Remove Analytics Remove Cloud Remove Scalability
article thumbnail

Cloud analytics migration: how to exceed expectations

CIO

A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making.

Analytics 146
article thumbnail

Revolutionizing data management: Trends driving security, scalability, and governance in 2025

CIO

The evolution of cloud-first strategies, real-time integration and AI-driven automation has set a new benchmark for data systems and heightened concerns over data privacy, regulatory compliance and ethical AI governance demand advanced solutions that are both robust and adaptive.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

The AI Future According to Google Cloud Next ’25: My Interesting Finds

Xebia

Google Cloud Next 2025 was a showcase of groundbreaking AI advancements. Native Multi-Agent Architecture: Build scalable applications by composing specialized agents in a hierarchy. bigframes.pandas provides a pandas-compatible API for analytics, and bigframes.ml BigFrames 2.0 offers a scikit-learn-like API for ML.

article thumbnail

A look at the future of mainframe modernization with hybrid cloud

CIO

At the same time, many organizations have been pushing to adopt cloud-based approaches to their IT infrastructure, opting to tap into the speed, flexibility, and analytical power that comes along with it. It’s a decision that maps back to the overarching goals of a business and how they want to leverage their data.

Cloud 167
article thumbnail

Best Practices for Deploying & Scaling Embedded Analytics

Embedding analytics in your application doesn’t have to be a one-step undertaking. Read more about how to simplify the deployment and scalability of your embedded analytics, along with important considerations for your: Environment Architecture: An embedded analytics architecture is very similar to a typical web architecture.

article thumbnail

Bridging the gap between mainframe data and hybrid cloud environments

CIO

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Without integrating mainframe data, it is likely that AI models and analytics initiatives will have blind spots. It enhances scalability, flexibility, and cost-effectiveness, while maximizing existing infrastructure investments.

Cloud 147
article thumbnail

What is data architecture? A framework to manage data

CIO

Cloud storage. Not all data architectures leverage cloud storage, but many modern data architectures use public, private, or hybrid clouds to provide agility. Cloud computing. In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data.