Data Science Community
In its simplest form, data science involves developing methods of recording, storing, and analyzing... View more
Organizer:
- Organized by
-
-
Recording for July 2022 Community Conversation + Next Month’s Details + Announcements
-
Recording for July 2022 Community Conversation + Next Month’s Details + Announcements
Hello Data Science Community Members,
Thanks for attending the July 19, 2022 Data Science Community Conversation! For those unable to attend, we missed you and look forward to seeing you online next month. During this Community Conversation we were joined by Sean Otto, Director of Analytics at AES, who led a discussion around, “Data Governance – Rat Race or Eternal Quest: Learnings from AES to Helping You Strategize Your Journey.”
Please find the recording and presentation deck for this Community Conversation in the library. If you haven’t taken our post-meeting evaluation, please take a minute and complete it at the following link: https://www.surveymonkey.com/r/UAIComm2022
We look forward to seeing you online next month for the next Data Science Community Conversation which takes place Tuesday, August 16th at 1:00 PM CT. During this community conversation, we’ll be joined by Brad Gall, Sr. Data Architect and Sarah Valovcin, Sr. Data Scientist at The Energy Authority who will be leading a discussion around, “Using Machine Learning to Detect Broken AMI Meters.” To stay up-to-date with this session and each of our future community conversations be sure to visit our Events Calendar.
Keep reading for a few quick announcements!- Join us at UA Week 2022
- Website URL: https://www.utilityanalyticsweek.com/2022
- Date: October 18-20 (2022)
- Location: DoubleTree by Hilton | San Diego, CA
- Host: SDG&E
- Utility Analytics 101 Training – Register Today for 2022
- Website URL: https://training.utilityanalytics.com/
- UAI has partnered with The University of Oklahoma, Data Science and Analytics Institute to develop and deliver training and certification in analytics topics in the utilities sector. We could not be more excited to bring this new offering to the industry!
- Register for public classroom, virtual classroom and private group training options.
- The training will provide a Certificate of Participation and Completion and Continuing Education Units (CEUs) through the University of Oklahoma.
- Contribute a High Value Use Case for our Upcoming Repository
- The high value analytics use case form is for collecting information about planned, underway, or complete high value analytics use cases.
- The Executive Advisory Council (EAC) request the collection of these use cases each year. The collected information is for UAI member UTILITY COMPANY representatives ONLY.
- Submission Link: https://www.surveymonkey.com/r/CY8NMVF
- Speak During a Future Community Conversation!
- All of our members have a different story to tell which is what makes the UAI Community great! Share what projects you’re working on at your utility by being a speaker during a future community conversation.
- Proposal Link: https://uaievents.wufoo.com/forms/x1ei9mtx17zuq9w/
- Remember, you don’t have to be at the end of your journey to share …sharing along the way is a valuable part of the process and could ultimately help you make adjustments and improvements.
Again please find the recording and presentation deck for this Community Conversation in the library.——————————
Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
—————————— - Join us at UA Week 2022
-
2 Replies
-
This is a good question. Depends upon the Database. If your OMS is like our OMS then you’ll have 500 tables, all of which 50 may be important. The goal is to bring over only the business relevant data into the core datalake. Keeping it small also minimizes the data modeling you have to do. If you are running into challenges where you are purchasing hard drive space every 3 months, it is cheaper to just append everything to the cloud and put it in glacial storage. We’ve done that with a few of our databases. Cost is far cheaper to offload 4 years of data and keep 2 or 3 in the database than to keep adding storage space. It also improves performance of the system :)
I like to think of this is a journey or laps around a track. We focus on what is needed for the business immediately and expand from them with a long term goal of storing the data in the data lake.
Hope this helps answer your question.
——————————
Sean Otto
Director of Analytics
AES
——————————
——————————————-
Original Message:
Sent: 07-19-2022 15:11
From: Leslie Cook
Subject: Data Governance Question from July 19 2022 Community ConversationWe ran out of time today during the July 19, 2022 UAI Data Science Community Conversation. We had one question pending for @Sean.
Sean, do you mind answering the following question from @Dan?
- What is the practice for bringing data to the lake in terms of scope? Do you strive to bring in whole databases, only specific tables needed, or only specific subsets of tables needed?
Thanks so much to Sean for a great session today!
Cheers,
Leslie
——————————
Leslie Cook
Membership & Digital Engagement Manager
Utility Analytics Institute (UAI)
719-203-8650, lcook@utilityanalytics.com
—————————— -
That’s what we are doing here at NYPA. The Data Governance team discusses with the data stewards what’s critical to move into the lake. Not everything is moved in.
Ben Ettlinger
IT Data Analytics Architect
123 Main St.
White Plains, NY 10601
914-681-6496 |
——————————————-
Original Message:
Sent: 7/20/2022 10:18:00 AM
From: Sean Otto
Subject: RE: Data Governance Question from July 19 2022 Community ConversationThis is a good question. Depends upon the Database. If your OMS is like our OMS then you’ll have 500 tables, all of which 50 may be important. The goal is to bring over only the business relevant data into the core datalake. Keeping it small also minimizes the data modeling you have to do. If you are running into challenges where you are purchasing hard drive space every 3 months, it is cheaper to just append everything to the cloud and put it in glacial storage. We’ve done that with a few of our databases. Cost is far cheaper to offload 4 years of data and keep 2 or 3 in the database than to keep adding storage space. It also improves performance of the system :)
I like to think of this is a journey or laps around a track. We focus on what is needed for the business immediately and expand from them with a long term goal of storing the data in the data lake.
Hope this helps answer your question.
——————————
Sean Otto
Director of Analytics
AES
——————————
——————————————-
Original Message:
Sent: 07-19-2022 15:11
From: Leslie Cook
Subject: Data Governance Question from July 19 2022 Community ConversationWe ran out of time today during the July 19, 2022 UAI Data Science Community Conversation. We had one question pending for @Sean.
Sean, do you mind answering the following question from @Dan?
- What is the practice for bringing data to the lake in terms of scope? Do you strive to bring in whole databases, only specific tables needed, or only specific subsets of tables needed?
Thanks so much to Sean for a great session today!
Cheers,
Leslie
——————————
Leslie Cook
Membership & Digital Engagement Manager
Utility Analytics Institute (UAI)
719-203-8650, lcook@utilityanalytics.com
——————————
Log in to reply.