Upgrade to Pro — share decks privately, control downloads, hide ads and more …

The Office Hours Data Conundrum

Sponsored · Your Podcast. Everywhere. Effortlessly. Share. Educate. Inspire. Entertain. You do you. We'll handle the rest. →
Avatar for Christina Koch Christina Koch
February 15, 2018
Research
0
190

The Office Hours Data Conundrum

Avatar for Christina Koch

Christina Koch

February 15, 2018
Tweet

More Decks by Christina Koch

See All by Christina Koch
Data Carpentry SQL Introduction
Avatar for Christina Koch christinalk
0
1.3k
A Different Kind of Carpentry
Avatar for Christina Koch christinalk
0
200
Best Practices For All
Avatar for Christina Koch christinalk
0
150
Query Live Database
Avatar for Christina Koch christinalk
0
650
Workshop Development en breve
Avatar for Christina Koch christinalk
0
110
Software Portability
Avatar for Christina Koch christinalk
0
320
Software Licenses and Interpreted Languages
Avatar for Christina Koch christinalk
0
140
Research Computing Taxonomy
Avatar for Christina Koch christinalk
0
230
HTCondor User Tutorial
Avatar for Christina Koch christinalk
0
330

Other Decks in Research

See All in Research
Agentic AI フレームワーク戦略白書 (2025年度版）
Avatar for MIKIO KUBO mickey_kubo
1
130
「車1割削減、渋滞半減、公共交通2倍」を 熊本から岡山へ＠RACDA設立30周年記念都市交通フォーラム2026
Avatar for Traffic Brain trafficbrain
1
730
Off-Policy Evaluation and Learning for Matching Markets
Avatar for Yudai Hayashi yudai00
0
100
大規模言語モデルにおけるData-Centric AIと合成データの活用 / Data-Centric AI and Synthetic Data in Large Language Models
Avatar for tsurubee tsurubee
1
520
通時的な類似度行列に基づく単語の意味変化の分析
Avatar for hajime kiyama rudorudo11
0
170
2025-11-21-DA-10th-satellite
Avatar for Yuka Egusa yegusa
0
130
【SIGGRAPH Asia 2025】Lo-Fi Photograph with Lo-Fi Communication
Avatar for Chinatsu Ozawa toremolo72
0
130
Akamaiのキャッシュ効率を支えるAdaptSizeについての論文を読んでみた
Avatar for bootjp / ぶーと bootjp
1
500
学習型データ構造：機械学習を内包する新しいデータ構造の設計と解析
Avatar for Yusuke Matsui matsui_528
6
3.8k
視覚から身体性を持つAIへ: 巧緻な動作の3次元理解
Avatar for Take Ohkawa tkhkaeio
1
210
データサイエンティストの業務変化
Avatar for The Japan DataScientist Society datascientistsociety
PRO
0
290
量子コンピュータの紹介
Avatar for OQTOPUS oqtopus
0
230

Featured

See All Featured
Fantastic passwords and where to find them - at NoRuKo
Avatar for Phil Nash philnash
52
3.6k
[RailsConf 2023 Opening Keynote] The Magic of Rails
Avatar for Eileen M. Uchitelle eileencodes
31
10k
How to optimise 3,500 product descriptions for ecommerce in one day using ChatGPT
Avatar for Katarina Dahlin katarinadahlin
PRO
1
3.5k
A designer walks into a library…
Avatar for Paul Jervis Heath pauljervisheath
210
24k
Understanding Cognitive Biases in Performance Measurement
Avatar for Philip Tellis bluesmoon
32
2.8k
For a Future-Friendly Web
Avatar for Brad Frost brad_frost
183
10k
Mozcon NYC 2025: Stop Losing SEO Traffic
Avatar for Sam Torres samtorres
0
170
B2B Lead Gen: Tactics, Traps & Triumph
Avatar for Sophie Logan marketingsoph
0
75
Design in an AI World
Avatar for tapps tapps
0
170
Deep Space Network (abreviated)
Avatar for Tony Rice tonyrice
0
89
Become a Pro
Avatar for Speaker Deck speakerdeck
PRO
31
5.8k
Heart Work Chapter 1 - Part 1
Avatar for Lake Fama lfama
PRO
5
35k

Transcript

  1. { The  Office  Hours   Conundrum Christina  Koch Data  Story

     Slam,  February  2018

  2. This  is  me   (Christina)

  3. My  colleague  Lauren  and  I  work  for  the   Center

     for  High  Throughput  Computing  (CHTC)   as  research  computing  facilitators

  4. { New  accounts,  ongoing  meetings,   and  weekly  office  hours.

    We  meet  with  a  lot   of  people.

  5. { Question How  many  people  do  Christina  and  Lauren  meet

      with  every  month?

  6. Version  1:  Calendar

  7. Version  2:  Form

  8. Version  3:  Sign  In

  9. Success!

  10. { Busiest  Month May:  77  people

  11. { Slowest  Month December:  27  people

  12. None

  13. { What  happened   in  July? Christina  and  Lauren  were

     out  of  the  office   (conferences,  summer  school,  workshops)

  14. { 312 Number  of  people  new  to  CHTC

  15. None

  16. Ñ  Everyone  has  to  deal  with  data Ñ  Sometimes  a

     simple  solution  is  the  best  solution Ñ  Structure  your  data Ñ  Once  you  have  data,  you  can  tell  a  story Lessons  Learned