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What is Infometry Google Connectors?

Infometry's Google Connectors enable the effortless merging of Google Applications with Informatica Cloud IDMC, which was formerly known as IICS. Their certified Google Sheets Connectors provide users with native interfaces for streamlined interaction. Organizations that adopt Infometry's Connectors can experience seamless integration while gaining access to real-time data analytics. Additionally, the Google Connector for Informatica simplifies the processes of application integration, data extraction for downstream systems, and ETL operations for Enterprise Data Warehouses. Many customers utilizing Informatica Cloud Connectors store a variety of datasets in Google Sheets, such as Sales Forecasts, Goals, Product Master records, SKU data, Lab Results, Headcount estimates, and OpEx Budgets, all of which require efficient transfer to Enterprise Data Warehouses, Cloud Applications, and Data Lakes. Infometry has created a Google Sheet connector that harnesses Informatica’s native interface, covering extensive API operations like reading, writing, updating, deleting, and searching, thus providing a comprehensive solution for data management. This integration not only enhances analytics but also significantly improves decision-making capabilities for businesses looking to maximize the value of their data. By leveraging these connectors, companies can ensure their data flows smoothly between platforms, fostering a more connected and efficient operational environment.

What is Data Quality Validator (DQV)?

DQV is an all-encompassing platform for data quality and testing, designed by Kumaran Systems, specifically for teams managing, masking, or validating large datasets. This sophisticated tool systematically assesses both source and target datasets on a granular level, pinpointing inconsistencies and generating comprehensive mismatch reports, thereby removing the necessity for tedious manual verification through spreadsheets. It boasts five essential features: it conducts field-level comparisons while identifying drift, enables migration mapping across diverse schemas, provides deterministic PII masking, performs validation at both record and table levels with the capability for immediate corrections, and creates synthetic data for teams without access to production environments for testing purposes. DQV supports a variety of data sources, such as SQL Server, Oracle, MySQL, PostgreSQL, AWS, Azure, GCP, flat files, JSON, XML, and REST APIs, and it integrates effortlessly with tools like Informatica, Databricks, and CI/CD pipelines. Alternatively, it can function independently as a library or command-line interface tool. In practical scenarios, DQV has demonstrated impressive performance by successfully validating 26.6 million bank records in under 22 minutes, underscoring its remarkable efficiency. Furthermore, it offers a free trial along with diverse licensing choices, including individual, enterprise, and on-premises plans, catering to the varied needs of organizations. This adaptable solution not only improves data integrity but also simplifies the testing workflow across multiple platforms, making it an invaluable asset for data management teams.

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Integrations Supported

Google Ads
Google Cloud Bigtable
Google Cloud Pub/Sub
Google Drive
Google Sheets
Informatica Intelligent Data Management Cloud

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Not specified

Company Facts

Organization Name

Infometry

Date Founded

2008

Company Location

United States

Company Website

www.infometry.net

Company Facts

Organization Name

Kumaran Systems

Date Founded

1992

Company Location

United States

Company Website

kumaran.com/products/dqv/

Categories and Features

Integration

Not specified

Categories and Features

Data Quality

Not specified

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