... source operational systems, data extraction tools, data
transformation tools, the data dictionary definitions, and other sources all contribute to
the data warehouse metadata. Metadata management, ... navigate through the data ware-
house and any data marts.
From the outset, pay special attention to metadata for your data warehouse environ-
ment. Prepare a metadata initiativ...
... warehouse data models, source-staging area mappings, staging area-
warehouse mappings, data extraction rules, data transformation rules, data cleansing
rules, data aggregation rules, data loading and ... METADATA
197
METADATA REPOSITORY
Information Navigator
Technical Metadata
Business Metadata
Source systems data models, structures of external data sources, staging area file...
... individual transactions to change the data there. Data updates are commonplace in
an operational database; not so in a data warehouse. The data in a data warehouse is not as
volatile as the data in an ... Tools 50
1 Data Fusion 50
1 Multidimensional Analysis 51
1 Agent Technology 51
1 Syndicated Data 52
1 Data Warehousing and ERP 52
1 Data Warehousing a...
... 3-8 Integration of KM and data warehouse.
Types of Metadata
Metadata in a data warehouse fall into three major categories:
ț Operational Metadata
ț Extraction and Transformation Metadata
ț End-User ... metadata contain all of
this information about the operational data sources.
Extraction and Transformation Metadata. Extraction and transformation metada-
ta contain data about the...
... Chapter 2:
ț Source data
Production data
Internal data
Archived data
External data
ț Data staging
Data extraction
Data transformation
Data loading
ț Data storage
ț Information delivery
ț Metadata
ț ... internal and external data sources form the source data
architectural component. Source data governs the extraction of data for preparation and
storage in the dat...
... Data
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DATA
STAGING
Key Data
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DATA
STAGING
Key Data
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DATA
STAGING
Key Data
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DATA
STAGING
B
EF
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AF
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Key ... extracted data is raw data and it cannot be applied to the
data warehouse. First, all the extracted data must be made usable in the...
... poten-
tial effect of bad data. The low-priority data may be cleansed if you have any time and re-
DATA QUALITY INITIATIVE
309
DATA
QUALITY
INITIATIVES
DATA
CONSUMER
(User Dept.)
DATA
EXPERT
(User ... companies serious about data quality pull all these factors together and establish a
data quality framework. Essentially, the framework provides a basis for launching data...
... organizations gather enterprise data from the source operational systems,
move the data through a transformation and cleansing process, and store the data in data
warehouses in a form suitable for ... Prefabricated multidimensional cubes are not created beforehand and stored
in special databases. The relational data is presented as virtual multidimensional data
cubes.
364
O...
... just a couple of ex-
amples. Review all the initialization parameters and set each appropriately.
Data Arrays
What are data arrays? Suppose in a financial data mart you need to keep monthly balances
of ... suitable for low-selectivity data? Why?
9. What is data partitioning? Give two reasons why data partitioning is helpful in a
data warehousing environment.
10. What is...
... start with a large volume of data,
even a small percentage increase can result in substantial additional data.
In the first place, a data warehouse may contain too much historical data. Data ... huge amounts of data that has taken years to gather and accu-
mulate. The historical data may go back 10 or even up to 20 years. Before the data arrives
at the data warehouse, y...