Microsoft Office Tutorials and References
In Depth Information
For example, if (Region.East, Time.[Quarter 4], Product.Prod1) is one of your tuples, and (Region.East,
Time.[Quarter 1], Product.Prod2) is the second, then the set that comprises these two tuples looks like this:
{(Region.East, Time.[Quarter 4], Product.Prod1), (Region.East, Time.[Quarter 1], Product.Prod2)}
When you create MDX queries, it’s always good to include comments that provide sufficient
information and make logical sense. You can write single-line comments by using either “//” or “—” or multiline
comments using “/*…*/”.
Best Practices
For more about advanced MDX queries, built-in functions, and their references, consult the book Pro SQL Server 2012 BI
Solutions by randal root and Caryn Mason (apress, 2012).
Putting It All Together
Table 1-2 gives an overview of the database models and their entities, their query languages, and the tools used to
retrieve information from them.
Table 1-2. Database models
Nature of usage
Transactional (R/W)
Add, Update, Delete
Analytics (R)
Data Drilldown, Aggregation
Type of DB
OLTP
OLAP
Entities
Tables, Stored Procedures, Views, and so on
Cubes, Dimensions, Measures, and so on
Query Language(s)
T-SQL/PL-SQL
MDX
Tools
SQL Server 2005 (or higher), SSMS
SQL Server 2005 (or higher), SSMS, SSDT, SSAS
Before proceeding, let’s take a look at some more BI concepts.
The BI Foundation
Now that you understand OLAP system and cubes, let’s explore some more fundamental business intelligence (BI)
concepts and terms in this section.
Data Warehouses
A data warehouse is a combination of cubes. It is how you structure enterprise data. Data warehouses are typically
used at huge organizations for aggregating and analyzing their information.
Because cubes are integral parts of a data warehouse, it’s evident that a data warehouse comprises both relational
and disconnected databases. Data warehouses are a consolidation of many other small slices (as shown in Figure 1-10 )
that include data marts, tools, data sources, and ETL.
 
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