ETL Frameworks in 2025 for Robust, Future-Proof Data Pipelines

ETL (Extract, Transform, Load) frameworks have evolved significantly over the past two decades. In 2025, as data pipelines expand across cloud platforms, real-time systems, and regulatory constraints, the architecture and flexibility of ETL frameworks are more critical than ever. This post explores the key principles, features, and operational concerns that modern data professionals need to understand to build effective, scalable ETL frameworks for data engineering use cases.

Real-Time Data Processing in 2025 and Beyond

In 2025, data doesn’t just support the business — it drives it. That means real-time decision-making is no longer optional. From fraud detection and customer engagement to predictive maintenance and logistics optimization, real-time data processing is the foundation of business agility. Yet many professionals still struggle with legacy bottlenecks: batch ETL jobs, siloed data, and limited pipeline observability.

PostgreSQL CDC for Real-Time Data Replication

In the era of real-time data, Change Data Capture (CDC) in PostgreSQL has become a critical capability for organizations aiming to sync systems, trigger events, and power analytics with fresh, consistent data. This guide will take you through the core concepts, methods, tools, and best practices of how to enable CDC in PostgreSQL instance, making it easier for you to build efficient, reliable, and scalable data pipelines.

How to Achieve Secure, Scalable Multi-tenancy for GPU Infrastructure

By Erez Schnaider, Technical Product Marketing Manager, ClearML In a previous blog post, we laid the foundations for understanding multi-tenancy in GPU-access infrastructure and highlighted its critical importance. In this post, we’ll dive into ClearML’s approach to achieving secure and efficient multi-tenancy. At a high level, multi-tenancy refers to the ability to share a single resource pool, typically GPU or CPU clusters, across multiple, logically isolated entities known as tenants.

Data-driven admissions: Optimizing enrollment with automation

Universities must integrate scalable, automated data solutions to centralize information, reduce inefficiencies, and enhance decision-making, ensuring a seamless, student-centric experience. To discuss how to do just that, Ilia Xheblati, Director of Analytics Engineering at Northeastern University, joined us to get to the heart of embracing scalable, automated data solutions so universities can eliminate inefficiencies, streamline decision-making, and create a more connected, student-centric experience.

Ep 22 | Lessons in Tech and the Two-Way Street of Mentorship with AWS's Melissa Dougherty

As part of our Women Leaders in Technology (WLIT) series on The AI Forecast, we’re joined by Melissa Dougherty, Global Managing Director of Partner Sales, Financial Services. Each quarter, we’ll take a break from the regularly scheduled AI programming on The AI Forecast to direct our attention to this important topic in tech.

The AI-Driven Enterprise Advantage with Teresa Tung, Global Data Capabilities Lead at Accenture

In this episode, Dana Gardner, Principal Analyst at Interarbor Solutions is joined by Teresa Tung, Global Data Capabilities Lead at Accenture. They discuss how enterprises can accelerate and broaden the application of data to attain more business value through agentic AI, the pivotal role of proprietary data as a competitive advantage, and the need for data practitioners to adapt to new responsibilities involving data quality and AI agent interaction.