Prepare Data for Exploration

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  • Data types and structures
    • We all generate lots of data in our daily lives. In this part of the course, you’ll check out how we generate data and how analysts decide which data to collect 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 exploration.
  • Bias, credibility, privacy, ethics, and access
    • When data analysts work with data, they always check that the data is unbiased and credible. In this part of the course, you’ll learn how to identify different types of bias in data and how to ensure credibility in your data. You’ll also explore open data and the relationship between and importance of data ethics and data privacy.
  • Databases: Where data lives
    • When you’re analyzing data, you’ll access much of the data from a database. It’s where data lives. In this part of the course, you’ll learn all about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also check out metadata to discover the different types and how analysts use them.
  • Organizing and protecting your data
    • Good organization skills are a big part of most types of work, and data analytics is no different. In this part of the course, you’ll learn the best practices for organizing data and keeping it secure. You’ll also learn how analysts use file naming conventions to help them keep their work organized.
  • Optional: Engaging 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’ll explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.
  • *Course challenge*
    • Prepare for the course challenge by reviewing terms and definitions in the glossary. Then, demonstrate your knowledge of data collection, ethics and privacy, and bias during the quiz. You will also have an opportunity to apply your skill with spreadsheet and SQL functions, as well as filtering and sorting. Finally, secure and organize data with data analytics best practices.