The data mesh approach has gained popularity over the last couple of years as organizations look for reliable ways to break down data silos. At first, data lakes looked like a good way to improve data management and make information more discoverable. Unfortunately, data lakes — and data warehouses — don’t always conform to business needs. They’re often slow and even unresponsive to queries. Potentially even worse, they can still lead to data silos.

Kipi.bi and Hevo Data have been bringing increased efficiency and maturity into enterprise organizations’ data stacks for years, and both teams are thrilled to formalize their partnership! Both organizations share a keen dedication to enabling data-driven decision-making by allowing businesses to leverage the power of modern data solutions.

This tutorial shows how to use ClearML to manage MONAI experiments. Originating from a project co-founded by NVIDIA, MONAI stands for Medical Open Network for AI. It is a domain-specific open-source PyTorch-based framework for deep learning in healthcare imaging. This blog shares how to use the ClearML handlers in conjunction with the MONAI Toolkit. To view our code example, visit our GitHub page.

In the competitive landscape of iOS app development, ensuring the quality and functionality of your application is crucial. That’s where automated testing tools come in, enabling developers to streamline their testing processes and deliver robust, bug-free applications. In this comprehensive overview, we dive into the world of automated testing tools for iOS, exploring the top contenders that can revolutionize your testing efforts.

Natural language processing and large language models to help BigQuery process dataframes.

The Apigee API Gateway is a tool that enables the management, analysis, and security of APIs. This API gateway enables organizations to optimize their digital ecosystems and deploy user-friendly products. It is particularly valuable for developers, IT professionals, and SaaS businesses interested in enhancing their API infrastructure, streamlining development workflows, and ensuring secure and seamless connectivity.

The rise of generative AI and the massive popularity of OpenAI’s ChatGPT has led to widespread recognition that software applications are about to fundamentally change. Generative AI offers the potential to both deliver breakthrough new application capabilities and transform the way people interact with software.

Helping companies leverage their data to make better decisions and improve their performance is something we strive for at Databox. Until recently, this type of analysis has only been reserved for larger enterprises with dedicated teams and budgets for complex tools. Fortunately, recent innovations are reshaping this landscape.

One of the main value propositions of the Moesif product is the fact that it works so well with a wide variety of tools. One such tool – Logstash – is an incredibly powerful solution for managing events and logs. Understanding how to pull Logstash logs into Moesif is a critical function for any business utilizing Logstash at scale. Today, we’re going to look at how to log API calls from Logstash using the HTTP Output plugin for import into Moesif.