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.

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.

With its simplicity, flexibility, and cost-efficient characteristics, Amazon Simple Storage Service (Amazon S3) cloud object storage has become the preferred platform for collecting, analyzing, and retaining today’s growing mountain of diverse and disjointed enterprise data. And as Amazon Web Services (AWS) continues to grab market share in the hyperscale IaaS/PaaS/SaaS marketplace, organizations of every size are leveraging Amazon S3 to underpin a variety of use cases, such as.

Big data is more crucial to businesses than ever, especially with the rise of artificial intelligence (AI) and machine learning technologies across multiple industries. The expanding internet of things (IoT) plus the multiple digital engagement points between businesses and customers create huge swathes of data and new challenges in how to manage this glut of information.

Next year, finance teams utilizing SAP will face unparalleled pressure due to a confluence of economic challenges. The demand for actionable insights will grow amidst a landscape marred by economic recession and escalating inflation rates. These adversities heighten the necessity for finance professionals to adeptly translate raw data into strategic guidance.

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.