Category: Amazon S3 Tables

Data scientists and engineers spend hours writing complex data pipelines to extract, transform, and load (ETL) data from various sources into their data lakes for data integration and creating unified data models to build business insights. The process involves understanding the source and target systems, discovering schemas, mapping source and target, writing and testing ETL […]

Organizations face mounting challenges in managing and operationalizing their ever-growing data assets for machine learning and analytics workflows. When dealing with billions and trillions of objects, teams struggle to find what data they have and how to efficiently find specific datasets. Without proper data discovery and metadata management, teams spend valuable time searching for relevant […]

Zeta Global is a data-driven marketing technology company that uses consumer insights to empower brands in customer acquisition, growth, and retention. At the core of its operations is the Zeta Marketing Platform, an advanced system that applies sophisticated AI and machine learning (ML) capabilities on proprietary data from over 245 million U.S. consumer profiles. This […]

Modern cybersecurity teams are facing unprecedented challenges in data analysis by the scale, complexity, and velocity of data. Cloud environments continuously generate massive amounts information in form of access logs, configuration changes, alerts, and telemetry. Traditional analysis methods of looking at these data points in isolation can’t effectively detect threats such as lateral movement and […]

In today’s data-driven world, the ability to interact with your data through natural language is becoming increasingly valuable. By combining the power of conversational AI with Amazon S3 Tables, organizations can democratize data access and enable individuals across technical skill levels to query, analyze, and gain insights from their data using simple conversations. Model Context […]

Organizations are increasingly focused on addressing the growing challenge of managing and analyzing vast data volumes, while making sure that their data teams have timely access to this data to enable rapid insights and decision-making. Data analysts and scientists need self-service analytics capabilities to build and maintain data products, often involving complex transformations and frequent […]

Organizations often struggle to extract maximum value from their data lakes when running generative AI and analytics workloads due to data quality challenges. Although data lakes excel at storing massive amounts of raw, diverse data, they need robust governance and management practices to prevent common quality issues. Without proper data validation, cleansing processes, and ongoing […]

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 […]