AWS Big Data Blog

Category: Artificial Intelligence

Data: The genesis for modern invention

It only takes one groundbreaking invention—one iconic idea that solves a widespread pain point for customers—to create or transform an industry forever. From the invention of the telegraph, to the discovery of GPS, to the earliest cloud computing services, history is filled with examples of these “eureka” moments that continue to have long-lasting impacts on […]

Design a data mesh with event streaming for real-time recommendations on AWS

This blog post was co-authored with Federico Piccinini. The data landscape has been changing in recent years: there is a proliferation of entities producing and consuming large quantities of data within companies, and for most of them defining a proper data strategy has become of fundamental importance. A modern data strategy gives you a comprehensive […]

How Fresenius Medical Care aims to save dialysis patient lives using real-time predictive analytics on AWS

This post is co-written by Kanti Singh, Director of Data & Analytics at Fresenius Medical Care. Fresenius Medical Care is the world’s leading provider of kidney care products and services, and operates more than 2,600 dialysis centers in the US alone. The company provides comprehensive solutions for people living with chronic kidney disease and related […]

Build a multilingual dashboard with Amazon Athena and Amazon QuickSight

Amazon QuickSight is a serverless business intelligence (BI) service used by organizations of any size to make better data-driven decisions. QuickSight dashboards can also be embedded into SaaS apps and web portals to provide interactive dashboards, natural language query or data analysis capabilities to app users seamlessly. The QuickSight Demo Central contains many dashboards, feature showcase […]

Use a linear learner algorithm in Amazon Redshift ML to solve regression and classification problems

Amazon Redshift is the fastest, most widely used, fully managed, and petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Amazon Redshift ML, powered by Amazon SageMaker, makes it easy for SQL users such as data analysts, data scientists, and […]

Secure data movement across Amazon S3 and Amazon Redshift using role chaining and ASSUMEROLE

Data lakes use a ring of purpose-built data services around a central data lake. Data needs to move between these services and data stores easily and securely. The following are some examples of such services: Amazon Simple Storage Service (Amazon S3), which stores structured, unstructured, and semi-structured data Amazon Redshift, a fully managed, petabyte-scale data […]

Use Amazon CodeGuru Profiler to monitor and optimize performance in Amazon Kinesis Data Analytics applications for Apache Flink

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data and gain actionable insights in real time with Apache Flink. Apache Flink is an open-source framework and engine for processing data streams in real time. Kinesis Data Analytics reduces the complexity of building and managing Apache Flink applications using open-source libraries and […]

Solution Architecture

Build and deploy custom connectors for Amazon Redshift with Amazon Lookout for Metrics

Amazon Lookout for Metrics detects outliers in your time series data, determines their root causes, and enables you to quickly take action. Built from the same technology used by Amazon.com, Lookout for Metrics reflects 20 years of expertise in outlier detection and machine learning (ML). Read our GitHub repo to learn more about how to […]

How Cynamics built a high-scale, near-real-time, streaming AI inference system using AWS

This post is co-authored by Dr. Yehezkel Aviv, Co-Founder and CTO of Cynamics and Sapir Kraus, Head of Engineering at Cynamics. Cynamics provides a new paradigm of cybersecurity — predicting attacks long before they hit by collecting small network samples (less than 1%), inferring from them how the full network (100%) behaves, and predicting threats […]

Backtest trading strategies with Amazon Kinesis Data Streams long-term retention and Amazon SageMaker

Real-time insight is critical when it comes to building trading strategies. Any delay in data insight can cost lot of money to the traders. Often, you need to look at historical market trends to predict future trading pattern and make the right bid. More the historical data you analyze, better trading prediction you get. Back […]