ETL is a process that involves extracting data from multiple sources, transforming it to fit operational needs, and loading it into a data warehouse. It provides a method of moving data from various source systems into a data warehouse to enable complex business analysis. The ETL process consists of extraction, which gathers and cleanses raw data from source systems, transform, which prepares the data for the data warehouse through steps like validation and standardization, and load, which stores the transformed data in the data warehouse. ETL tools automate and simplify the ETL process and provide advantages like faster development, metadata management, and performance optimization.

1. Extraction
Transform
Load
Submitted By:
Rohin Rangnekar
MCA 2nd Year Afternoon

2. WHY ETL? Companies need a way to analyze their
data for critical business decisions.
Transactional Database can’t answer
complex business questions.
A data warehouse provide a common data
repository
ETL provide a method of moving data from
various source into a data warehouse.

3. ExtractionGathering the data
 Raw data that was written directly into the disk.
 Data written to flat files or relational tables from structured source systems.
 Data can be read multiple times, if needed.
Cleansing the data
 Eliminate duplicates or fragmented data.
 Exclude unwanted / unneeded information.
Transform
 Preparing the data to be housed in the data warehouse.
 Converting the extracted data:
 Using rules and lookup tables
 Combining data
 Verification/Validity checks
 Standardization

4. Load
 Storing the transformed data in the data warehouse.
 Batch/Real-time processing
 Can follow star schema and snowflake schema
Extraction Transform Load ProcessThe process
of reading
data from a
database
The process of converting data from one form to another
The process
of writing
data into the
target
database

5. Advantage of ETL Tool
 Simple, faster and cheaper development.
 Most ETL tools provide a metadata repository, synchronizing metadata from various s
ource.
 Most ETL tools deliver good performance, even for very large dataset.
 Provide impact analysis tools for any proposed schema changes.
 Have built-in connectors for all the major RDBMS systems.
 Allows reuse of the existing complex programs.
 Offer visual development environment.
 Offer build-in scheduler sequencers and documentation.
 Several ETL tools offer various performance optimization options such as parallel
processing, complex load balancing, etc.
Popular ETL Tools Company
Infosphere Datastage IBM
Oracle Warehouse Builder ORACLE
Transformation Manager ETL Solutions