API Automation and TDD to Implement Master Data Survivorship Rules

API Automation and TDD to Implement Master Data Survivorship Rules

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  API Automation andTDD to implement Master Data Survivorship Rules Hrishi Potdar Software Quality Assurance Engineer Dell Boomi
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  Dell Boomi’s UnifiedPlatform Integrate Master Data Hub Workflow Automation and App Development B2B/EDI Management API Design and Management Application and Data Integration
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  Challenges With MasteringData Unreliable data Challenging to Manage Data Scattered in DifferentApplications
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  Data Integrity Challenges “Ourdata is neither standardized nor rationalized.” “Our data is slowing down the business… it’s inaccurate, inconsistent, incomplete.” “It’s too difficult to find the right information with all these duplicate records.” “We don’t have the resources to deal with data governance.” “It is hard to keep up with data audits across systems.” “There are too many systems to track all the changes.” “Our data is distributed across the organization and resides in silos.”
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  “The growing complexityof digital business drives an assumption that data should be collected centrally or connected in a distributed fashion. Current data and analytics strategies are falling short of business requirements, thus organizations need to look into alternative approaches such as a data hub.” Source: Gartner, “Use a Data Hub Strategy to Meet Your Data and Analytics Governance and Sharing Requirements”, A. White & T. Friedman, Feb 2, 2017 Boomi Master Data Hub
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  Data Synchronization withBoomi Master Data Hub Data Stewardship Data Quality Analytics Real-time, Bi-Directional Data Flow Data Governance Community Driven Modeling Simplified Integration Centralized Data Quality
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  Master Data Hub •Managing ~30 million Golden Records • Processes ~3.5 million Golden Records Per Day • Serves businesses in multiple countries in multiple continents • 100’s of thousands of records cleansed; thousands of duplicates removed • With SLA of 99.99% availability for our Clouds
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  Data Survivorship Rule(DSR) implementation • Lets you select and define your most trusted source of data per field • Applies to all different data types and field types such as references, collections, groups and operations such as create, update, delete, link, resolve data for the reference fields • Creates a trusted relationship with the source • Filters unwanted data coming into the system and reduces further processing workload and time • Sends out highly trusted field records to synchronize with other systems
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  DSR Testing Challenges •100’s of unique scenarios to test • Complex test scenarios involving multiple fields, field types and sources • Support multiple operations such as create/update/delete/link/resolve • Impact on Performance • Impact on existing application and regression
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  TDD Vs Traditionaldevelopment approach Traditional Development Development first Defect finding Test follows developed features Test Driven Development Test First Defect Prevention Test drives feature development Proactive Reactive
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  DSR Testing Matrix •Some test scenarios • Functional Testing Matrix
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  SMARTBEAR ReadyAPI toAssist withTesting • Demo in ReadyAPI – https://drive.google.com/file/d/1VO- 5TcYwzE7BB0jTKg6Jz5on4br2ryAN
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  Execution •
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  Reporting •
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  Reporting
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  Project Outcome • Projectwas released and tested in shortest sprint of the year • No functional issues reported related to DSR since release • Regression tests run daily in QA
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  Winning strategy Offense Design &development Assist Tools Defense QA & Testing and deployment practices
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  Questions?