Google Data Analytics Professional Certificate Review

 Data analysis is almost the same as data science. Still, it deals less with machine learning and artificial intelligence and focuses more on generating insight into the company data by connecting patterns and trends with the company goal. The concept of data analysis is not actually new, and people are using this science hundred of years ago, but the concept becomes famous when computers come to life in the last decade.

Data analytics helps marketers and companies understand their customer’s behavior, so they can decide what’s good offers to drive to them and transform the education, healthcare industry, and many more, to name a few. Learning data science is not that hard since you will not understand many programming languages or deal with artificial intelligence.

Hence, if you plan to have these skills in under six months, you should probably take this program called Google Data Analytics Professional Certificate offered by Google through the Coursera platform.

1. The Instructors Review

This specialization offers by an initiative called Grow With Google, which last collaborates with different schools, universities, and organizations to launch courses that teach people digital skills such as programming, marketing, data analysis, and more. They have gained millions of students worldwide since 2017, which is the year this initiative has come to live.

2. Course Content

2.1. Foundations: Data, Data, Everywhere

This first section will teach you how data analysis uses data analytics to make decisions for their companies and how analytical thinking can drive decision-making. Later you will learn about the data phases and tools used by data analytics and exploring some of the tools used by data analytics, such as SQL and spreadsheets. Finally, learn the specific job that these people do for their businesses.

2.2. Ask Questions to Make Data-Driven Decisions

Before you analyze your data, you have to ask some questions that you have to answer by analyzing your data to learn the common analysis challenges and how to address them. Next, you will explore all kinds of data you will face during your journey in the data analysis and share this through reports and dashboards and explore how data analysis uses spreadsheets in their daily routine.

2.3. Prepare Data for Exploration

You will start by learning how people generate their data and how you, as a data analyst, will decide which data to collect for your analysis. You will also learn how to identify the different bases in your data and extract data from the database. Finally, you will learn how the organization keeps the data safe and secure.

2.4. Process Data from Dirty to Clean

You will learn why data integrity is so important for successful decision-making and discovering the different data structures. Before you start analyzing data, you have to clean it first, so this section will teach you the different tools used to clean the data, such as using SQL language. Finally, you will find out the process of verifying and reporting data cleaning.

2.5. Analyze Data to Answer Questions

You will begin by understanding the importance of organizing the data and how to achieve this using spreadsheet and SQL language. Next, you will also learn how to convert and format your data using SQL language. Later, you will see how to combine data from multiple database tables and perform data calculations using SQL and spreadsheets.

2.6. Share Data Through the Art of Visualization

Before you start making visualization of your data, you first learn the key concepts like design thinking that play an important role in data visualization. Also, you will start exploring Tableau for data visualization and make some simple visualization and learn how to develop presentations and slideshows.

2.7. Data Analysis with R Programming

Starting this section by discovering the R programming language that is used for data analysis and how to use its IDE called R studio. Next, you will start learning the concepts of the R language and how to use its functions and also apply these functions to data for analysis purposes. Later, you will gain some knowledge of data visualization using the R language.

2.8. Google Data Analytics Capstone

This last section will allow you to showcase your skills to your employee after completing this specialization by choosing an analytics-based scenario and asking questions about the problem you are trying to solve, preparing the data, analyzing them, and visualizing the final result.

Conclusion

Data analysis is one of the best skills to have if you will be a data scientist or even going to create your own company since this will help you understand your market size and however you are going to solve this problem.