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Master SQL for data analysis
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Master SQL for data analysis
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Master SQL for data analysis
Streaming Video

Master SQL for data analysis

2023
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Overview
Learn SQL, the most popular query language to extract, load, and manipulate data from databases. Master SQL and gain the fantastic flexibility to explore, filter, and aggregate raw data in multiple dimensions. About This Video: Learn sequential query language terminology, build databases, and write SQL syntax step by step. Create/load data into databases, schema, and tables, and analyze data with filter and search patterns. Learn about datasets and e-commerce datasets, and handle SQL queries and subqueries efficiently. In Detail: SQL is a popular language for extracting, stacking, and querying data from databases. Master SQL to explore, filter, and aggregate almost any raw data into multiple dimensions of valuable input. Level 1 teaches SQL from scratch to let you understand SQL and data analysis and is designed to jumpstart your knowledge of SQL and perform various data analysis tasks. You will learn SQL terminologies, databases, and syntax. You will create and load databases, schemas and tables, analyze data using filtering conditions and search patterns, count distinct values across dataset attributes, group rows, calculate using aggregation functions, and use aliases for columns and tables. Level 2 directly continues from topics explored in Level 1. It covers more advanced SQL tools and capabilities. You will combine data from multiple sources, break complex queries into subqueries, transform and classify data, analyze data with window functions, create views and CTEs, and explore SQL to the core. You will work on quizzes and exercises to practice and sharpen your understanding of the learning objectives. Upon completion, you will comprehensively acquire knowledge about SQL syntax, queries and subqueries, perform data analysis tasks independently, and garner thorough understanding of SQL, and use it in your data visualization and analysis. All resources are available at GitHub.
Publisher
PACKT Publishing
ISBN
1837638683, 9781837638680