Systems | Development | Analytics | API | Testing

Everyone associated with Business Intelligence (BI) applications is talking about their Artificial Intelligence (AI) journey and the integration of AI in analytics. Artificial intelligence encompasses a broad spectrum of categories, including machine learning, natural language processing, computer vision, and automated insights. ThoughtSpot has been a leader in augmented analytics, leveraging AI to automate insights and empower users to make data-driven decisions.

Open table formats offer enterprises the capabilities of data warehouses and the flexibility of data lakes.

Centralized data allows data teams to dedicate their effort to last-mile analytics and AI challenges.

Quality engineering and assurance efforts, and testing as a part of those, have never been more critical than they are today.

First published on platformengineering.com. Application modernization has become a critical initiative for organizations looking to remain competitive in today’s rapidly evolving digital landscape. As businesses embrace cloud computing, microservices and AI-driven automation, modernizing legacy applications is no longer optional. It’s essential for scalability, agility and innovation.

If you’re building AI systems—whether for personalization, fraud detection, or predictive analytics—you already know the brutal truth: your models are only as good as the data you feed them. Enter Countly, an analytics platform that doesn’t just collect user data but transforms it into rocket fuel for AI. This isn’t about explaining what Countly does (AI can do that for you).

ClearML, Latent AI, and Carahsoft recently teamed up to talk about how teams can innovate, adapt, and collaborate in service of their mission goals by utilizing emerging AI technologies. If you couldn’t attend, you’re in luck!

Cloud computing has reshaped the digital landscape, offering unparalleled scalability, flexibility, and cost-effectiveness to businesses worldwide. Imagine entrusting your most valuable possessions to a high-tech, automated storage facility—accessible anytime, anywhere, but also potentially vulnerable if not adequately protected. This analogy perfectly encapsulates cloud computing: convenient, yet requiring robust security measures to guard against threats.

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. As a finance professional, you’ll need different types of financial analysis and modeling for different situations.

If you’re part of an IT team tasked with supporting your organization’s AI ambitions, you already know the headaches: complex security setups, manual configurations, and the constant pressure to keep sensitive data and models secure. Good news! ClearML just made your life a lot easier. We’re excited to announce that we’ve just rolled out advanced new IT governance and security controls.