Database Reference
In-Depth Information
2
Introduction to Structured
Query Language
●
To understand the use of extracted data sets in
business intelligence (BI) systems
●
To understand the use of ad-hoc queries in
business intelligence (BI) systems
●
To understand the history and significance of
Structured Query Language (SQL)
●
To understand the SQL SELECT/FROM/WHERE
framework as the basis for database queries
●
To create SQL queries to retrieve data from a single
table
●
To create SQL queries that use the SQL SELECT, FROM,
WHERE, ORDER BY, GROUP BY, and HAVING clauses
●
To create SQL queries that use the SQL DISTINCT,
AND, OR, NOT, BETWEEN, LIKE, and IN keywords
●
To create SQL queries that use the SQL built-in functions
of SUM, COUNT, MIN, MAX, and AVG with and without
the SQL GROUP BY clause
●
To create SQL queries that retrieve data from a single
table while restricting the data based upon data in
another table (subquery)
●
To create SQL queries that retrieve data from multiple
tables using the SQL join and JOIN ON operations
●
To create SQL queries that retrieve data from multiple
tables using the SQL OUTER JOIN operation
In today's
business environment, users
typically use data stored in databases to pro-
duce information that can help them make business
decisions. In Chapter 12, we will take an in-depth look at
business intelligence (BI) systems
, which are information systems used
to support management decisions by producing information for assess-
ment, analysis, planning, and control. In this chapter, we will see how BI
systems users use
ad-hoc queries
, which are essentially questions that can
be answered using database data. For example, in English an ad-hoc query
would be “How many customers in Portland, Oregon, bought our green
baseball cap?” These queries are called
ad-hoc
because they are created
by the user as needed, rather than programmed into an application.
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