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ease
features
design
support

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Description

Enhance the efficiency and effectiveness of decision-making across various levels by leveraging a comprehensive suite of automation, scalability, statistical expertise, and transparency, drawing from our extensive experience with numerous utilities globally. As the grid continues to evolve, it is essential to utilize a forecasting platform that can handle vast data sets to yield insights that reach down to the circuit level. SAS Energy Forecasting has demonstrated its ability to deliver detailed insights derived from these extensive data collections. By providing results that are repeatable, scalable, traceable, and defensible, this solution significantly boosts forecasting accuracy across diverse locations and levels of aggregation. The forecasts produced are transparent and well-documented, facilitating communication with both internal teams and external stakeholders, which can help prevent potential regulatory fines that could amount to millions. Furthermore, taking advantage of all available data can optimize investments in smart meters and advanced metering infrastructure, ultimately leading to improved operational outcomes. This comprehensive approach ensures that utilities remain agile and well-informed in a rapidly changing energy landscape.

Description

UST IQ for AMI Analytics streamlines the entire data engineering process, managing everything from the ingestion of large-scale, high-frequency metering data to delivering comprehensive insights, allowing AMI business operations to prioritize essential decision-making over IT infrastructure concerns. It efficiently collects both real-time and historical data, including meter readings, events, alarms, GIS information, and external data sources, and transforms this information into query-ready formats using a cloud-native, microservices architecture. This setup supports self-service querying, location-aware and role-specific analytics, and proactive exception management, providing operations teams with crucial insights regarding network anomalies, meter performance, outages, and environmental data such as seismic activity or weather patterns. By doing so, it enhances the ability to optimize field crew deployment, avert expensive failures, and improve restoration efforts. The system processes vast quantities of data, handling hundreds of millions of records each day through low-latency micro-batching, typically in 5-minute intervals, while also offering features like 30-day rolling averages and alert-triggered notifications to further support operational efficiency. This comprehensive approach not only accelerates data processing but also ensures that actionable insights are readily available when needed, ultimately leading to improved operational effectiveness.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

SAS Data Loader for Hadoop
SAS MDM

Integrations

SAS Data Loader for Hadoop
SAS MDM

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

SAS Institute

Founded

1976

Country

United States

Website

www.sas.com/en_hk/software/energy-forecasting.html

Vendor Details

Company Name

UST

Country

United States

Website

www.ust.com/en/what-we-do/digital-transformation/data-analytics/ust-iq/ami

Product Features

Utility Management Systems

Billing & Invoicing
Cable
Customer Management
Demand Planning
Electricity
Natural Gas
Plant Management
Service Call Management
Trash
Water
Work Order Management
Workforce Management

Alternatives

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