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What is ETL DataHub?

ETL Solutions introduces DataHub, a powerful platform designed for data integration, orchestration, and management that caters specifically to enterprises, allowing organizations to consolidate, harmonize, and effectively leverage data from diverse sources within a well-regulated and accessible framework. This innovative platform streamlines the seamless ingestion and transformation of both structured and unstructured data, utilizing a range of pre-built connectors and mappings alongside automated workflows, change data capture, and real-time data pipelines that support analytics, reporting, and AI/ML projects. Built to operate efficiently in hybrid and multi-cloud environments, DataHub integrates metadata and business logic while upholding stringent standards for data governance, lineage tracking, and quality assurance, thus enabling stakeholders to confidently harness enterprise data. In addition, its advanced orchestration engine skillfully handles complex dependencies and scheduling, ensuring prompt data delivery and consistency across varied systems, which significantly boosts overall operational efficiency. Moreover, DataHub's user-friendly interface and robust capabilities empower organizations to transform their data into actionable insights, driving better decision-making and fostering innovation. Ultimately, this comprehensive platform not only enhances data management practices but also positions enterprises for future growth and success.

What is DataHUB+?

DataHUB+ represents an advanced process data historian and visualization solution for modern enterprises. It empowers users to monitor assets and systems in real-time across extensive networks, providing quick insights through integrated analytics and visualization tools, enabling visibility into the status of any facility, plant, or system at any given moment. Being agnostic to equipment and sensors, DataHUB+ can effortlessly import data from any IoT devices or sensors, regardless of whether the data is structured or unstructured. This adaptability allows DataHUB+ to establish itself as the definitive source of truth, ensuring all operational data is securely and reliably stored. Additionally, the platform proactively assesses data quality prior to ingestion and notifies teams of any issues that arise. Unlike traditional process historians that depend on expensive IT infrastructure, DataHUB+ is designed for easy scalability to meet the demands of enterprise data management. Furthermore, it integrates seamlessly with VROC's AI solution OPUS, facilitating forecasting, predictive maintenance, and sophisticated analytics. By removing data silos and minimizing data wrangling within organizations, DataHUB+ enhances data-driven decision-making processes. Organizations can harness DataHUB+ to gain deeper insights into their operations and drive significant improvements in efficiency.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Microsoft Azure

Integrations Supported

AVEVA Historian
AVEVA PI System
AWS Amplify
Aspen HYSYS
Azure Industrial IoT
Canary Historian
ControlST
DCS
FactoryTalk Historian
Ignition SCADA
Microsoft Entra ID
SIMATIC SCADA

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Competitive pricing structure based on number of tags. Includes unlimited users and data analytics

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ETL

Date Founded

2002

Company Location

United States

Company Website

etlsolutions.com/datahub-data-integration-service-landing/

Company Facts

Organization Name

VROC

Date Founded

2016

Company Location

Australia

Company Website

vroc.ai/products/datahub/

Categories and Features

Data Integration

Not specified

Categories and Features

Data Historians

Not specified

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