Fri.Aug 25, 2023

article thumbnail

Things You Should Know When Scaling Your Web Data-Driven Product

KDnuggets

Scaling your data-driven product helps grow your business, but it requires certain expertise. In this article, you will learn how scaling works and what to keep in mind while doing it.

Data 92
article thumbnail

Streamlit and MongoDB: Storing Your Data in the Cloud

Towards Data Science

Deploying your Streamlit app to the Cloud means that any data that you create with that app disappears when the app terminates — unless… Continue reading on Towards Data Science »

MongoDB 87
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

7 Projects Built with Generative AI

KDnuggets

Learn how to build a strong portfolio with personal projects using Generative AI. This will help you to stand out from the crowd!

Project 99
article thumbnail

Developing a Career at Confluent: Collaboration Is Key

Confluent

Senior software engineer Yash Mayya talks about his career path to Confluent and working on Kafka Connect.

Kafka 98
article thumbnail

Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

article thumbnail

How to Ace Data Scientist Professional Certificate Exam

KDnuggets

Gain insights into the certification process and expert tips for passing the certificate exam.

article thumbnail

How I Built A Cascading Data Pipeline Based on AWS (Part 2)

Towards Data Science

Automatic, scalable, and powerful Continue reading on Towards Data Science »

article thumbnail

Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences

Monte Carlo

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs.