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As enterprise AI technologies rapidly reshape our digital environment, the foundation of your cloud infrastructure is more critical than ever. That’s why Cloudera and Red Hat, renowned for their open-source solutions, have teamed up to bring Red Hat Enterprise Linux (RHEL) to Cloudera on public cloud as the operating system for all of our public cloud platform images. Let’s dive into what this means and why it’s a game-changer for our customers.

Why did we choose MongoDB for our projects? Here’s a quick overview of the five big reasons that convinced us. From its perfect fit with JavaScript to its unmatched flexibility and growth.

Need to connect to NetSuite’s rich data pools through your applications? The NetSuite ODBC driver bridges this gap. This article walks you through installation, configuration, and usage for optimal data integration, including troubleshooting tips for common issues you might encounter.

Introducing new BigQuery SQL features for performing two of the most common time-series operations: windowing and gap filling.

Having frequently worked with governments around the world over the course of my career, I’ve had all kinds of discussions about the global impact of generative AI. Today, I’m publicly wading into those waters to deliver my perspective, and my opinion is that … it’s incredibly hard to predict the future. Done. Wrapped up this entire post in a single sentence.

Snowflake is committed to helping our customers unlock the power of artificial intelligence (AI) to drive better decisions, improve productivity and reach more customers using all types of data. Large Language Models (LLMs) are a critical component of generative AI applications, and multimodal models are an exciting category that allows users to go beyond text and incorporate images and video into their prompts to get a better understanding of the context and meaning of the data.

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

According to a study by Statista, the cloud storage market was valued at $90.17 billion in 2022 and will reach a value of $472.47 billion by 2030. These figures indicate a growing shift toward cloud computing and data storage solutions. A typical scenario in modern data management involves data transfer from cloud storage to cloud-based computing platforms. Amazon’s Simple Storage Service (S3) is among the go-to options for the former, and businesses trust Snowflake for the latter.

Considering BigQuery vs. Redshift for your data warehousing needs? This guide is for you. Both BigQuery and Redshift stand as leading cloud data warehouse solutions each offering a multitude of features catering to multiple use cases. Google’s BigQuery offers seamless scalability and performance within its cloud platform, while Amazon’s Redshift provides great parallel processing and tuning options.

In this article, we present some best practices and key concepts for using Confluent Schema Registry.