Category: Amazon Kinesis

Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and online order transaction data to develop customer order fulfillment applications, improve customer satisfaction, and get insights into sales revenue to create a promotional offer for the customer. It’s essential to store these data points in a centralized data […]

Streaming data is used extensively for use cases like sharing data between applications, streaming ETL (extract, transform, and load), real-time analytics, processing data from internet of things (IoT) devices, application monitoring, fraud detection, live leaderboards, and more. Typically, data streams are stored for short durations of time before being loaded into a permanent data store […]

This is a customer post written by the engineers from German startup Baqend and the AWS EMEA Prototyping Labs team. Baqend is one of the fastest-growing software as a service (SaaS) startups in Germany, serving over 5,000 business customers with more than 100 million monthly users and $2 billion EUR revenue per year. Baqend’s main […]

Data streaming technologies like Apache Kafka and Amazon Kinesis Data Streams capture and distribute data generated by thousands or millions of applications, websites, or machines. These technologies serve as a highly available transport layer that decouples the data-producing applications from data processors. However, the sheer number of applications producing, processing, routing, and consuming data can […]

Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and Internet of Things (IoT) data so that you can develop insights on sensor activity across various industries, including smart spaces, connected factories, smart packing, fitness monitoring, and more. It’s important to store these data points in a centralized […]

Businesses in ecommerce have the challenge of measuring their ad-to-order conversion ratio for ads or promotional campaigns displayed on a webpage. Tracking the number of users that clicked on a particular promotional ad and the number of users who actually added items to their cart or placed an order helps measure the ad’s effectiveness. Utilizing […]

Data is ubiquitous in businesses today, and the volume and speed of incoming data are constantly increasing. To derive insights from data, it’s essential to deliver it to a data lake or a data store and analyze it. Real-time or near-real-time data delivery can be cost prohibitive, therefore an efficient architecture is key for processing, […]

Many organizations are processing and analyzing clickstream data in real time from customer-facing applications to look for new business opportunities and identify security incidents in real time. A common practice is to consolidate and enrich logs from applications and servers in real time to proactively identify and resolve failure scenarios and significantly reduce application downtime. […]

The success of many modern streaming applications depends on the ability to sequentially detect each change as soon as possible after it occurs, while continuing to monitor the data stream as it evolves. Applications of change point detection range across genomics, marketing, and finance, to name a few. In genomics, change point detection can help […]

Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. With Amazon Redshift, you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. When you use Vertica, you have to install and upgrade Vertica database software and manage the […]