In the age of big data, where humans generate 2.5 quintillion bytes of data every single day, organizations like yours have the potential to harness more powerful analytics than ever before. But gathering, organizing, and sorting data still proves a challenge. Put simply, there's too much information and not enough context. The most popular commercial data warehouse solutions like Amazon Redshift say they deliver structured, usable data for businesses. But is this true?

This blog series covers how to run, train, fine-tune, and deploy large language models securely inside your Snowflake Account with Snowpark Container Services This year there has been a surge of progress in the world of open source large language models (LLMs). This world of free and open source LLMs took yet another major step forward just this week with Meta’s release of Llama v2.

Utilizing big data is one of the biggest assets your organization can use to stay ahead of the competition. Even though big data continues to grow, most organizations have yet to leverage its capabilities fully. Why? Because millions of data sources exist on the internet and physically. Ingesting and integrating this data can quickly become overwhelming. With data lakes, you can integrate raw data from multiple sources into one central storage repository.

In this post, we'll configure a Phoenix LiveView application to use a structured logger. We'll then use AppSignal to correlate log events with other telemetry signals, like exception reports and traces. Along the way, you'll learn about the benefits of structured logging, and you'll see how to configure a distinct framework and application logger in your Phoenix app. Let's get started!

In the realm of big data analytics, Hive has been a trusted companion for summarizing, querying, and analyzing huge and disparate datasets. But let’s face it, navigating the world of any SQL engine is a daunting task, and Hive is no exception. As a Hive user, you will find yourself wanting to go beyond surface-level analysis, and deep dive into the intricacies of how a Hive query is executed.

At ThoughtSpot, we believe making data accessible to every knowledge worker requires human-centered technology—an analytics experience that bridges the “language” barrier between technology and people. AI is the perfect compliment to search because it empowers organizations to analyze, understand, and act on data.

Mobile apps are essential for many businesses to reach their target customer. As a result, flawless performance has become a top priority. Mobile testing plays a crucial role in this context by validating an app’s functionality, usability, and security across different devices, operating systems, and network environments. However, choosing the proper testing framework can be daunting due to the sheer number of options available and the unique considerations of each one.

Mastering Salesforce means taking advantage of every tool that can optimize your workflows and improve efficiency. Salesforce offers a few process automation tools that make it easy for you to automate repetitive tasks, such as sending notifications, collecting data, and comparing metrics. Curious to learn more about how Salesforce automation tools work? This complete guide will help everyone in your organization.

Welcome to the world of test automation tools, where efficiency, accuracy, and enhanced test coverage are just a click away. No, really. Automation testing tools offer numerous advantages, including time and cost savings, increased test coverage, improved accuracy, scalability, and the ability to handle complex testing scenarios. By utilizing automation testing tools effectively, organizations can enhance the quality and reliability of their software applications while optimizing their testing efforts.