What is ETL?
Ø The
process of updating the data warehouse
Ø ETL
is the automated and auditable data
acquisition process from source system that involves one or more sub
processes of data extraction, data transportation, data transformation, data
consolidation, data integration, data loading and data cleaning.
Need for ETL
Ø The
process of ETL is required so that data from different heterogeneous sources
can be combined and brought into one common source.
Ø The
Advantage of having the process of ETL is that, as data from different sources
can be brought together, highly complex and user friendly reports can be
generated for decision making
----------------------------------------------------------------------------------------------
Ø Data
stored in different formats in different types of databases.
Ø Some
data sources might be archives while others may be active operational systems
Ø Data
extraction and cleansing - time-consuming and difficult
Ø Aggregation
of data
What ETL is Not ?
·
Data warehouses are not OLTP systems
Duplication of
calculations in Source system & the
data warehouse should not be attempted, as in future the process in the
source system can change that will result in asynchronous data.
Feature of ETL Tools
Ø Support
data extraction, cleansing, aggregation, reorganization, transformation, and
load operations
Ø Generate
and maintain centralized metadata
Ø Filter
data, convert codes, calculate derived values, map source data fields to target
data fields
Ø Automatic
generation of ETL programs
Ø Closely
integrated with RDBMS
Ø High
speed loading of target data warehouses using Engine-driven ETL Tools
Advantages of using ETL Tools
Ø GUI based design of jobs – ease of
development and maintenance
Ø Generation of directly executable
code
Ø Engine driven technology is fast,
efficient and multithreaded
Ø In-memory data streaming for
high-speed data processing
Ø Products
are easy to learn and require less training
Ø Automatic generation and maintenance
of open, extensible metadata
Ø Support
for multiple data formats and platforms
Ø Large number of vendor supplied data
transformation objects
Meta Data
Ø Data
about data
Ø Needed
by both information technology personnel and users
Ø IT
personnel need to know data sources and targets; database, table and column
names; refresh schedules; data usage measures; etc.
Ø Users
need to know entity/attribute definitions; reports/query tools available;
report distribution information; help desk contact information, etc.
Very informative blog. Got more information about this technology.
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