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What is Informatica Enterprise Data Catalog?

Efficiently scan and catalog metadata to uncover and characterize data while ensuring comprehensive lineage tracking across millions of datasets. Organize and classify data assets in various environments to maximize their value and promote reuse. Conduct automated scanning in multi-cloud environments, business intelligence tools, ETL processes, and external metadata catalogs, encompassing a wide array of data types. Leverage AI-driven capabilities for domain discovery, data similarity evaluation, business term associations, and customized recommendations tailored to user needs. Monitor data movement with accuracy, from broad system overviews to detailed column-level lineage, all supported by thorough impact assessments. Utilize the Data Asset Analytics dashboard for insights into asset utilization, enrichment processes, and collaborative initiatives. Analyze data quality protocols, scorecards, metric clusters, and profiling statistics within their respective contexts. Collaborate with shared data intelligence through certifications, ratings, feedback, a Q&A feature, and timely change alerts. What sets Informatica apart is its comprehensive and powerful suite of enterprise-grade data management solutions, which provide extensive support for a variety of data requirements. This multitude of features empowers organizations to adeptly navigate their complex data landscapes, facilitating more informed decision-making and strategic planning. By harnessing such capabilities, businesses can efficiently leverage their data assets for competitive advantage.

What is Aggua?

Aggua functions as an AI-enhanced data fabric platform aimed at equipping both data and business teams with easy access to their information, building trust, and providing actionable insights for more informed decision-making based on data. With just a few clicks, you can uncover essential details about your organization's data framework instead of remaining unaware of its complexities. Obtain insights into data costs, lineage, and documentation effortlessly, allowing your data engineers to maintain their productivity without interruptions. Instead of spending excessive time analyzing how changes in data types affect your pipelines, tables, and overall infrastructure, automated lineage facilitates your data architects and engineers in reducing the time spent on manual log checks, allowing them to concentrate on implementing necessary infrastructure improvements more effectively. This transition not only simplifies operations but also fosters better collaboration among teams, leading to a more agile and responsive approach to tackling data-related issues. Additionally, the platform ensures that all users, regardless of their technical background, can engage with data confidently and contribute to an organization's data strategy.

Media

Media

Integrations Supported

Snowflake
Accenture Cloud Retail Execution
Amazon Web Services (AWS)
Azure Marketplace
BigID
Databricks
Deloitte Cascade Suite
Eviden MDR Service
Google Cloud Platform
Microsoft 365
Microsoft Azure
Salesforce
SendGrid
Tableau

Integrations Supported

Snowflake
Amazon Redshift
Google Cloud BigQuery

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Informatica

Company Location

United States

Company Website

www.informatica.com/products/data-catalog/enterprise-data-catalog.html

Company Facts

Organization Name

Aggua

Date Founded

2020

Company Location

United States

Company Website

www.aggua.io

Categories and Features

Data Catalog

Not specified

Metadata Management

Not specified

Categories and Features

Data Catalog

Not specified

Data Engineering

Not specified

Data Fabric

Not specified

Data Governance

Not specified

Data Lineage

Not specified

Data Management

Not specified

Data Mapping

Not specified

Data Observability

Not specified

Data Quality

Not specified

Metadata Management

Not specified

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