Big Data Analysis with SQL Specialization - PSDF

Big Data Analysis with SQL Specialization


This Specialization teaches the essential skills for working with large-scale data using SQL. Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you. Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable. To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open-source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines. This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala.

  • Distinguish operational from analytic databases, and understand how these are applied in big data
  • Understand how database and table design provides structures for working with data
  • Appreciate how differences in volume and variety of data affect your choice of an appropriate database system
  • Recognize the features and benefits of SQL dialects designed to work with big data systems for storage and analysis


Training Type




Course Duration

Approx. 3 weeks to complete Suggested 3.5 hours/week


We are aiming to train 10,000 trainees by the end of 2021

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