ETL Testing Training
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Our ETL Testing Course is Extract, transform, Load (ETL) process of integration that merges data from different data source platforms into a single unit of data storage that can later be loaded in data warehouses. ETL basically refers to, the “Extraction of data from different applications” developed & supported by different vendors, managed & operated by different persons hosted on different technologies. Our extensive training is inclusive of the core concepts of ETL like Joining and Deduplication of data, filtering and sorting the data using specific attributes, Transposing data, making business calculations, etc. Enroll now and get certified in it.
ETL Testing Training Course Syllabus
✔ Why Data Warehouse
✔ What is Data Warehouse?
✔ OLTP VS OLAP
✔ Data Warehouse Architecture
✔ Importance of Staging
✔ Dimension Modeling
✔ Type of dimensions
✔ Surrogate Keys
✔ WHERE, Group By, Having
✔ Except, UNION, UNION ALL
✔ Rank, Row_Number functions
✔ String functions
✔ Date functions
✔ Practices queries on SQL SERVER 2008 R2
✔ QA roles and responsibilities in ETL Testing
✔ What is mapping document (Transformation, cleansing, etc…)
✔ Data flow from source to staging to target
✔ Test Scenarios
✔ Test Cases writing
✔ Source to stage
✔ Stage to target
✔ Test Execution
✔ Initial and Incremental load testing
✔ Level of Testing
✔ Functional Testing
✔ ETL jobs/scheduled testing
✔ Defects in ETL
✔ Practice on UNIX commands using CYGWIN tool
✔ Import flat file to database table in Oracle/Teradata/SQL Server
✔ Instruction document on running and monitoring workflows/jobs in SSIS/Informatica
✔ Samples in SSIS tool
|Live Instructor Based Training With Software|
|Lifetime access and 24×7 support|
|Certification Oriented content|
|Hands-On complete Real-time training|
|Get a certificate on course completion|
|Live Recorded Videos Access|
|Study Material Provided|
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ETL Testing Training FAQ'S
ETL stands for Extraction, Transformation, and Loading. It is an essential concept in Data Warehousing systems. There are three basic steps in Data Integration Process. Extraction stands for extracting the data from different data sources such as transactional systems or applications. Transformation stands to apply the conversion rules on data so that it becomes suitable for analytical reporting. Loading process involves, moving the data into the target system, i.e., Data Warehouse.
Extracted the data from an external source and move it to the data Warehouse pre-processor database.
Transform data task allows point-to-point generating, modifying, and transforming the data.
In this task, the data is added to the database table in a warehouse.
The three layers in the ETL are:
- Staging Layer: Staging layer is used to store the data which is extracted from the different data source systems.
- Data Integration Layer: Integration layer transforms the data from the staging layer and moves the data to a database. In the database, the data is arranged into hierarchical groups, which is often called dimension, and into facts and aggregation facts. The combination of facts and dimension table in a data warehouse system is called a schema.
- Access Layer: Access layer is used by the end-users to retrieve the data for analytical reporting.
Business Intelligence is the process for collecting raw business data and transforming it into a meaningful vision that is more useful for business.
The popular ETL tools available in the market are:
- IBM- Websphere DataStage
- Informatica- Power Center
- SAP- Business objects data service BODS
- SAS - Data Integration Studio
- Oracle- Warehouse Builder
- Open source Clover ETL.
Get ahead in your career by learning ETL Testing through VISWA Online Trainings