ETL Testing – Online Training

“ETL” stands for Extract Transform Load. ETL process extracts data from Source Tables, transforms them in to the desired format …

    “ETL” stands for Extract Transform Load. ETL process extracts data from Source Tables, transforms them in to the desired format based on certain rules and finally loads them onto Target tables (Data Warehouse). There are numerous tools that help with the ETL process – Informatica, Talend, Control-M being a few notable ones.

    What does this course offer me?

    • What is a Data Warehouse and what is a Database
    • What is ETL
    • DWH Architecture and ETL Process
    • ETL Test Phases and Environment
    • Roles & responsibilities of Tester in ETL and Database Testing
    • ETL Testing Methodologies
    • Fact Table, Dimension Table, Star Schema, and Snow Flake Schema
    • Data Modeling and Data Mapping
    • Types of database uses in ETL testing
    • Relational Database and Non – Relational Database
    • Types of Data Integrity
    • Lack of data integrity and Bugs
    • Understanding Database Normalization: First, 2nd and 3rd Normal Form
    • Understanding Database De-normalization
    • Introduction to SQL and SQL Basics
    • SQL Advanced level queries for Testing
    • Testing Database Objects
    • Basic Unix Commands and Writing Commands and Usage
    • Introduction to Shell Scripting
    • Automation Testing : Approach and tools ( back-end testing)

    What is “Data Warehouse” and “Business Intelligence”?

    • “Business Intelligence”, also known as “BI” describes the process a business user to gather all its raw data from multiple sources and process it into practical information they will apply to determine effectiveness of business processes, create policy, forecast trends, analyze the market and much more.
    • “Data Warehouse” is an integral part of any effective Business Intelligence & Analysis. Data Warehousing is more than just a database-like method of storing information. Its sole purpose is to view and inspect existing data and help business users with conclusive analysis, and quicker generation of reports.

    When does a Company need Data Warehouse?

    It is time for a Company to invest into a Data Warehouse when it begins:

    • Generating too much data for Excel to handle.
    • Downloading data exports from multiple systems and combining them together in Excel.
    • Wasting too much time updating existing reports.
    • Seeing discrepancies in reports on the same data, generated by different departments.
    • Delaying business decisions while waiting for facts and answers.

    So what is the difference between “Database Testing” and “ETL Testing”?

    There is a popular misconception that “Database Testing” and “ETL or Data Warehouse Testing” are the same. The fact of the matter is they are as different as night and day.

    Database Testing involves:

    • Data from uniform sources.
    • Performing only CRUD (Create, read, update and delete) operation.
    • Normalized data (Data is organized in fields of a relational database table to minimize redundancy and dependency).
    • Data which is of smaller scale and transactional nature, i.e. OLTP (Online Transaction Processing).

    ETL Testing involves:

    • Data from different kind of data sources which are sequentially inconsistent.
    • Performing read-only (Select) operation.
    • Denormalized data (Data is optimized to increase the read performance by grouping redundant data).
    • Data which is of a larger volume and involves OLAP (Online Analytical Processing).

    Types of “ETL Testing”

    • New Data Warehouse Testing: A new Data Warehouse is built and verified from scratch. Data is extracted and loaded in the new DW from client requirements and various data sources and verified with the help of ETL tools.
    • Migration Testing: Client might be looking to replace the current ETL tool which a more efficient tool, and migration testing would help make that decision.
    • Change Request: New data is added from different sources to an existing Data Warehouse. Client also might needs to change their existing business rule or integrate a new rule.
    • Report Testing: Report generated for Business Intelligence in a Data Warehouse would be tested by validating layout, data in the report and calculation.

    Course Requirements

    • You are self-driven and motivated to learn.
    • Participation in this course requires consistently spend least 10 hours per week to your exercises
    • You can communicate fluently and professionally in written and spoken English.
    • You have access to a computer with a broadband connection, on which you’ll install a professional code/text editor

    Who is the target audience?

    • Fresh Graduates
    • Students
    • Software Testers
    • ETL Developers
    • Business Analysts
    • Anyone from the IT or non-IT field who is looking for a career in the QA field

    Future Job Profiles

    • ETL Tester
    • Test Consultant
    • Software Tester

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