AWS Big Data Blog

Tag: Data Lake

Build a Data Lake Foundation with AWS Glue and Amazon S3

A data lake is an increasingly popular way to store and analyze data that addresses the challenges of dealing with massive volumes of heterogeneous data. A data lake allows organizations to store all their data—structured and unstructured—in one centralized repository. Because data can be stored as-is, there is no need to convert it to a predefined schema. This post walks you through the process of using AWS Glue to crawl your data on Amazon S3 and build a metadata store that can be used with other AWS offerings.

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From Data Lake to Data Warehouse: Enhancing Customer 360 with Amazon Redshift Spectrum

Achieving a 360o-view of your customer has become increasingly challenging as companies embrace omni-channel strategies, engaging customers across websites, mobile, call centers, social media, physical sites, and beyond. The promise of a web where online and physical worlds blend makes understanding your customers more challenging, but also more important. Businesses that are successful in this […]

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Building a Real World Evidence Platform on AWS

Deriving insights from large datasets is central to nearly every industry, and life sciences is no exception. To combat the rising cost of bringing drugs to market, pharmaceutical companies are looking for ways to optimize their drug development processes. They are turning to big data analytics to better quantify the effect that their drug compounds […]

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New AWS Training: Building a Serverless Data Lake

by Sara Snedeker | on | Permalink | Comments |  Share

AWS Training allows you to learn from the experts so that you can advance your knowledge with practical skills and get more out of the AWS Cloud. We are adding one of our most popular event boot camps, Building a Serverless Data Lake, to our permanent instructor-led training portfolio. This one-day course is designed to […]

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Amazon Redshift Spectrum Extends Data Warehousing Out to Exabytes—No Loading Required

When we first looked into the possibility of building a cloud-based data warehouse many years ago, we were struck by the fact that our customers were storing ever-increasing amounts of data, and yet only a small fraction of that data ever made it into a data warehouse or Hadoop system for analysis. We saw that […]

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Visualize Big Data with Amazon QuickSight, Presto, and Apache Spark on Amazon EMR

Last December, we introduced the Amazon Athena connector in Amazon QuickSight, in the Derive Insights from IoT in Minutes using AWS IoT, Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight post. The connector allows you to visualize your big data easily in Amazon S3 using Athena’s interactive query engine in a serverless fashion. This turned […]

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Top 10 Performance Tuning Tips for Amazon Athena

This blog post has been translated into Japanese.  Amazon Athena is an interactive query service that makes it easy to analyze data stored in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply […]

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Derive Insights from IoT in Minutes using AWS IoT, Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight

Ben Snively is a Solutions Architect with AWS Speed and agility are essential with today’s analytics tools. The quicker you can get from idea to first results, the more you can experiment and innovate with your data, perform ad-hoc analysis, and drive answers to new business questions. Serverless architectures help in this respect by taking […]

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Introducing the Data Lake Solution on AWS

by Nick Corbett | on | Permalink | Comments |  Share

This blog post has been translated into Japanese.  Many of our customers choose to build their data lake on AWS. They find the flexible, pay-as-you-go, cloud model is ideal when dealing with vast amounts of heterogeneous data. While some customers choose to build their own lake, many others are supported by a wide range of […]

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Optimizing Amazon S3 for High Concurrency in Distributed Workloads

Aaron Friedman is a Healthcare and Life Sciences Solution Architect with Amazon Web Services The healthcare and life sciences landscape is being transformed rapidly by big data. By intersecting petabytes of genomic data with clinical information, AWS customers and partners are already changing healthcare as we know it. One of the most important things in […]

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