The Logical Data Model » Attributes: Context for your levels of data

Attributes: Context for your levels of data

After the facts are determined, the attributes must be identified. Attributes allow you to answer questions about a fact and provide a context for reporting and analyzing those facts.

For example, consider the sales figures of your company. If you were informed that your company had sales of $10,000, you can gather little useful information. To make the sales figure meaningful, you would need to know more about the source of that sales figure such as:

A time frame for the sales
Who and how many people contributed to the sales total
What products were sold from which departments
The scope of the sale, such as national, regional, local, or a single store

Attributes provide context and levels for convenient summarization and qualification of your data to help answer the type of questions listed above. They are used to answer business questions about facts at varying levels of detail. For example, if your sales data is stored at the day level, a Month attribute allows you to see the same sales data summarized at the month level.

To those familiar with SQL, attributes generally represent the non-numeric and non-aggregatable columns in database tables. These columns are used to qualify and group fact data.

For example, in the following SQL statement, the MONTH_ID column in the warehouse maps to the Month attribute in the MicroStrategy environment:

SELECT a11.MONTH_ID MONTH_ID,

max(a12.MONTH_DESC) MONTH_DESC,

sum(a11.TOT_DOLLAR_SALES) DLRSALES
FROM MNTH_CATEGORY_SLS a11
			join LU_MONTH a12
			 on (a11.MONTH_ID = a12.MONTH_ID)
WHERE a11.MONTH_ID in 

(200201,200202,200203)
GROUP BY al1.MONTH_ID

Attribute forms contain additional descriptive information about a given attribute and are discussed in terms of the logical data model in Attribute forms.

For a complete discussion about attributes, refer to The Context of Your Business Data: Attributes.