Enterprise Data Platform Automation for Data Validation and Integration

This project aims to implement a robust and scalable solution that automates critical data validation, reconciliation, and profiling tasks across multiple data sources such as SQL Server, Oracle, PeopleSoft etc. into an Enterprise Data Platform on Snowflake. This solution will streamline processes, ensuring data accura…

Source ID: us-nyc-current-solicitations-20250122013

Scope overview

This project aims to implement a robust and scalable solution that automates critical data validation, reconciliation, and profiling tasks across multiple data sources such as SQL Server, Oracle, PeopleSoft etc. into an Enterprise Data Platform on Snowflake. This solution will streamline processes, ensuring data accuracy, completeness, and reliability while enabling seamless integration with various data sources.

By incorporating automated capabilities for testing, validation, and performance monitoring, the project will enhance operational efficiency and support data-driven decision-making. Additionally, the solution will include features for test management, incremental data validation, and ensure consistency across environments. It will also provide tools for generating quality scores and enabling effective monitoring.

This initiative is aligned with industry best practices and will empower teams to handle complex datasets with confidence and precision. Agency: NYC Health + Hospitals Status: Solicitation

Statusopen
CategoryGoods
CountryUnited States
Publish dateFeb 3, 2025
Submission deadlineMar 6, 2025
Estimated value
Notice typetender_notice
Sourceus-nyc-city-record-procurement-nyc-health-hospitals
BuyerNYC Health + Hospitals
Buyer websitehttps://data.cityofnewyork.us/
CityNew York

Buyer & contacts

Contact namePilar Grullón
Emailrfp_contacts@nychhc.org
Phone(646) 815-3815
OrganizationNYC Health + Hospitals

Tags & Signals

data validationenterprise data platformSnowflake integrationdata reconciliationautomated testingdata profilingoperational efficiencydata quality

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