As we’ve discussed, SQL lets us manage and analyze large databases. We can think of it as a reasonable balance between scalability and query flexibility:

• Some tools, like NoSQL databases, provide more scalability, but aren’t as friendly as SQL to perform analytics.
• Some other tools, like pandas or R, provide higher flexibility for data manipulation and analysis, but aren’t as scalable as SQL.

A beginner’s understanding of SQL consists of knowing the basics of how to pull data from a SQL database. This is useful for analysts who use tools like pandas and need to retrieve their data from a SQL table.

In the context of learning SQL, this Beginner level teaches the fundamentals of SQL syntax, introducing:

• The SELECT statement, which is SQL’s basic building block. SELECT is the instruction that asks SQL to retrieve data from tables.

• SQL’s basic filter, the WHERE clause. The ´WHERE´ clause lets us specify which subset of rows SQL should retrieve from a particular table by providing a condition.

• The basic functions for data processing, which include:

  • Renaming columns from certain tables with the keyword AS.
  • Obtaining metrics to summarize information from a table, such as the total sum of the values within a particular column, their average, or the number of elements.

In summary, this course will allow you to:

• Learn the basics of the SQL syntax to continue the SQL learning path. This is a step toward being able to perform analytics on large volumes of data directly in SQL.
• Know enough SQL to retrieve the data from a SQL database in order to process it elsewhere with more familiar tools like Python or R. This only works for smaller datasets, as these other languages are not as scalable as SQL.