A practical guide to synthetic data generation with Gretel and BigQuery DataFrames
In this tutorial, learn how to use Gretel to generate synthetic data with BigQuery DataFrames, a Python client for BigQuery.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
How To Delete Local And Remote Branches In Git: A Complete Guide
Understanding the difference between local and remote branches is crucial for working with Git effectively.
Turbocharging Atlas: How we reduced server initialization time to less than 2 minutes
ThoughtSpot prioritizes the high availability and minimal downtime of our systems to ensure a seamless user experience. In the realm of modern analytics platforms, where rapid and efficient processing of large datasets is essential, swift metadata access and management are critical for optimal system performance. Any delays in metadata retrieval can negatively impact user experience, resulting in decreased productivity and satisfaction.
Combining Automation Frameworks with Design Patterns | Raneesh Chaudhary | #Testflix2024
In this insightful session, Raneesh Chaudhary dives into the world of automation frameworks and how design patterns can empower them to handle more complex, "heavier" lifting. With design patterns as a foundation, scaling becomes a whole lot easier, setting your automation frameworks up for high-impact, long-term success. Raneesh walks us through the practical benefits of incorporating design patterns like the Facade, Factory, and Singleton, each bringing unique strengths to the table—from simplifying complex systems to managing resources efficiently.
New Challenges in Software Quality Brought by GenAI and LLMs | Federico Toledo | #Testflix2024
In this compelling talk, Federico delves into the new challenges in software quality brought by the rise of Generative AI (GenAI) and Large Language Models (LLMs). As these advanced technologies become more integrated into applications, ensuring their quality presents unique hurdles. He explores the specific quality concerns associated with using LLMs, GenAI, and Retrieval-Augmented Generation (RAG), and discuss innovative testing approaches tailored to these systems. This session is designed to help you navigate these complexities, ensuring your applications not only meet but exceed quality standards.
Functional Testing: An In-Depth Overview
To define it simply, we can say- Functional testing ensures every part of an application does exactly what it’s supposed to do. It’s about verifying that the software’s functions and features behave as expected from an end-user’s perspective. And unlike other types of testing, such as performance or load testing, functional testing focuses on the functionality itself rather than factors like speed or stability under load.
KPIs for Cost Management: Evaluating Costs in Databricks
Precise cost forecasting and management are essential, yet 80% of data management experts struggle (Forrester). The challenges stem from a lack of granular visibility, siloed data, and the absence of AI-driven predictive tools.Discover your new set of metrics to understand and optimize your spending with Unravel Data. Watch this Weekly Walkthrough series, FinOps Metrics that Matter, to understand these core metrics to speak the language of both finance and data engineering, and bridge the gap between technical and business stakeholders.
What is an API Ecosystem?
An API ecosystem refers to the interconnected network of applications, services, and APIs that collaborate to enable data exchange, functionality, and interactions between various software components. An API connects all the software developments so they can work together. Developers can connect apps that don’t normally work together, allowing for combined strengths and opportunities to close gaps in product capabilities.
Why CSPs Should Consider Using GPU-as-a-Service
When it comes to building AI models, the process is often oversimplified as “just get a GPU and start building.” While securing access to GPUs can be a challenge, gaining access to GPU clusters is only the beginning of the journey. The real complexity lies in effectively leveraging GPU capabilities to deliver meaningful business impact.
Unlocking Faster Insights: How Cloudera and Cohere can deliver Smarter Document Analysis
Today we are excited to announce the release of a new Cloudera Accelerator for Machine Learning (ML) Projects (AMP) for PDF document analysis, “Document Analysis with Command R and FAISS”, leveraging Cohere’s Command R Large Language Model (LLM), the Cohere Toolkit for retrieval augmented generation (RAG) applications, and Facebook’s AI Similarity Search (FAISS).