects all of the data from the table but that isn't quite correct, it selects all features of the data but a where clause would limit the data as well, so saying select * selects all of the data is misleading.

One day of material spread over a suggested 5 weeks. Most of the material can be cut or moved to another course about general computer and professions skills. Is it a coincidence that they offer 14-day free trial but don't teach anything for the first 5 weeks? Finally, parts of the course seem politically motivated, like classifying all data a "fact". Instead, they should focus on teaching the material and leave their personal politics at home.

Well presented but often a game of guess the appropriate corporate jargon than come to grips with concepts.

I would not recommend this course to anyone. This course is designed for a specific type of person, with a specific type of rote memorization and recitation learning style. By taking this course, you can pretend to understand data by learning the lingo and following the steps. A bit horrifying to see, but illuminating as to how the world has gone so wrong. Honest review from a real person with decades of expert hands-on real-world professional data experience in the manufacturing industry.

I would say for absolute begineer its fine but for begineer please just go straight why we are using SQL, how to use SQL python power BI tableu uses then go for programing

Overall, I found the "Foundations: Data, Data, Everywhere" Google Coursera course to be an excellent learning resource for anyone interested in understanding the fundamentals of working with data. Here are my feedback and suggestions:

1. Comprehensive Content: The course provides a comprehensive overview of various data-related concepts, including data types, data storage, data cleaning, data analysis, and data visualization. The content is well-structured, with clear explanations and examples, making it easy to grasp even for beginners.

2. Practical Approach: I appreciate the emphasis on hands-on exercises and practical applications throughout the course. The use of real-world datasets and the integration of Google tools like Google Sheets and Google Data Studio were particularly valuable in reinforcing the concepts learned and bridging the gap between theory and practice.

3. Engaging Instructors: The instructors were knowledgeable and engaging, delivering the course material in a clear and engaging manner. They demonstrated a good balance between providing theoretical explanations and practical demonstrations, making the learning experience enjoyable.

4. Well-Designed Assignments: The assignments were well-designed, allowing learners to apply their knowledge and skills to real-world scenarios. The feedback provided by the instructors on the assignments was helpful in identifying areas for improvement and reinforcing learning.

5. Additional Resources: The course provided additional resources, such as supplementary readings and external references, which were valuable for those who wanted to explore the topics further. These resources complemented the course material and enriched the learning experience.

6. Course Duration: The course was well-paced, and the duration was appropriate for covering the foundational concepts of data. However, in some instances, certain topics could have been expanded upon to provide a more in-depth understanding.

7. Community and Discussion Forums: The course could benefit from a more active and engaged community and discussion forums. Encouraging learners to interact and share their insights or challenges could enhance the collaborative learning experience and provide opportunities for peer-to-peer learning.

8. Practical Examples: While the course included practical examples, incorporating more diverse and industry-specific use cases would further enhance the course's relevance and applicability to different domains and professional settings.

9. Certification: Offering a certification option upon course completion would be beneficial for learners who want to showcase their newly acquired skills and knowledge to potential employers or clients.

Overall, "Foundations: Data, Data, Everywhere" is a highly informative and practical course for beginners seeking to develop a solid foundation in data-related concepts. With a few minor enhancements, such as expanding certain topics and fostering a more interactive learning community, this course has the potential to become even more impactful and valuable to learners.

I had the pleasure of working with [Data Analyst's Name] as a data analyst, and I can confidently say that they are an exceptional professional in their field. Their expertise and dedication to their work have greatly contributed to the success of our projects. I would like to share my review of their performance as a data analyst.

First and foremost, [Data Analyst's Name] has a deep understanding of the data analysis process. From asking the right questions to delivering actionable insights, they consistently demonstrate a strong grasp of the entire data analysis workflow. Their ability to define problems, collect and clean data, perform insightful analysis, and present findings in a clear and concise manner is truly commendable.

One of the key strengths of [Data Analyst's Name] is their meticulous attention to detail. They have a keen eye for identifying errors, inconsistencies, and outliers in the data, ensuring the accuracy and reliability of the analysis. Their commitment to data quality and their proactive approach in addressing data issues make them a valuable asset to any team.

Additionally, [Data Analyst's Name] possesses excellent technical skills. They are proficient in various data analysis tools and techniques, enabling them to efficiently process and analyze complex datasets. Their ability to utilize advanced statistical methods, data visualization tools, and programming languages greatly enhances their ability to extract meaningful insights from the data.

Furthermore, [Data Analyst's Name] is a great collaborator and communicator. They actively engage with stakeholders and subject-matter experts, seeking their input and feedback to ensure that the analysis aligns with the business objectives. Their strong interpersonal skills and ability to translate technical concepts into understandable language make them effective in presenting complex findings to both technical and non-technical audiences.

Lastly, [Data Analyst's Name] consistently demonstrates a growth mindset and a passion for learning. They stay up to date with the latest advancements in the field of data analysis, continuously expanding their knowledge and skills. Their curiosity and eagerness to explore new approaches and techniques contribute to their ability to tackle complex problems and deliver innovative solutions.

Data analysis plays a crucial role in Google's programs, enabling them to derive valuable insights and make data-driven decisions. With the vast amount of data generated by Google's platforms and services, data analysis helps uncover patterns, trends, and correlations to improve user experience and enhance their products. By analyzing user behavior, search patterns, and ad performance, Google can optimize its algorithms, personalize search results, and deliver targeted advertisements to users.

Google utilizes various techniques and tools for data analysis, including statistical analysis, machine learning, and data visualization. These approaches enable them to process and interpret complex data sets, extract meaningful information, and identify areas for improvement. Through data analysis, Google can identify user preferences, understand market trends, and refine their products and services to meet customer needs.

Furthermore, data analysis at Google involves not only quantitative analysis but also qualitative insights. User feedback, surveys, and sentiment analysis provide valuable qualitative data that complements the quantitative data analysis. This holistic approach helps Google gain a comprehensive understanding of user needs and preferences.

Overall, data analysis is an integral part of Google's operations, driving innovation, and improving their services. By leveraging data insights, Google continues to enhance its products, deliver personalized experiences, and shape the future of technology.

As someone who is already a data analyst and wants to go back to learn the basics (I learned data analysis as a necessity of my work, not intentionally), I found this course highly useful. It can be a bit repetitive at times, but it does not take that long to get through all the course content. In contrast, I value being drilled repeatedly on all the steps, especially on the 'thinking '-related ones. I think it is very valuable to be reminded to always take a step back and consider the data and steps from different angles. Those that just want to get to the technical bit will probably not find this course as useful though.

Everything you need to know about the data, its all here. From basic level to an advanced level, how to see data as data and what the steps involved in the data analysis process, have been explained with proper understanding.

It was a super intro to the field of data analysis! There were many questions I had to solve myself in my head, and now I am more confident about what I want. At the same time, it motivates me to continue.