Organizational Understanding and Data Understanding - Data Mining for the Masses - page 16

examine the differences between databases , data warehouses , and data sets . We will also
examine some of the variations in terminology used to describe data attributes.
Although we will be examining the differences between databases, data warehouses and data sets,
we will begin by discussing what they have in common. In Figure 2-1, we see some data organized
into rows (shown here as A, B, etc.) and columns (shown here as 1, 2, etc.). In varying data
environments, these may be referred to by differing names. In a database, rows would be referred
to as tuples or records , while the columns would be referred to as fields .
Figure 2-1: Data arranged in columns and rows.
In data warehouses and data sets, rows are sometimes referred to as observations , examples or
cases , and columns are sometimes called variables or attributes. For purposes of consistency in
this topic, we will use the terminology of observations for rows and attributes for columns. It is
important to note that RapidMiner will use the term examples for rows of data, so keep this in
mind throughout the rest of the text.
A database is an organized grouping of information within a specific structure. Database
containers, such as the one pictured in Figure 2-2, are called tables in a database environment.
Most databases in use today are relational databases —they are designed using many tables which
relate to one another in a logical fashion. Relational databases generally contain dozens or even
hundreds of tables, depending upon the size of the organization.