Category: Amazon Athena

The University of California, Irvine (UCI) is a public land-grant research university with troves of research data stored on servers in lab environments on about 1500 faculty-research lab environments on campus. UCI needed a solution to address the practical and economic challenge of providing a centralized backups for these independently-administered servers. The goal for the […]

When was the last time you found yourself trying to look at rows and rows of data in a spreadsheet struggling to interpret and draw conclusions? Many analysts and engineers experience the same challenge every day. Whether it’s analyzing sales trends, monitoring operational metrics, or understanding customer behavior, the challenge lies not just in interpreting […]

Pendulum is an AI-powered analytics platform that aggregates and analyzes real-time data from social media, news, and podcasts. Designed to help organizations stay ahead, it enables reputation monitoring, early crisis detection, and influencer activity tracking. Using machine learning (ML) enables Pendulum to surface key insights from multiple channels, providing a comprehensive view of the digital […]

Amazon S3 redefined data storage when it launched as the first generally available AWS service in 2006 to deliver highly reliable, durable, secure, low-latency storage with virtually unlimited scale. While designed to deliver simple storage, S3 has proven to be built to handle the explosive growth of data we have seen in the last 19 […]

As businesses continue to rely on data-driven decision-making, there’s an increasing demand for tools that streamline and accelerate the process of data analysis. Efficiency and simplicity in application architecture can serve as a competitive edge when driving high-stakes decisions. Developers are seeking lightweight, flexible tools that seamlessly integrate with their existing application stack, specifically solutions […]

Organizations are modernizing data platforms to use generative AI by centralizing data from various sources and streaming real-time data into data lakes. A strong data foundation, such as scalable storage, reliable ingestion pipelines, and interoperable formats, is critical for businesses to discover, explore, and consume data. As organizations modernize their platforms, they often turn to […]

Organizations today seek data analytics solutions that provide maximum flexibility and accessibility. Customers need their data to be readily available using their preferred query engines, and break down barriers across different computing environments. At the same time, they want a single copy of data to be used across these solutions, to track lineage, be cost […]

Businesses are increasingly adopting real-time data processing to stay ahead of user expectations and market changes. Industries such as retail, finance, manufacturing, and smart cities are using streaming data for everything from optimizing supply chains to detecting fraud and improving urban planning. The ability to use data as it is generated has become a critical […]

Modern data lakes integrate with multiple engines to meet a wide range of analytics needs, from SQL querying to stream processing. A key enabler of this approach is the adoption of Apache Iceberg as the open table format for building transactional data lakes. However, as the Iceberg ecosystem expands, the growing variety of engines and languages has […]

UPDATE (1/27/2025): Amazon S3 Metadata is generally available. Object storage provides virtually unlimited scalability, but managing billions, or even trillions, of objects can pose significant challenges. How do you know what data you have? How can you find the right datasets at the right time? By implementing a robust metadata management strategy, you can answer these […]