AWS Big Data Blog

Category: Analytics*

Create Custom AMIs and Push Updates to a Running Amazon EMR Cluster Using Amazon EC2 Systems Manager

Amazon EMR lets you have complete control over your cluster, giving you the flexibility to customize a cluster and install additional applications easily. EMR customers often use bootstrap actions to install and configure custom software in a cluster. However, bootstrap actions only run during the cluster or node startup. This makes it difficult for you […]

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Unite Real-Time and Batch Analytics Using the Big Data Lambda Architecture, Without Servers!

The Big Data Lambda Architecture seeks to provide data engineers and architects with a scalable, fault-tolerant data processing architecture and framework using loosely coupled, distributed systems. At a high level, the Lambda Architecture is designed to handle both real-time and historically aggregated batched data in an integrated fashion. It separates the duties of real-time and […]

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Amazon QuickSight Now Supports Search, Filter Groups, and Amazon S3 Analytics Connector

Today, I’m excited to share information about some new features in Amazon QuickSight. First, you can now search for datasets, analyses, and dashboards in Amazon QuickSight using the unified search box, making it faster and easier to find and access your data. Next, you can now create filter groups with multiple filter conditions that are […]

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Analyzing Salesforce Data with Amazon QuickSight

Salesforce Sales Cloud is a powerful platform for managing customer data. One of the key functions that the platform provides is the ability to track customer opportunities. Opportunities in Salesforce are used to track revenue, sales pipelines, and other activities from the very first contact with a potential customer to a closed sale. Amazon QuickSight […]

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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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Analyzing AWS Cost and Usage Reports with Looker and Amazon Athena

This is a guest post by Dillon Morrison at Looker. Looker is, in their own words, “a new kind of analytics platform–letting everyone in your business make better decisions by getting reliable answers from a tool they can use.”  As the breadth of AWS products and services continues to grow, customers are able to more easily […]

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Harmonize, Query, and Visualize Data from Various Providers using AWS Glue, Amazon Athena, and Amazon QuickSight

Have you ever been faced with many different data sources in different formats that need to be analyzed together to drive value and insights?  You need to be able to query, analyze, process, and visualize all your data as one canonical dataset, regardless of the data source or original format. In this post, I walk […]

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Upsert into Amazon Redshift using AWS Glue and SneaQL

This is a guest post by Jeremy Winters and Ritu Mishra, Solution Architects at Full 360. In their own words, “Full 360 is a cloud first, cloud native integrator, and true believers in the cloud since inception in 2007, our focus has been on helping customers with their journey into the cloud. Our practice areas […]

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Deploy a Data Warehouse Quickly with Amazon Redshift, Amazon RDS for PostgreSQL and Tableau Server

One of the benefits of a data warehouse environment using both Amazon Redshift and Amazon RDS for PostgreSQL is that you can leverage the advantages of each service. Amazon Redshift is a high performance, petabyte-scale data warehouse service optimized for the online analytical processing (OLAP) queries typical of analytic reporting and business intelligence applications. On […]

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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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