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What is DQE One?

In our current digital age, customer information can be found everywhere, from mobile devices and social media to IoT gadgets, CRM systems, ERP tools, and various marketing strategies. While organizations gather an enormous amount of data, much of it tends to be underused, incomplete, or inaccurate, which can hinder operational efficiency and threaten potential growth. To avoid disruptions, it is crucial that customer data acts as an integrated component linking all aspects of business operations. Ensuring the reliability and accessibility of this information for all stakeholders at any given moment is paramount. The DQE One solution is designed to support all departments that depend on customer data, enhancing the quality of information and building trust in the decision-making process. As contact information accumulates from various sources within corporate databases, issues may arise, such as data entry errors, incorrect contact details, and missing information. Therefore, it becomes essential to consistently validate and maintain the customer database throughout its lifecycle, converting it into a trustworthy asset. By emphasizing data quality, businesses can not only enhance their operational efficiency but also open doors to new opportunities for growth and innovation that were previously unexplored. Ultimately, the commitment to high-quality data management can significantly influence a company's long-term success.

What is APERIO DataWise?

Data is fundamental to all operations within a processing facility, acting as the cornerstone for workflows, strategic planning, and environmental oversight. However, complications often arise from this very data, leading to operator errors, faulty sensors, safety issues, or subpar analytics. APERIO is designed to effectively tackle these problems. The reliability of data is essential for Industry 4.0, supporting advanced applications such as predictive analytics, process optimization, and custom AI solutions. APERIO DataWise, known for its robust reliability, stands out as the leading source of trustworthy data. By automating the quality assurance for your PI data or digital twins in a scalable and continuous manner, organizations can guarantee validated information that enhances asset dependability. This not only enables operators to make well-informed decisions but also helps in identifying risks to operational data, which is crucial for sustaining operational resilience. Additionally, it offers accurate monitoring and reporting of sustainability metrics, thus fostering more responsible and efficient practices. In the current landscape driven by data, harnessing dependable information has transitioned from being a mere advantage to an essential requirement for achieving success. The integration of high-quality data solutions can transform the way organizations approach their operational challenges and sustainability goals.

Media

Media

Integrations Supported

Integrations Supported

ABB Analyze
AVEVA Connect
Actian DataConnect
Amazon QuickSight
Amazon SageMaker
Amazon Timestream
Amazon Web Services (AWS)
Apache Parquet
CitectHMI
Databricks
Google Cloud Managed Service for Apache Airflow
Honeywell Forge
IBM Cloud
LUMINAI Refinery Advisor
Microsoft Azure
Qumulex QxControl
SAP Cloud Platform
WANdisco
Yokogawa Enterprise Pipeline Management
aspenONE Supply Chain Management

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

DQE

Date Founded

2008

Company Location

United Kingdom

Company Website

dqe.tech/en/dqe-one/

Company Facts

Organization Name

APERIO

Company Location

United States

Company Website

aperio.ai/aperio-datawise/

Categories and Features

Data Deduplication

Not specified

Data Quality

Not specified

Categories and Features

Data Quality

Not specified

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