Arquitectura de Bus

1. DATA WAREHOUSING
Multi Dimensional
Data Modeling.
DW Bus architecture and matrix

2. 2

3.  Obviously, building the enterprise’s data
warehouse in one step is too daunting, yet
building it as isolated pieces defeats the
overriding goal of consistency.
 For long-term data warehouse success, we
need to use an architected, incremental
approach to build the enterprise’s warehouse.
 The approach we advocate is the data
warehouse bus architecture.
3

4.  By defining a standard bus
interface for the data
warehouse environment,
separate data marts can be
implemented by different
groups at different times.
 The separate data marts
can be plugged together
and usefully coexist if they
adhere to the standard
4

5.  During the limited duration architecture phase, the
team designs a master suite of standardized
dimensions and facts that have uniform
interpretation across the enterprise. This establishes
the data architecture framework
5

6.  The rows of the bus matrix
correspond to data marts.
 You should create separate
matrix rows if the sources
are different, the
processes are different, or
if the matrix row
represents more than
what can reasonably be
tackled in a single
implementation iteration.
6

7.  Common dimensions for different processes
should be the same.
 A dimension that has exactly the same meaning
and content when being referred from different
fact tables.
 Where attributes apply, they should mean the
same thing.
 Roll-up dimensions conform to the base-level
atomic dimension if they are a strict subset of that
atomic dimension. (granularity)
7

8. 8

9.  Revenue, profit, standard prices, standard
costs, measures of quality, measures of
customer satisfaction, and other key
performance indicators (KPIs) are facts that
must be conformed.
9

10.  The Data Warehouse Toolkit.Second
Edition.The Complete Guide to Dimensional
Modeling.Ralph Kimball.Margy Ross
10