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Ratings and Reviews 0 Ratings
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What is DataHub?
DataHub stands out as a dynamic open-source metadata platform designed to improve data discovery, observability, and governance across diverse data landscapes. It allows organizations to quickly locate dependable data while delivering tailored experiences for users, all while maintaining seamless operations through accurate lineage tracking at both cross-platform and column-specific levels. By presenting a comprehensive perspective of business, operational, and technical contexts, DataHub builds confidence in your data repository. The platform includes automated assessments of data quality and employs AI-driven anomaly detection to notify teams about potential issues, thereby streamlining incident management. With extensive lineage details, documentation, and ownership information, DataHub facilitates efficient problem resolution. Moreover, it enhances governance processes by classifying dynamic assets, which significantly minimizes manual workload thanks to GenAI documentation, AI-based classification, and intelligent propagation methods. DataHub's adaptable architecture supports over 70 native integrations, positioning it as a powerful solution for organizations aiming to refine their data ecosystems. Ultimately, its multifaceted capabilities make it an indispensable resource for any organization aspiring to elevate their data management practices while fostering greater collaboration among teams.
What is CA Data Content Discovery?
Recognizing, organizing, and safeguarding essential business information is crucial for minimizing risks and ensuring compliance with regulations. CA Data Content Discovery assists businesses in identifying potential data exposure risks while allowing them to establish strong protection measures for their information. By discovering data within mainframe systems, classifying it based on sensitivity levels, and producing comprehensive reports, organizations can improve their compliance and auditing practices. As companies confront a more complex regulatory environment alongside the demands of the digital economy, it becomes imperative to categorize data in line with compliance standards or organizational goals, leading to reduced manual efforts, streamlined compliance processes, and enhanced productivity. A thorough comprehension of your data landscape is vital for effective data security. Leveraging critical insights and detailed reporting can guide strategic decision-making, minimize risks, and fortify the organization, ensuring resilience amidst the challenges of the modern business world. This proactive approach not only protects vital assets but also bolsters the organization's long-term sustainability and growth.
Integrations Supported
Active Directory
Alibaba Cloud Data Integration
Amazon S3
Apache Kafka
Apache NiFi
ClickHouse
Delta Lake
Iceberg
Intertrust ExpresssPlay
Microsoft Azure
Integrations Supported
Active Directory
Alibaba Cloud Data Integration
Amazon S3
Apache Kafka
Apache NiFi
ClickHouse
Delta Lake
Iceberg
Intertrust ExpresssPlay
Microsoft Azure
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
DataHub
Company Location
United States
Company Website
datahubproject.io
Company Facts
Organization Name
Broadcom
Date Founded
1991
Company Location
United States
Company Website
www.broadcom.com/products/mainframe/compliance-data-protection/data-content-discovery
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics