Working with SQL

(upbeat music) - [Ben] A SQL stands for Structured Query Language, and it's the most universal of all programming languages, and one of the few that has a standard syntax that all databases support. This language was designed as if it were to be read as English, and over the years it has evolved into a complex and expressive language that allows you to manipulate, transform, analyze, and even update or delete data in your database. This language is supported by virtually all databases, even new or big data systems known as NoSQL databases. - [Dan] SQL is the language of tabular data. It started as the query language for relational databases, but now it's used in data analytics tools, like Apache Spark and Kafka distributed streaming platforms. So why is SQL so popular? The short answer is that it is well-suited for working with tabular data. Much of the data we use lends itself to tabular structures. Retailers track customers' data in tables. Health care companies manage patients' data with relational tables. In fact it's hard to think of an industry that can't make use of SQL and tabular data. Statistics is a broad and useful set of mathematical techniques for understanding data and making predictions. It's not surprising that relational databases have evolved to support statistics and SQL. That statistics in this course is just a sample of the mathematical tools we have available to us for analyzing data with SQL and statistics. - [Emma] When you use a business intelligence or BI reporting system to drag and drop columns into a report, the software is almost certainly building an SQL query behind the scenes which runs on the database and returns your selected data. Knowing how to use the SQL itself can make you an expert user of BI systems or help you to abandon your reporting interface all together and talk to your database directly. - [Lynn] NoSql is a set of database technologies designed to store non-relational data at large or very large scale. NoSql databases originated out of work done by Google, Facebook and Yahoo to solve Web-scale problems such as indexing the entire internet, predicting subscriber behavior or targeting Facebook adds. We'll apply knowledge to real-world scenarios so you can put your new understanding of NoSQL databases to practical use.