Quality Assurance professionals performing Extract Transform and Load (ETL) operations often face challenges with understanding the requirements for functional data mapping. Understanding data dimensions and attributes, execution pointing to multiple sources, validation of huge data volume and transformation of data add to these challenges. This, in turn, affects the turnaround time and cost efficiency. However, automation of ETL processes enhances efficiency and reduces the turnaround time, along with providing an array of benefits across the testing lifecycle.

Automate Testing for Faster & Efficient ETL

Overview

Atos Syntel Approach

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DB Agnostic Framework Based Approach - Design & Execution

Req. /Mapping documents

Source /Target SQLGeneration

Database Setup Query Execution ComparisonSummary

Automation Automation

D/W - ETL Test Automation Framework

Key Highlights Value Delivered

• Query file analyzer

• End-to-end automation framework

• Data and count validation

• Automated aggregate tests

• Selective automation for summary reporting for test cases

• Wide coverage rather than sampling

• Aggregate verification

• Test case level summary reporting

• Faster turnaround time for testing

• Up to 100% test data coverage

• Database agnostic framework

• Up to 60-70% automation testing for any ETL system

• Accurate data validation at record level

• Elimination of manual errors

• Almost 40% reduction in efforts across testing lifecycle

For more information, visit us at www.atos-syntel.net

Atos Syntel helps overcome these challenges with its three-step independent automation framework Data Validator-Test Automation Framework. Its Swing-based unified graphical interface simplifies query creation for ETL/ data warehousing (DW) mapping. Data comparison between source and target and execution of manual test cases is also automated. Data Validator also makes tracking of real time data flows easy, along with execution statistics and an optional trace mode.