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What is Lenses?

Enable individuals to effectively delve into and assess streaming data. By organizing, documenting, and sharing your data, you could increase productivity by as much as 95%. Once your data is in hand, you can develop applications designed for practical, real-world scenarios. Establish a data-centric security model to tackle the risks linked to open-source technologies, ensuring that data privacy remains a top priority. In addition, provide secure and user-friendly low-code data pipeline options that improve overall usability. Illuminate all hidden facets and deliver unparalleled transparency into your data and applications. Seamlessly integrate your data mesh and technology stack, which empowers you to confidently leverage open-source solutions in live production environments. Lenses has gained recognition as the leading product for real-time stream analytics, as confirmed by independent third-party assessments. With insights collected from our community and extensive engineering efforts, we have crafted features that enable you to focus on what truly adds value from your real-time data. Furthermore, you can deploy and manage SQL-based real-time applications effortlessly across any Kafka Connect or Kubernetes environment, including AWS EKS, simplifying the process of tapping into your data's potential. This approach not only streamlines operations but also opens the door to new avenues for innovation and growth in your organization. By embracing these strategies, you position yourself to thrive in an increasingly data-driven landscape.

What is AVEVA Unified Engineering?

Leveraging Software as a Service (SaaS) through our industrial cloud platform, AVEVA Connect, AVEVA Unified Engineering provides a data-centric ecosystem for obtaining real-time engineering insights. This all-encompassing solution addresses the full spectrum of the project lifecycle, spanning from initial conceptual design to front-end engineering and design (FEED) and the detailed design stages. By promoting data transparency throughout various project disciplines and phases, it uniquely serves as the only data-driven framework that aligns both process and asset engineering lifecycles. Teams can effectively perform conceptual, FEED, and detailed engineering designs from a unified data source, enhancing collaboration among internal teams and outside suppliers alike. The development of a digital twin, fueled by real-time project data, significantly improves engineering visibility for all stakeholders involved while reducing transition challenges. Furthermore, the platform ensures secure operations from any location, which ultimately enhances productivity and empowers teams. This capability allows for rapid scalability to address project requirements, thereby ensuring that all facets of engineering are managed and optimized effectively. Consequently, AVEVA Unified Engineering allows organizations to adapt swiftly to changing demands while maintaining high standards of efficiency.

Media

Media

Integrations Supported

Amazon EKS
Amazon MSK
Amazon S3
Apache Cassandra
Apache Kafka
Cloudera
Datadog
GitHub
GitLab
Kubernetes
Okta
PagerDuty
Slack
Splunk Enterprise
Zoho Directory

Integrations Supported

AVEVA Connect
AVEVA Diagrams
AVEVA E3D Design
AVEVA Electrical and Instrumentation
AVEVA Engineering

API Availability

API Availability

Pricing Information

$49 per month

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Lenses.io

Date Founded

2016

Company Location

United Kingdom

Company Website

lenses.io

Company Facts

Organization Name

AVEVA

Company Location

United Kingdom

Company Website

www.aveva.com/en/products/unified-engineering/

Categories and Features

Data Governance

Not specified

Data Masking

Not specified

DataOps

Not specified

Streaming Analytics

Not specified

Categories and Features

Engineering

Not specified

Simulation

Not specified

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