Remove machine-learning-in-production-software-architecture
article thumbnail

What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. This post (1 of 5) is the beginning of a series that explores the benefits and challenges of implementing a data mesh and reviews lessons learned from a pharmaceutical industry data mesh example.

article thumbnail

11 most in-demand gen AI jobs companies are hiring for

CIO Business Intelligence

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Insiders

Sign Up for our Newsletter

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

article thumbnail

#ClouderaLife Spotlight: Amogh Desai, Software Engineer II

Cloudera

This month’s #ClouderaLife Spotlight features software engineer Amogh Desai. Snatching victory from the jaws of defeat Amogh and his fellow hackathon team members felt the rush of victory after winning Cloudera’s 2022 global hackathon in the product development category. At the time the product was still in its infancy.

article thumbnail

IBM Cloud solution tutorials: 2023 in review

IBM Big Data Hub

Platform engineering, internal development platform – Platform engineering is at the forefront of modern software development, driving innovation and collaboration across teams. This year, IBM Cloud introduced projects and deployable architectures. This year, IBM Cloud introduced projects and deployable architectures.

article thumbnail

Unleashing the potential: 7 ways to optimize Infrastructure for AI workloads 

IBM Big Data Hub

Enterprises have reported a 30% productivity gain in application modernization after implementing Gen AI. In this blog, we’ll explore seven key strategies to optimize infrastructure for AI workloads, empowering organizations to harness the full potential of AI technologies.

article thumbnail

Connected products at the edge

IBM Big Data Hub

But there is one very practical and promising use case that has been commonly deployed without many people thinking about it: connected products. This use case involves devices and equipment embedded with sensors, software and connectivity that exchange data with other products, operators or environments in real-time.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists.