Energy Cognito

Energy CognitoEnergy CognitoEnergy Cognito

Energy Cognito

Energy CognitoEnergy CognitoEnergy Cognito
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    • Home
    • 日本語
    • About Us
      • Energy Cognito
      • Technology Platform
      • Japan Power Market
      • Contact Us
    • Solutions & Services
      • Portfolio Management
      • Data Service
      • Energy Forecast System
      • Analytics
    • News
    • Client Login
  • Home
  • 日本語
  • About Us
    • Energy Cognito
    • Technology Platform
    • Japan Power Market
    • Contact Us
  • Solutions & Services
    • Portfolio Management
    • Data Service
    • Energy Forecast System
    • Analytics
  • News
  • Client Login

Our Approach to Technology

Philosophy

User Interface (UI):

Energy Cognito utilizes and develops standard BI applications and various GUI solutions (Excel Add-In, .NET framework, Tableau, PowerBI and etc) for

  • Standardize processes and share works to enhance productivities across teams
  • Low cost and quicker development for each company’s versatile business environment

Models:

In modern market analytics platform, a model cannot exist in standalone off-the-shelf basis, but rather it should be a part of company’s proprietary processes.

  • Under current technology and maturity of energy market analytics, mix of multiple model/vendor choices should be considered for the specific expertise
  • Our in-depth experiences encompass risk models, advanced pricing analytics, fundamentals and transmission models, optimization models, and machine learning, etc.

Database:

Most critical foundation of analytics platform

  • Centralized repository of market data and proprietary information
  • Model/process inputs & outputs should be stored in database for ease of access, transparency and 
  • records of operation
  • Database would be critical not only for market analysis but also for all analytical, operational and execution processes  


Implementation

  • Energy Cognito adopts flexible technologies interchangeably
  • Backend and Frontend can be separable with the API
  • Backend can be easily convertible to SaaS structure or customized customer specific environments
  • Data collection/scrapping is performed with light/flexible python packages
  • Model or computation engines are modularized

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