Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
The Open Source Data Tooling Landscape
Search
Carol Willing
PRO
August 24, 2021
Technology
1
81
The Open Source Data Tooling Landscape
Given for Coiled webinar on August 24, 2021.
Carol Willing
PRO
August 24, 2021
Tweet
Share
More Decks by Carol Willing
See All by Carol Willing
Lessons in Leadership: Python, AI, and Heuristics
willingc
PRO
0
85
Embracing Python, AI, and Heuristics: Optimal Paths for Impactful Software
willingc
PRO
0
820
Thriving with Python: Navigate the pitfalls in a polyglot world
willingc
PRO
1
140
Pragmatic Python: Python 3.12 and beyond
willingc
PRO
0
160
The Future is Notebooks
willingc
PRO
0
99
PyCon 2023 Keynote
willingc
PRO
0
190
Python: The People's Programming Language
willingc
PRO
0
100
A Random Walk with Snakes and Friends
willingc
PRO
0
52
Jupyter Notebooks for Humans
willingc
PRO
0
230
Other Decks in Technology
See All in Technology
Goで作って学ぶWebSocket
ryuichi1208
3
2.4k
Iceberg Meetup Japan #1 : Iceberg and Databricks
databricksjapan
0
290
エンジニアが加速させるプロダクトディスカバリー 〜最速で価値ある機能を見つける方法〜 / product discovery accelerated by engineers
rince
4
530
実は強い 非ViTな画像認識モデル
tattaka
1
1k
JavaにおけるNull非許容性
skrb
1
400
Swiftの “private” を テストする / Testing Swift "private"
yutailang0119
0
140
大規模アジャイルフレームワークから学ぶエンジニアマネジメントの本質
staka121
PRO
2
150
【5分でわかる】セーフィー エンジニア向け会社紹介
safie_recruit
0
18k
Pwned Labsのすゝめ
ken5scal
0
190
コンテナサプライチェーンセキュリティ
kyohmizu
1
130
OPENLOGI Company Profile for engineer
hr01
1
20k
Windows の新しい管理者保護モード
murachiakira
0
190
Featured
See All Featured
Building Adaptive Systems
keathley
40
2.4k
Designing Experiences People Love
moore
140
23k
A designer walks into a library…
pauljervisheath
205
24k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
33
2.1k
Typedesign – Prime Four
hannesfritz
40
2.5k
Rebuilding a faster, lazier Slack
samanthasiow
80
8.8k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
29
1k
Building Better People: How to give real-time feedback that sticks.
wjessup
367
19k
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
656
59k
Statistics for Hackers
jakevdp
797
220k
How To Stay Up To Date on Web Technology
chriscoyier
790
250k
Embracing the Ebb and Flow
colly
84
4.6k
Transcript
The Open Source Data Tooling Landscape Carol Willing VP of
Learning Noteable web: noteable.io email: carol AT noteable.io twitter: @WillingCarol github: willingc
Headline Slide Sub-headline The 10 Best Practices for Remote Software
Engineering Focusing on the human element of remote software engineer productivity Vanessa Sochat DOI:10.1145/3459613 Attribution: xkcd 1 Today
Common Data Challenges Exploring Solutions with Open Source Data Tools
2 Data
SCALE
SPEED
CONNECTIONS
CHOICES
The Data Pipeline Perspectives Attribution: Red Bull 3 People
The Data Pipeline Executives Opportunity and Fear
The Data Pipeline Engineers Infrastructure and Process Executives Opportunity and
Fear
The Data Pipeline Engineers Infrastructure and Process Data Scientists Algorithms
and Models Executives Opportunity and Fear
The Data Pipeline Engineers Infrastructure and Process Data Scientists Algorithms
and Models Executives Opportunity and Fear Users Productivity and Needs
Attribution: Red Bull Start small...
@WillingCarol 14 Justine Dupont surfs the greatest wave of her
life in Nazaré, Portuga l © Rafael G. Riancho / Red Bull Content Poo l ...and scale.
Open Source Data Tooling Landscape 4 Ecosystem
Python R Julia Fortran SQL C++ Go Rust Java Scala
4 Ecosystem Programming Languages JavaScript TypeScript Data Analysis Workflows Interactivity
4 Ecosystem Data Work fl ow Project Definition Data Collection
Computation and Modeling Evaluation Deploy at Scale Monitoring Data Preparation Exploratory Analysis Share Results Revisit Goals
Challenges ‣ Foundation (existing infrastructure to cloud) ‣ Variability (DIY
to Hosted/Managed Service) ‣ Complexity ‣ Language ecosystems ‣ Growth
Challenges (cont.) ‣ Best practices / de facto standards ‣
Jargon ‣ Abstractions ‣ Hype CRISP-DM Attribution: IBM Cross-industry standard process for data mining 1996
4 Ecosystem Taxonomy Business Goals People Ethics Model creation Training
Testing Project Definition Data Collection Computation and Modeling Cleaning Labeling Validating Data Preparation Ingest Exploratory Analysis Descriptive statistics Visualization Evaluation Deploy at Scale Monitoring Share Results Revisit Goals Charts Reports Dashboard Web app Scheduling CI/CD Platform Metrics Comparison Satisfy goals Automation Infrastructure Model Observability Technical Business Ethical
4 Ecosystem Julia Taxonomy Business Goals People Ethics Model creation
Training Testing Project Definition Data Collection Computation and Modeling Cleaning Labeling Validating Data Preparation Ingest Exploratory Analysis Descriptive statistics Visualization Evaluation Deploy at Scale Monitoring Share Results Revisit Goals Charts Reports Dashboard Web app Workflow Scheduling CI/CD Platform Metrics Comparison Satisfy goals Automation Infrastructure Model Observability Technical Business Ethical DrWatson.jl ParameterSchedulers.jl Pluto.jl IJulia JupyterLab nteract VSCode Plots.jl (Viz) Gadfly.jl (Viz) Makie.jl (Viz - GPU) Flux.jl (ML) Knet.jl (ML/BL) MLJ.jl (ML) Mocha.jl (ML/DL) Tensorflow.jl (ML/DL wrapper) JuMP (optimization) Dataframes.jl ProgressMeters.jl
4 Ecosystem Python Taxonomy Business Goals People Ethics Model creation
Training Testing Project Definition Data Collection Computation and Modeling Cleaning Labeling Validating Data Preparation Ingest Exploratory Analysis Descriptive statistics Visualization Evaluation Deploy at Scale Monitoring Share Results Revisit Goals Charts Reports Dashboard Web app Workflow Scheduling CI/CD Platform Metrics Comparison Satisfy goals Automation Infrastructure Model Observability Technical Business Ethical Dask JupyterHub Binder Kubernetes papermill Dagster Airflow prefect scipy statsmodel JupyterLab nteract VSCode matplotlib seaborn altair plotly numpy scikit-learn pytorch tensorflow pandas PyJanitor dask datasette evidently bokeh panel voila dash python scripts napari geopandas feast keras fastai fairlearn
4 Ecosystem R Taxonomy Business Goals People Ethics Model creation
Training Testing Project Definition Data Collection Computation and Modeling Cleaning Labeling Validating Data Preparation Ingest Exploratory Analysis Descriptive statistics Visualization Evaluation Deploy at Scale Monitoring Share Results Revisit Goals Charts Reports Dashboard Web app Scheduling CI/CD Platform Metrics Comparison Satisfy goals Automation Infrastructure Model Observability Technical Business Ethical RStudio JupyterLab IRkernel ggplot tidyverse dplyr tidyr lubridate readr readxl googlesheets4 ggplot2 rmarkdown Shiny plumber purrr reticulate Keras Tensorflow sparklyr ropensci.org knitr forcats mlr3 CNTK theanos
Algorithmic Business Thinking (ABT) 5 Management Paul McDonagh-Smith MIT Sloan
School of Management https://mitsloan.mit.edu/faculty/directory/paul-mcdonagh-smith https://www.youtube.com/watch?v=bqtn2tYg-kw
@WillingCarol 25 Justine Dupont surfs the greatest wave of her
life in Nazaré, Portuga l © Rafael G. Riancho / Red Bull Content Poo l Got data at scale? Use open source tools.
web: noteable.io email: carol AT noteable.io twitter: @WillingCarol github: willingc
Thank you The Open Source Data Tooling Landscape Carol Willing VP of Learning Noteable
6 Additional Resources https://krzjoa.github.io/awesome-python-data-science/#/ https://github.com/FavioVazquez/ds-cheatsheets https://www.the-modeling-agency.com/crisp-dm.pdf https://github.com/academic/awesome-datascience