AWS Partner Network (APN) Blog

Tag: Amazon Athena

Reducing the Cost of Managing Multiple AWS Accounts Using AWS Control Tower

As larger and more complex workloads are deployed on AWS, multi-account solutions are an increasingly common architectural blueprint. Often referred to as cloud “landing zones,” these blueprints enable simple administrative boundaries. However, using multiple accounts increases the complexity of security tooling, access control and authorization, and cross-account networking. AWS Control Tower simplifies the process of setting up multi-account environments with predefined security baseline templates.

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Building a Data Processing and Training Pipeline with Amazon SageMaker

Next Caller uses machine learning on AWS to drive data analysis and the processing pipeline. Amazon SageMaker helps Next Caller understand call pathways through the telephone network, rendering analysis in approximately 125 milliseconds with the VeriCall analysis engine. VeriCall verifies that a phone call is coming from the physical device that owns the phone number, and flags spoofed calls and other suspicious interactions in real-time.

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Running SQL on Amazon Athena to Analyze Big Data Quickly and Across Regions

Data is the lifeblood of a digital business and a key competitive advantage for many companies holding large amounts of data in multiple cloud regions. Imperva protects web applications and data assets, and in this post we examine how you can use SQL to analyze big data directly, or to pre-process the data for further analysis by machine learning. You’ll also learn about the benefits and limitations of using SQL, and see examples of clustering and data extraction.

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How Steamhaus Used AWS Well-Architected to Improve Sperry Rail’s Artificial Intelligence System

Over two days, Steamhaus conducted an AWS Well-Architected Review on-site with the team who designed, built, and currently manage Elmer at Sperry Rail. Elmer uses machine intelligence to inspect thousands of miles of ultrasound scans collected by Sperry’s inspection vehicles, searching for evidence of cracks in the rail. This partnership allowed quick improvements in efficiency, while ensuring the requirements of running the business day-to-day did not get in the way of improving Elmer.

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Gathering Market Intelligence from the Web Using Cloud-Based AI and ML Techniques

Many organizations face the challenge of gathering market intelligence on new product and platform announcements made by their partners and competitors—and doing so in a timely fashion. Harnessing these insights quickly can help businesses react to specific industry trends and fuel innovative products and offerings inside their own company.Learn how Accenture helped a customer use AWS to gather critical insights along with key signals and trends from the web using AI and ML techniques.

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Improving Dataset Query Time and Maintaining Flexibility with Amazon Athena and Amazon Redshift

Analyzing large datasets can be challenging, especially if you aren’t thinking about certain characteristics of the data and what you’re ultimately looking to achieve. There are a number of factors organizations need to consider in order to build systems that are flexible, affordable, and fast. Here, experts from CloudZero walk through how to use AWS services to analyze customer billing data and provide value to end users.

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AWS Partner Network

The Most Viewed APN Blog Posts in 2019

Take a look at the most popular APN Blog posts in 2019. Our goal with this blog is to share timely and relevant news, technical solutions, partner success stories, and more from Amazon Web Services and the AWS Partner Network (APN) specifically. The APN is the global partner program for AWS and helps tens of thousands of organizations across the world build, market, and sell their AWS-based offerings. Thank you for reading, and Happy New Year!

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How to Enable Mainframe Data Analytics on AWS Using Model9

Mainframe proprietary storage solutions such as VTLs hold valuable data locked in a platform with complex tools. This can lead to higher compute and storage costs, and make it harder to retain existing employees or train new ones. When mainframe data is stored in a cloud storage service, however, it can be accessed by a rich ecosystem of applications and analytics tools. Model9 enables mainframe customers to backup and archive directly to AWS.

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Using ‘athena-express’ to Simplify SQL Queries on Amazon Athena

Deloitte’s Gary Arora, an APN Ambassador, will show you how to integrate an application with Amazon Athena to execute SQL queries with ‘athena-express.’ This is a wrapper around the AWS SDK that can simplify executing SQL queries in Amazon Athena and fetch the JSON results in the same synchronous call—a capability well suited for many web applications. Developers can use ‘athena-express’ to help save time and effort in setting up the integration and focus on core application development.

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Now You Can Query and Visualize Amazon Athena Data Directly in Chartio

Amazon Athena is a Presto-distributed SQL engine used to query unstructured data using standard SQL, where you pay only for the amount of data you query. Chartio, an AWS Competency Partner, recently announced support for Athena. Their solution allows you to query and visualize data stored in an Amazon S3 data lake using standard SQL. You can also use their visual drag-and-drop SQL layer, which generates native SQL queries for you.

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