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Data Warehousing and Data Mining
notes 3. Enabled better understanding of customer behavior and customer profiles
4. Helped customer increase its market share and understand competition better
5.9 summary
l z In the process of extracting data from one source and then transforming the data and
loading it to the next layer, the whole nature of the data can change considerably.
l z It might also happen that some information is lost while transforming the data. A
reconciliation process helps to identify such loss of information.
l z One of the major reasons of information loss is loading failures or errors during loading.
l z Data reconciliation is often confused with the process of data quality testing. Even worse,
sometimes data reconciliation process is used to investigate and pin point the data issues.
l z While data reconciliation may be a part of data quality assurance, these two things are not
necessarily same.
l z Scope of data reconciliation should be limited to identify, if at all, there is any issue in the
data or not.
l z The scope should not be extended to automate the process of data investigation and pin
pointing the issues.
5.10 keywords
Data Aggregation: Data aggregation is any process in which information is gathered and
expressed in a summary form, for purposes such as statistical analysis.
Data Extraction: Extraction is the operation of extracting data from a source system for further
use in a data warehouse environment.
Data Quality: Data quality has been defined as the fraction of performance over expectancy, or
as the loss imparted to society from the time a product is shipped.
Update Propagation: Data Propagation is the distribution of data from one or more source data
warehouses to one or more local access databases, according to propagation rules.
5.11 self assessment
Choose the appropriate answers:
1. SQL stands for:
(a) Structured Query Language
(b) Structured Query League
(c) Systematic Query Language
(d) Structured Queue Language
2. PIN stands for:
(a) Permanent Identification Number
(b) Permanent Index Number
(c) Personal Identification Number
(d) Personal Index Number
102 LoveLy professionaL university