Remove Case Study Remove Data Engineering Remove Scalability
article thumbnail

The best way to start an AI project? Don’t think about the models

TechCrunch

Executives should, of course, have in mind a clear idea of the problem they want to solve as well as a business case. But the AI core team should include at least three personas, all of which will be equally important for the success of the project: data scientist, data engineer and domain expert.

article thumbnail

How to Screen and Interview Fintech Data Engineer

Mobilunity

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Insiders

Sign Up for our Newsletter

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

article thumbnail

How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

Netflix Tech

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. Give us a holler if you are interested in a thought exchange.

article thumbnail

Data Gravity in Cloud Networks: Distributed Gravity and Network Observability

Kentik

Tenets of network observability A detailed explanation of network observability itself is out of the scope of this article, but I want to focus on its core tenets before exploring a couple of brief case studies. Network observability, when properly implemented, enables operators to: Ingest telemetry from every part of the network.

Network 99
article thumbnail

Technology Trends for 2025

O'Reilly Media - Ideas

Building applications with RAG requires a portfolio of data (company financials, customer data, data purchased from other sources) that can be used to build queries, and data scientists know how to work with data at scale. Data engineers build the infrastructure to collect, store, and analyze data.

Trends 132
article thumbnail

How Scalable Architecture Boosts DDoS Detection Accuracy

Kentik

How Scalable Architecture Boosts Accuracy in Detection. This scalable, adaptive approach to monitoring and anomaly detection has been field-proven to be far more accurate than legacy approaches. For more detail, read our PenTeleData case study. Deep analytics.

article thumbnail

New live online training courses

O'Reilly Media - Ideas

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 94