What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)| Listen on Anghami

Apr 21

Europe, wake up! You Can't Be a Superpower on Someone Else's Servers (Ep. 304)

Rebuilding a defense industrial base takes 20 years and costs trillions. Tech sovereignty takes 3 years and political will. Europe is doing the hard thing and refusing the easy one. Here's why — and who's profiting from that refusal. Buy me a coffee https://ko-fi.com/datascience ... Show More

28m 11s

Apr 7

Social media is an ant mill (Internet is a disaster) (Ep. 303)

Internet followed nature. Until it didn't. And became the disaster we know. Buy me a coffee https://ko-fi.com/datascience ✨ Connect with us! Personal newsletter: https://defragzone.substack.com 📩 Newsletter: https://datascienceathome.substack.com 🎙 Podcast: Available on Spotify ... Show More

33m 39s

Apr 2

About Apple's Privacy (Ep. 302)

Paragon's spyware hacked fully updated iPhones without a single click. Apple just spent $2B on tech that reads your silent speech. And your iCloud? Governments can request it with paperwork. This is what the privacy brand actually buys you. Buy me a coffee https://ko-fi.com/datas ... Show More

45m 40s

Sep 2021

Massively Parallel Data Processing In Python Without The Effort Using Bodo

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Python has beome the de facto language for working with data. That has brought with it a number of challenges having to do with the speed and scalability of working with large volumes of information.There have been many ... Show More

1h 4m

Mar 2024

#454: Data Pipelines with Dagster

See the full show notes for this episode on the website at <a href="https://talkpython.fm/454">talkpython.fm/454</a>

58m 25s

Nov 2022

Analyze Massive Data At Interactive Speeds With The Power Of Bitmaps Using FeatureBase

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>The most expensive part of working with massive data sets is the work of retrieving and processing the files that contain the raw information. FeatureBase (formerly Pilosa) avoids that overhead by converting the data int ... Show More

59m 25s

Dec 2019

Building The Materialize Engine For Interactive Streaming Analytics In SQL

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Transactional databases used in applications are optimized for fast reads and writes with relatively simple queries on a small number of records. Data warehouses are optimized for batched writes and complex analytical qu ... Show More

48m 7s

Jul 2023

#422: How data scientists use Python

See the full show notes for this episode on the website at <a href="https://talkpython.fm/422">talkpython.fm/422</a>

1h 2m

Sep 2022

#382: Apache Superset: Modern Data Exploration Platform

See the full show notes for this episode on the website at <a href="https://talkpython.fm/382">talkpython.fm/382</a>

1h 8m

Nov 2021

Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. With the improvements in streaming engines it is now possible to perform all of your data integration in near r ... Show More

52m 53s

Aug 2023

#425: Memray: The endgame Python memory profiler

See the full show notes for this episode on the website at <a href="https://talkpython.fm/425">talkpython.fm/425</a>

1h 10m

Oct 2023

Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

<h2>Summary</h2> <p>Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. Decodable was built with a mission of eliminat ... Show More

1h 8m

What data transformation library should ...