The advancement and widespread availability of new artificial intelligence (AI) capabilities—through platforms like the Databricks Data Intelligence Platform and Mosaic AI—has completely reset expectations for engineering teams across every industry. Business now moves at a new pace, demanding rapid delivery of intelligent, real-time applications—instead of slowly stitched-together systems solving problems defined and scoped months prior.

At Qlik Connect 2025, Qlik unveiled their much-anticipated write back functionality, a welcome addition to their analytics platform, promising real-time collaboration and a streamlined data-entry experience. While this announcement marks Qlik’s entry into the world of write back capabilities, it’s clear their newly introduced functionality is designed for basic use cases.

In today's data-driven world, organizations must efficiently manage and transform their data to gain valuable insights. Data orchestration and ETL (Extract, Transform, Load) are two popular approaches to data management, each with distinct capabilities and purposes. Data orchestration manages the entire workflow of data processes across an enterprise, while ETL focuses specifically on extracting data from sources, transforming it, and loading it into destination systems.

Microsoft Power BI has historically been the default choice for organizations looking to visualize data and generate reports. It’s a capable tool, and no one disputes that. But as businesses scale, especially those embedding analytics into their own software applications, Power BI’s limitations start to show. At some point companies feel the need to reevaluate their business intelligence (BI) strategy, not because the tools they use are "bad," but because their data needs have evolved.

As IT leaders race to keep up with the demands of cloud computing, big data and especially AI, the energy consumption and efficiency of their data centers has become a major concern. This is where the sustainability of their data storage infrastructure comes into focus. Shifting from what may have once been seen as a tactical necessity, to become a strategic imperative for meeting an organization’s operational AND environmental objectives.

By Erez Schnaider, Technical Product Marketing Manager, ClearML.

As a product leader, you're always looking for ways to stay ahead of the curve, meet evolving customer needs, and keep your product competitive. But with tight budgets, growing pressure to innovate, and constantly changing demands, it’s not always easy. Embedding AI-powered analytics into your application can be a powerful way to overcome these challenges and add more value for your users. But why is this approach so crucial, and how can you implement it effectively?