Prepare Data for Exploration

This is the third course in the Google Data Analytics Certificate. As you continue to build on your understanding of the topics from the first two courses, you’ll be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives, and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, learners will: - Find out how analysts decide what data to collect for analysis. - Learn about structured and unstructured data, data types, and data formats. - Discover how to identify different types of bias in data to help ensure data credibility. - Explore how analysts use spreadsheets and SQL within databases and data sets. - Examine open data and the relationship between, and importance of, data ethics and data privacy. - Gain an understanding of how to access databases and extract, filter, and sort the data they contain. - Learn best practices for organizing data and keeping it secure.

• Data types and structures
• A massive amount of data is generated every single day. In this part of the course, you will discover how this data is generated and how analysts decide which data to use for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for analysis.
• Data responsibility
• Before you work with data, you must confirm that it is unbiased and credible. After all, if you start your analysis with unreliable data, you won’t be able to trust your results. In this part of the course, you will learn to identify bias in data and to ensure your data is credible. You’ll also explore open data and the importance of data ethics and data privacy.
• Database essentials
• When you analyze large datasets, you’ll access much of the data from a database. In this part of the course, you will learn about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also explore metadata to discover its many facets and how analysts use it to better understand their data.
• Organize and protect data
• Good organizational skills are a big part of most types of work, especially data analytics. In this part of the course, you will learn best practices for organizing data and keeping it secure. You’ll also understand how analysts use file naming conventions to help them keep their work organized.
• Engage in the data community
• Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you will explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.