Doing data science right in Excel-pervasive utilities (on demand)

Sandi Joralemon (Adm) September 1, 2018

[one_half]

Tuesday, September 25th, 11:00am-12:00pm Eastern

Clutter created by years of Excel usage is inescapable in the utility industry, as are its associated bad consequences. A few years ago The Energy Authority (TEA) decided to utilize R to break out of this bad practice with the goal of building accurate, explainable, adaptable, scalable, accessible and reproducible models. With very limited help from IT developers, a group of analysts built up their own platforms for modeling, data storage, and deployment, overcoming numerous obstacles along the way. In this webinar, TEA will share their solutions to improving analytics workflow by adopting the latest R technology.

Attendees will learn:

Important attributes for data science platforms
Quality control for analytics models
How to generate interactive web UI without IT developers

Speaker:

Eina Ooka – Senior Quantitative Analyst, The Energy Authority

Eina Ooka leads TEA’s quantitative modeling efforts, particularly focusing on multivariate stochastic forecasting models for electric power markets. She has developed production-level models from scratch that are now used throughout the company for portfolio management. Eina’s expertise includes neural network modeling, machine learning, data science, and risk analysis. Eina holds a Masters in Mathematics from the University of Washington.

[/one_half]
[one_half]
Register Today

[/one_half]

Categories: Strategy, Technology, Webinars

Sandi Joralemon (Adm)

Sandi Joralemon (rhymes with “you’re a lemon”) has experience in enterprise systems and analytics architecture, data modeling, technical business analysis, internal audit, finance, and vendor management which enables her to serve as a trusted partner to senior leaders, functional stakeholders, and third-party vendors. Prior to joining Endeavor’s UAI team, Sandi managed enterprise systems and established protocols for data quality and data governance while designing and building a centralized data management system and implementing an enterprise analytics platform for a municipally owned utility.

Related Articles