Modern Big Data Analysis with SQL Specialization
Learn essential skills for working with large-scale data using SQL. Gain expertise in distributed query engines like Hive and Impala. Prepare for the Cloudera Certified Associate (CCA) Data Analyst certification exam. Hands-on assignments included. No separate Capstone Project required.
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.
Each course in this Specialization includes a hands-on, peer-graded assignment. To earn the Specialization Certificate, you must successfully complete the hands-on, peer-graded assignment in each course. For this Specialization, there is not a separate Capstone Project like there is in some other Coursera Specializations.