AWS for Industries

Category: Amazon Redshift

Figure 1 Reference architecture for the proposed visualization sample

Making Site Selection Decisions Easy With AWS Data Exchange for Amazon Redshift

Many quick service restaurants (QSRs) and dining brands rely on third-party point-of-interest data to understand if they’re making the right market expansion moves. For example, a QSR looking to place its first location in New York City may want to know the clustering of bars and nightlife venues in Manhattan to set hours of operation […]

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CPG Partner Conversations: Manage Your Business Through Market Disruptions with Sigmoid’s Advanced Analytics Solutions

The COVID-19 pandemic created unprecedented disruption to businesses and global markets. Although most of the world appears to be past the uncertainty and turbulence of the pandemic, companies, especially in the consumer packaged goods (CPG) industry, continue to deal with major challenges. These include supply chain disruptions and labor shortages. Simultaneously, consumer buying patterns and […]

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A Reference Architecture for a Front Office Risk Store

Robert Butcher, Solution Architect, Global Financial Services, AWS Front Office risk data is the lifeblood of Investment Banks. It informs every trading decision that they take, both commercial and prudential, and it’s critical for planning and regulatory reporting purposes. In this post, we present a reference architecture for a Front Office Risk Store (risk store) […]

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How to Integrate Your AWS Cloud-Native Dynamic Supply Chain Application With External Systems

In our previous blog, How to build a dynamic supply chain platform: a primer, we discussed how companies can use Amazon Web Services (AWS) to build a dynamic supply chain that can proactively react to events and also provide complete visibility, communication, and data transfer. By collecting and analyzing near-real-time supply chain data, companies can […]

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Uplevel Your Revenue Growth Management for CPG With Sigmoid on AWS

Consumer packaged goods (CPG) companies are undergoing massive transformations on multiple fronts to cater to the demands of ever-changing consumer behavior, new supply chain practices, and increasing competition with new market entrants. A survey conducted by Boston Consulting Group (BCG) with global business leaders, whose companies underwent a transformation over the past five years, suggests […]

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Diagram illustrating how the Lake Formation service works. Data stores flow into the data lake where Lake Formation is shown managing AWS Glue functionality to provide self-service access to users through analytics services such as, Amazon Athena, Amazon Redshift, and Amazon EMR.

FSI Services Spotlight: Featuring AWS Lake Formation

Welcome back to the Financial Services Industry (FSI) Service Spotlight monthly blog series. Each month we look at five key considerations that FSI customers should focus on to help streamline cloud service approval for one particular service. Each of the five key considerations includes specific guidance, suggested reference architectures, and technical code that can be […]

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Retail Builders Blog Series

Managing Custom Clearance Risk in a Global Supply Chain

In our previous blog, How to Build a Dynamic Supply Chain Platform: A Primer, we discussed how companies can proactively manage market events in a global supply chain using AWS. In this post, we will focus on how companies can manage customs clearance risk in the same supply chain by using AWS artificial intelligence and […]

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Selling more wine, feeding more pets, influencing more customers: JBS Solutions and AWS power the new world of retail

Since the start of the pandemic, retail customers’ purchasing habits have shifted dramatically—and they’re not going back. From online shopping and curbside pickup to changing brand loyalties prompted by supply chain disruptions to purchase decisions strongly influenced by social media, the world of retail has changed for good. To compete, retailers need to reinvent their […]

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Perform interactive queries on your genomics data using Amazon Athena or Amazon Redshift (Part 2)

This is part 2 of a blog series – see part 1 for how to generate the data that is used in this blog. One of the main objectives of creating a data lake is to be able to perform analytics queries across large datasets to gain insights that would not be possible if the […]

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Build a genomics data lake on AWS using Amazon EMR (Part 1)

As data emerges from population genomics projects all over the world, researchers struggle to perform large-scale genomics analyses with data scattered across multiple data silos within their organizations. In order to be able to perform more sophisticated tertiary analysis on genomics and clinical data, researchers need to be able to access, aggregate, and query the […]

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