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ETL Testing Training


The data in a Data Warehouse framework is loaded with an ETL tool. As the name proposes, it plays out the underneath three tasks. It separates the information from our value-based system, which can be Microsoft, Oracle, or some other relational databases. It Transforms the data by performing the information purging tasks, and after that Stacking the information into the OLAP information stockroom. Extraction includes extracting the data from different heterogeneous information sources.

We can likewise separate the information from level documents, for example, spreadsheets and CSV records with the assistance of an ETL instrument and after that stacking it into an OLAP information distribution center for information examination and announcing.

An ETL tool is utilized for extracting the data from a few information sources, in change the information, and in stacking the information into a DW framework. Information change includes quite a bit of information remedy and purifying of information, expelling undesirable and off base information, inadequate information development, and settling information blunders.

However a Business Intelligence instrument is utilized as a part of producing the intelligent and impromptu reports for all end-clients, dashboard for senior administration and information perceptions for month to month, quarterly, and yearly executive gatherings.


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Extraction includes extracting the data from different heterogeneous information sources. It is in fact done by executing the booked occupations in off-business hours like running employments around evening time or throughout the end of the week. Change includes in changing the information into a reasonable configuration which can be effortlessly stacked into a Data Warehouse system.Here, Data change includes applying computations, making joins, and characterizing essential ,remote keys onto the information. For assume, on the off chance that we need certain % of aggregate income which is absent in database, we will apply that % equation in change and stacking the information. So also, on the off chance that we have the main name and the last name of our clients in a few segments, at that point we can apply an added task before stacking the information. There are Some situations where the information doesn’t require any change; those sort of information is known as immediate move or go through information.

Information quality is the way to the achievement of organizations. Awful information prompts erroneous data that could bring about incredible misfortune; this thus could conceivably prompt disappointment of the business. With a specific end goal to sidestep it, information should be handled and changed into quality data, and thus be accounted for to the perfect individuals at the opportune time. Put just, great information is useful in giving knowledge. Organizations, when equipped with this, can enhance the everyday choices they make. This isn’t only for administration; it applies to each level starting from the earliest stage the best. Be that as it may, information is once in a while helpful in its crude state; it must be prepared and exhibited in a way that works in the individual level, with the goal that it can be used properly.

Hye Infotech provides the best training on ETL Testing Training in chennai. We arrange classes based on student feasible timings, to take online or classroom trainings in chennai. We are the Best ETL Testing Training Institute in Chennai as far as ETL Testing syllabus CodedUI .

Course Objective

  • Data Ware Housing Concepts
  • What is Data Warehouse?
  • Need of Data Warehouse
  • Introduction to OLTP, ETL and OLAP Systems
  • Difference between OLTP and OLAP
  • Data Warehouse Architecture
  • Data Marts
  • ODS [Operational Data Store
  • Dimensional Modelling
  • Difference between relation and dimensional modelling
  • Star Schema and Snowflake Schema
  • What is fact table
  • What is Dimension table
  • Normalization and De-Normalization
  • ETL Testing
  • ETL architecture.
  • What is ETL and importance of ETL testing
  • Describe DWH ETL Testing is different from the Application Testing
  • Explain SDLC/STLC in the ETL Projects
  • Challenges in DWH ETL Testing compare to other testing
  • Incompatible and duplicate data.
  • Explain Loss of data during ETL process.
  • Explain the Testers have no privileges to execute ETL jobs by their own.
  • Volume and complexity of data is very huge.
  • Explain Fault in business process and procedures.
  • Explain the concept of Trouble acquiring and building test data.
  • Explain ETL Testing Work flow activities involved
  • Analyze and interpret business requirements/ workflows to Create
  • estimations
  • Approve requirements and prepare the Test plan for the system testing
  • Explain how to do Prepare the test cases with the help of design documents provided by the
  • developer team
  • Explain how to do Execute system testing and integration testing
  • Create quality documentations Practices
  • Explain how to detect the bugs in the ETL testing
  • Explain how to report the bugs in the ETL testing
  • How to co-ordinate with developer team for resolving the defects
  • Types of ETL Testing
  • Data completeness.
  • Data transformation.
  • Data quality.
  • Performance and scalability.
  • Integration testing.
  • User-acceptance testing.
  • SQL Queries for ETL Testing
  • Incremental load testing
  • Explain Initial Load / Full load testing
  • Different ETL tools available in the market
  • Informatica
  • Ab Initio
  • IBM Data stage
  • Power Center Components
  • Designer
  • Repository Manager
  • Workflow Manager
  • Workflow Monitor
  • Power Center Admin Console
  • Informatica Concepts and Overview
  • Informatica Architecture.
  • Sources
  • Working with relational Sources
  • Working with Flat Files
  • Targets
  • Working with Relational Targets
  • Working with Flat file Targets
  • Transformations – Active and Passive Transformations
  • Expression
  • Lookup –Different types of lookup Caches
  • Sequence Generator
  • Filter
  • Joiner
  • Sorter
  • Rank
  • Router
  • Aggregator
  • Source Qualifer
  • Update Strategy
  • Normalizer
  • Union
  • Stored Procedure
  • Slowly Changing Dimension
  • SCD Type1
  • SCD Type2 — Date, Flag and Version
  • SCD Type3
  • Workflow Manger
  • Creating Reusable tasks
  • Workflows, Worklets & Sessions
  • Tasks
  • Session
  • Decision task
  • Control Task
  • Event wait task
  • Timer task
  • Monitoring workflows and debugging errors
  • Indirect Loading
  • Constraint based load ordering
  • Target Load plan
  • Worklet ,Mapplet ,Resuable transformation
  • Describe the Migration XML migration and Folder Copy
  • Scheduling Workflow
  • Parameter and variables
  • XML Source, Target and Transformations
  • Performance Tuning
  • Pipeline Partition
  • Dynamic Partition
  • Pushdown optimization
  • Preparation of Test Cases
  • Executing Test case
  • Preparing Sample data
  • Data validation in Source and target
  • Load and performance testing
  • Unit testing Procedures.
  • Error handling procedures.

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