Is the Google Data Analytics Certificate for you and is it worth the time?

I recently completed the certification and personally feel that it was totally worth the time. The certificate not only strengthened my analytical and technical skill-sets but also helped me build a good portfolio by providing knowledge and resources to excel my career. In my opinion, this course can be taken by anyone trying to get into the field of analytics despite having no technical background.

Remember that one subject which we were not confident about in school but eventually ended up loving just because of the good teacher? This course was that good fun teacher for me.

I had applied for financial aid in every single course and fortunately received it in 15 days. After receiving the aid, the ideal time to complete this course is about 8 to 10 months but due to my technical background and pre-existing knowledge, I completed it in 3 months (15 days for creating a case study and a portfolio). So, if you are already familiar with the profession you might be able to complete the course way faster than expected.

The certification is divided into 8 sub-courses as shown in the figure below. And each course takes you one step further towards the journey of conducting analysis and becoming an analyst. Ask, Prepare, Process, Analyse, Act and Share are considered as the phases of creating a data analytics' project effectively in this course. These are explained thoroughly in each course with the help of videos, links, assignments and e-materials.

1. Foundations: Data, Data, Everywhere: The first course introduces the you to the scope of data analysis and also to it's important six phases. This course will also familiarises you with all the software and languages taught throughout the certification.

2. Ask Questions to Make Data-Driven Decisions: As the name suggests, this course teaches how to ask effective and right questions about the goals, data and data set. It also teaches effective way of discussing and communicating with the stakeholders regarding the goal.

3. Prepare Data for Exploration: In this course, information about what type of data can be collected and how to ensure data integrity, by avoiding bias and unreliable data. It also teaches about the importance of data ethics and privacy. Furthermore, it familiarises with the concept of filtering, sorting, organising and securing the data frames.

4. Process Data from Dirty to Clean: It teaches sample size determination, SQL queries for the cleaning, processing and transforming the data. Moreover, documenting results, and resume preparation.

5. Analyse Data to Answer Questions: The course includes organising, sorting, converting and formatting, combining multiple datasets in spreadsheet and SQL. Additionally, functions and features like VLOOKUP and pivot table in spreadsheet, JOINS, COUNT, COUNT DISTINCT in SQL are explained for data aggregation and validation.

6. Share Data through the Art of Visualisation: The course has modules that help students understand storytelling and communicating data insights via visualisation. It covers designing, exploring and sharing data in Tableau. Here is one of the visualisation that I created, which shows the effect of GDP on Happiness score of people around the globe: https://public.tableau.com/views/MyGooglecertiWorldHappinessData/Sheet2?:language=en-US&:display_count=n&:origin=viz_share_link . The course also helps to develop impressive presentation skills.

7. Data Analysis with R Programming: Learning an efficient language like R is important to handle large amount of data easily. Hence this course teaches the basics of R, along with that it helps to explore packages like tidyverse and ggplot2 for data processing and data visualisation. Besides that, exploring aesthetics, annotation and saving visualisations with developing documentation and reports using R Markdown.

8. Google Data Analysis Capstone: Complete a Case Study: In this course, two sample cases are given and you are suppose to do one from either.

I created the Cyclistic bike-share analysis (step by step) as a part of my case study, here a link for reference: https://www.kaggle.com/mahima5598/cyclistic-bike-share-analysis-step-by-step .

The course helps to create a portfolio, cracking the interview and sharing the case study work with recruiters.

I hope this article was useful to you and for any further queries you can contact me via LinkedIn : https://www.linkedin.com/in/mahima-chhagani/ .

If you like my work and have any freelance projects please feel free to contact me.