Data Science Community
In its simplest form, data science involves developing methods of recording, storing, and analyzing... View more
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Upcoming February (2022) Community Conversation
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Upcoming February (2022) Community Conversation
Hello Data Science Community Members,
I hope all is well! With February just kicking off, I wanted to reach out and get you excited for our February (2022) Data Science Community Conversation. On Tuesday, February 15th at 1:00 PM CT, we will be joined by Dominic Ciarlette, Senior Project Engineer – Data Solutions at EN Engineering who will be leading a discussion around, “Sifting Data for Suspicious Records with Machine Learning.” I’ll be providing more information on this session one week prior to our meeting but you can always learn more about each of our upcoming Community Conversations on our Events Page HERE.
Our latest IT update allows me to send meeting placeholders directly to your calendars through my alternate email address kpraet@sg.utilityanalytics.com. I sent out invitations for this community, and each of our other communities, last month. If you did not receive a calendar invitation let me know so I can help troubleshoot. As this seems to be an issue with some of our members’ firewalls, we recommend whitelisting my new email address kpraet@sg.utilityanalytics.com to ensure any invites don’t go to your spam/junk folders.
Again please let me know if you have any questions/concerns or do not have a calendar placeholder on your calendar.
Thanks and I look forward to connecting with you all this month!
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Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
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3 Replies
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Hello Kevin,
Can you add me the to the invite list for the calendar notices.
Thanks,
Brian
Brian Mori, Director of Data Analytics
Generation Strategy & Innovation
Integrated Fleet Management
Ontario Power Generation800 Kipling Ave, KR2-206, Toronto, ON M8Z 5G5 W (289) 440-3725 E brian.mori@opg.com
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Original Message:
Sent: 2/8/2022 12:31:00 PM
From: Kevin Praet
Subject: RE: Upcoming February (2022) Community ConversationHello Data Science Community Members,
I hope all is well! We are one week away from our February (2022) Data Science Community Conversation and want to get you excited about the session taking place. On Tuesday, February 15th at 1:00 PM CT, we’ll be joined by Dominic Ciarlette, Senior Project Engineer – Data Solutions at EN Engineering, who will be leading a discussion around, “Sifting Data for Suspicious Records with Machine Learning.” As this discussion will be interactive, we encourage you to come prepared with questions and your insight.
Learn more about this session and our speaker below!
Session Description:
When managing utility assets, public safety and federal regulations demand the most accurate data possible. Using machine learning, EN Engineering has developed a model that identifies individual records likely to contain erroneous data. This improves efficiency in correcting datasets and reveals trends that can then be analyzed to strengthen the accuracy of all records.
Session Takeaways:
– Identify data within a set most likely to be erroneous
– Improve accuracy of large datasets through machine learning
– Reveal and analyze trends in large datasets using data modelsSpeaker: Dominick Ciarlette, Senior Project Engineer – Data Solutions (EN Engineering)
Mr. Dominic Ciarlette is Senior Project Engineer and engineering consultant at EN Engineering with expertise in data analysis and modeling activities to support system design and operation.___________________________________________________________________________________________________________________________________________________
A calendar placeholder for this community conversation was sent out via my alternate email address (kpraet@sg.utilityanalytics.com). If you are not seeing a placeholder on your calendar for Tuesday, February 15th at 1:00 PM CT, please reach out to me so I can be sure you are forwarded the invite an alternate way.Thanks and I look forward to connecting next week!
——————————
Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
—————————— -
Hey @Brian,
Thanks for getting in touch! I just forwarded over our placeholder series would you mind confirming you recieved? Each placeholder will be updated with our Microsoft Teams credintials one day prior to each meeting.
Thanks again!
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Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
——————————
——————————————-
Original Message:
Sent: 02-08-2022 14:33
From: Brian Mori
Subject: Upcoming February (2022) Community ConversationHello Kevin,
Can you add me the to the invite list for the calendar notices.
Thanks,
Brian
Brian Mori, Director of Data Analytics
Generation Strategy & Innovation
Integrated Fleet Management
Ontario Power Generation800 Kipling Ave, KR2-206, Toronto, ON M8Z 5G5 W (289) 440-3725 E brian.mori@opg.com
Original Message:
Sent: 2/8/2022 12:31:00 PM
From: Kevin Praet
Subject: RE: Upcoming February (2022) Community ConversationHello Data Science Community Members,
I hope all is well! We are one week away from our February (2022) Data Science Community Conversation and want to get you excited about the session taking place. On Tuesday, February 15th at 1:00 PM CT, we’ll be joined by Dominic Ciarlette, Senior Project Engineer – Data Solutions at EN Engineering, who will be leading a discussion around, “Sifting Data for Suspicious Records with Machine Learning.” As this discussion will be interactive, we encourage you to come prepared with questions and your insight.
Learn more about this session and our speaker below!
Session Description:
When managing utility assets, public safety and federal regulations demand the most accurate data possible. Using machine learning, EN Engineering has developed a model that identifies individual records likely to contain erroneous data. This improves efficiency in correcting datasets and reveals trends that can then be analyzed to strengthen the accuracy of all records.
Session Takeaways:
– Identify data within a set most likely to be erroneous
– Improve accuracy of large datasets through machine learning
– Reveal and analyze trends in large datasets using data modelsSpeaker: Dominick Ciarlette, Senior Project Engineer – Data Solutions (EN Engineering)
Mr. Dominic Ciarlette is Senior Project Engineer and engineering consultant at EN Engineering with expertise in data analysis and modeling activities to support system design and operation.___________________________________________________________________________________________________________________________________________________
A calendar placeholder for this community conversation was sent out via my alternate email address (kpraet@sg.utilityanalytics.com). If you are not seeing a placeholder on your calendar for Tuesday, February 15th at 1:00 PM CT, please reach out to me so I can be sure you are forwarded the invite an alternate way.Thanks and I look forward to connecting next week!
——————————
Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
—————————— -
Hello Data Science Community Members,
I hope all is well! We are one week away from our February (2022) Data Science Community Conversation and want to get you excited about the session taking place. On Tuesday, February 15th at 1:00 PM CT, we’ll be joined by Dominic Ciarlette, Senior Project Engineer – Data Solutions at EN Engineering, who will be leading a discussion around, “Sifting Data for Suspicious Records with Machine Learning.” As this discussion will be interactive, we encourage you to come prepared with questions and your insight.
Learn more about this session and our speaker below!
Session Description:
When managing utility assets, public safety and federal regulations demand the most accurate data possible. Using machine learning, EN Engineering has developed a model that identifies individual records likely to contain erroneous data. This improves efficiency in correcting datasets and reveals trends that can then be analyzed to strengthen the accuracy of all records.
Session Takeaways:
– Identify data within a set most likely to be erroneous
– Improve accuracy of large datasets through machine learning
– Reveal and analyze trends in large datasets using data modelsSpeaker: Dominick Ciarlette, Senior Project Engineer – Data Solutions (EN Engineering)
Mr. Dominic Ciarlette is Senior Project Engineer and engineering consultant at EN Engineering with expertise in data analysis and modeling activities to support system design and operation.___________________________________________________________________________________________________________________________________________________
A calendar placeholder for this community conversation was sent out via my alternate email address (kpraet@sg.utilityanalytics.com). If you are not seeing a placeholder on your calendar for Tuesday, February 15th at 1:00 PM CT, please reach out to me so I can be sure you are forwarded the invite an alternate way.Thanks and I look forward to connecting next week!
——————————
Kevin Praet
Membership Coordinator
Utility Analytics Institute (UAI)
Boulder CO
315-440-3033
——————————
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