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.

I truly recommend this course. It will change your mind about how you see things, and how things happen around any business or even at your own house. Data and collection of data get to conclusions.

teaches me the principle of data analysis, & it's up to me how to apply it. rather than 'copy & paste' what the previous person has done, I can make it my own based on what i want to achieve.

Excelente introducción al mundo de los datos, es bastante educativo. Las herramientas utilizadas para el aprendizaje mantienen el interés del estudiante en todo momento.

Me ha encantado el curso, lo bien preparado que lo tienen, lo accesible que es y la información que contiene, es inmejorable. Muchas gracias

Great introduction to a new subject matter with real practical examples. The self paced learning is a winning strategy

So enlightening and easy to follow and move along

Amazing !!!! I have no words. It is just amazing.

good, informative and clear explanation of basics

Successfully I have completed the first course of the Google Data Analytics Professional Certificate. What I learn from this fundamental course “Foundations: Data, Data, Everywhere”, I just share with you all.

The systematization of the analytics process was exceptionally helpful - probably the best takeaway of the entire certificate program. This course is a great intro to data analytics skill. It introduces tools such as spreadsheets and SQL. Found out why I'm always analytical about things in my personal life and the critical thinking that this provides.

I enjoyed the stories that the different instructors shared, and can feel that they are personable people. I appreciate the work put into this!It would be nice if the subsequent text included a link to the section with the information because I felt some of the answers were difficult to go back and find.

Good basic overview and introduction.

Some inconsistencies in volume level and lack of continuity between video sessions made the course difficult to listen to at times.

Because it's so basic, if you have any experience at all you will find many of the exercises--especially the writing exercises--very tedious and not particularly helpful.

The course's framing of holistic/accurate/open-minded analysis as "fairness" is confusing and could easily prove problematic in the formation of new analysts.

This course provides an interesting panorama of data analysis. I believe it to be a good starting point for those pursuing this career path. I think the course should add an interactive SQL component and possibly also an interactive spreadsheet component in which participants can see the results of queries and get automatedd feedback on whether they match intended results.

I posted a question in the discussion forums and have not received a reply. So yeah the staffs are dead. This whole course could have ended in 3 modules honestly. Like there are a bunch of fillers in this course sadly. But 70% of the course was nice to go through and learn different things and get started on the data science bandwagon.

I found the course and pace very interesting and liked the ratio of videos to readings to logs etc. However, I felt the SQL and Query section needed way more practice for beginners like me. I don't think the section covered it enough to really get a grasp of SQL.

Comprehensive introduction to the data analytics methodology. It is especially helpful for people who are starting from scratch. If you scored well enough at the quiz and know excel, feel free to jump directly to the second course.

It'll be much more beneficial to indicate why an answer is wrong instead of returning to an entire video, because sometimes it's not really clear why the answer is wrong

Everything was very well structured EXCEPT SQL (didnt understand it cuz they went from 0 to a 100 real quick).

I would like to know why my certificate does not mention my name, instead appears Coursera Learner

I already attached my coursera account to Google, that is why even if I log into the coursera system from incognito mode the Qwiklabs keep getting an error as I am logged into my personal google account. That is so frustrating. Please fix it!

Course content is very basic