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Advanced ETL Testing Online Training in USA

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Advanced ETL Testing Online Training in USA

Brittsoft Provides Advanced ETL Testing online training with best guidance.This Course is based on industry standards and vetted by top industry professionals. ETL is a process that extracts data from source systems, transforms the information into a consistent data type. Then loads the data into a single depository. ETL testing refers to the process of validating, verifying, and qualifying data while preventing duplicate records and data loss.
Free

Course Overview of Advanced ETL Testing Online Training

ETL testing is done before data is moved to production data warehouse systems.
It is also called table balancing or product reconciliation.
ETL testing is different from database testing in terms of its scope and the steps followed during this testing.
ETL testing involves the following operations
Validation of data movement from source to the target system.
Data count verification in the source and target system.
ETL testing verifies if table relations join and keys are preservers during the transformation.

Who are eligible for Advanced ETL Testing Online Training

  • Knowledge in software testing tools and testing concepts.
  • Hands-on experience of handling a database using SQL queries.
  • Have an elementary knowledge of data warehousing concepts.

Advanced ETL Testing Online Training Syllabus

Course Curriculum

Session 1

  • Introduction to ETL and DW Concepts

Session 2

Session 3

Session 4

Session 5

Session 6

Session 7

Session 8

Session 9

Session 10

Frequently asked questions (FAQ’s):

Do you conduct assignments?
Yes we do conduct assignments every week.
Do you provide a certificate at the end of the course?
Brittsoft provides you a course completion certificate at the end of your course.
Why should you take Advanced ETL Testing Training?

The scope of ETL testing will increase in the future.
   There is a demand for automated data integration with ETL testing tools
   that can produce substantial quantities of data independently without looking for human interference in real-time

 

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