Parul Dubey

Sep, 2020 - [Internally Transferred to Cognizant from Medtronic]

Information management Services (Health care and life science)

CLIENT: Medtronic

TOOLS:

ETL - Informatica Power Center (10.4),Informatica Cloud (IICS)

Database- MS SQL, Oracle(12c)

Scheduler - IBM Tivoli (TWS)

Reporting Tools- Power BI, SAP Business Object XI,

Reporting Modeler - SAP HANA

Server- Unix

Code Repository - GIT

• Proficient at various level of application development, support and enhancement including requirement gathering, analysis, design, development, testing, production implementation, post deployment support and its associated documentation.
• Extracted data from flat files and other RDBMS databases into staging area and populated onto Data warehouse.
• Used various transformations like Source Qualifier, Filter, Expression, Sequence Generator, Update Strategy, Joiner, Stored Procedure, Lookup and Union to develop robust mappings in Informatica Designer.
• Developed mapping parameters and variables to support SQL override.
• Modified existing mappings for enhancements of new business requirements
• Wrote UNIX shell Scripts commands for FTP of files from remote server.
• Involved in Performance tuning at source, target, mappings, sessions, and system levels. Used Debugger to test mappings and fix bugs.
• Prepared migration document to move mappings from development to testing and then to production repositories.
• Using Informatica Power Center Designer analyzed the source data to Extract & Transform from various source systems(oracle 10g,DB2,SQL server and flat files) by incorporating business rules using different objects and functions that the tool supports.
• Constantly interacted with business users to discuss requirements.

Associate IT Developer : Medtronic [ Sep, 2018 - Aug,2020 ] :

An automated approach to incident classification using Machine Learning (Supervised Machine Learning, Classification Problem)

CLIENT : Medtronic

TOOLS : Python, SQL

• The project was designed as analytic approach for design and development of machine learning algorithm for incident classification and resolution in Global IT. The algorithm was designed based on Supervised Machine Learning methodology. The model so developed is aimed at eliminating manual effort needed in addressing and resolving service now tickets.