KDnuggets

OCTOBER 25, 2024

The richness of Python’s ecosystem has one downside: it makes it difficult to decide which libraries are the best for your needs. This article is an attempt to amend this by suggesting ten (and some more, as a bonus) libraries that are an absolute must in data science.

Data Science 125

Data Science Python Data IT 125

Monte Carlo

OCTOBER 25, 2024

“As he lay awake in his Bay Area apartment, the data leader couldn’t shake the feeling that something wasn’t right. He tried to shut his eyes—to force them closed—but the more the data engineer tried, the more convinced he became. Suddenly, a light appeared from the darkness. It was a Slack from the CEO. She was working late. And the data…it couldn’t be…it looked wrong.

Data Engineering 78

Data Engineering Data Engineer Data Engineering 78

KDnuggets

OCTOBER 25, 2024

Using Python to build engaging and interactive applications where users can pass in an input, get and feedback and make use of multimedia elements such as images, videos, and audio.

Python 106

Python Building Data Science Data 106

databricks

OCTOBER 25, 2024

Discover how the Databricks and XponentL partnership is allowing customers to unlock their FHIR needs. Learn more about dbignite. Imagine you’re feeling.

Data 74

Data Healthcare 74

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Engineering at Meta

OCTOBER 25, 2024

At Meta, we’re always looking for ways to enhance the productivity of our engineers and developers. But how exactly do you measure developer productivity? On this episode of the Meta Tech Podcast Pascal Hartig ( @passy ) sits down with Sarita and Moritz , two engineers at Meta who have been working on Diff Authoring Time (DAT) – a method for measuring how long it takes to submit changes to a codebase.

Engineering 68

Engineering IT 68

Confluent

OCTOBER 25, 2024

Proceed further by establishing your own headless data architecture—formalizing a data access layer at the center of your org, accessible by both analytics and operations.

Data Architecture 59

Data Architecture Architecture Data Accessible 59

Towards Data Science

OCTOBER 25, 2024

How modern trends can be traced back to Conway’s Law Image by the author. (Generated by Midjourney, touched up with Krita) This article was originally posted on my blog [link]. The article was triggered by and riffs on the “Beware of silo specialisation” section of Bernd Wessely’s post Data Architecture: Lessons Learned. It brings together a few trends I am seeing plus my own opinions after twenty years experience working on both sides of the software / data team divide.

Software Engineer 49

Software Engineer Software Engineering Data Analytics Data Engineering 49