Get a comprehensive overview of SQL and Relational Databases 101
Distributed Computing with Spark SQL
2.5
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This course is all about big data and distributed computing using Apache Spark. It is designed for students with SQL experience who want to take the next step on their data journey. Through four modules, students will gain a thorough understanding of the Spark architecture, queries within Spark, common ways to optimize Spark SQL, and how to build reliable data pipelines. They will also learn about storage vs. compute, caching, partitions, and troubleshooting performance issues via the Spark UI. Additionally, students will explore new features in Apache Spark 3.x such as Adaptive Query Execution, connecting to databases, schemas and data types, file formats, and writing reliable data. Finally, they will learn about data lakes, data warehouses, and lakehouses, and build production grade data pipelines by combining Spark with the open-source project Delta Lake. By the end of this course, students will have honed their SQL and distributed computing skills to become more adept at advanced analysis.
SQL for Data Science
2.5
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This course, SQL for Data Science, is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will learn how to retrieve and work with data, and use SQL to select data from tables, create new tables, filter and pare down results, combine data, and use case statements. You will also discuss topics on data governance and profiling, and practice using real-world programming assignments. By the end of this course, you will be able to interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes.
Introduction to Transact SQL
4.5
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Explore the essentials of Introduction to Transact SQL
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