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Utilities Meter Data Management VS MyAnalytics

Compare Utilities Meter Data Management VS MyAnalytics and see what are their differences

Utilities Meter Data Management logo Utilities Meter Data Management

Oracle's Applications for Meter Data Management helps utilities to support the loading, validation, editing, and estimation (VEE) of meter data.

MyAnalytics logo MyAnalytics

MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.
  • Utilities Meter Data Management Landing page
    Landing page //
    2023-05-12
  • MyAnalytics Landing page
    Landing page //
    2023-09-21

Category Popularity

0-100% (relative to Utilities Meter Data Management and MyAnalytics)
Energy And Utilities Vertical Software
Technical Computing
0 0%
100% 100
Project Management
100 100%
0% 0
Business & Commerce
41 41%
59% 59

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What are some alternatives?

When comparing Utilities Meter Data Management and MyAnalytics, you can also consider the following products

The PI System - With the PI System, OSIsoft customers have reduced costs, opened new revenue streams, extended equipment life, increased production capacity, and more.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

Oracle DataRaker - Oracle DataRaker unlocks smart meter data and transforms it into compelling, quantifiable, and actionable results with low upfront investment and risk.

Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.

ATLAS Energy Monitoring System - AtlasEVO Energy Management & Energy Monitoring Systems. Collect and analyse energy usage data (electric, gas, water etc) from any number of metering points.

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.