AWS Architecture Blog

Category: Amazon Athena

Figure 2- Spoke and hub architecture

Field Notes: Analyze Cross-Account AWS KMS Call Usage with AWS CloudTrail and Amazon Athena

Businesses are expanding their footprint on Amazon Web Services (AWS) and are adopting a multi-account strategy to help isolate and manage business applications and data. In the multi-account strategy, it is common to have business applications deployed in one account accessing an Amazon Simple Storage Service (Amazon S3) encrypted bucket from another AWS account. When […]

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Figure 1. Audit Surveillance data lake architecture diagram

How Parametric Built Audit Surveillance using AWS Data Lake Architecture

Parametric Portfolio Associates (Parametric), a wholly owned subsidiary of Morgan Stanley, is a registered investment adviser. Parametric provides investment advisory services to individual and institutional investors around the world. Parametric manages over 100,000 client portfolios with assets under management exceeding $400B (as of 9/30/21). As a registered investment adviser, Parametric is subject to numerous regulatory […]

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Serverless S3 metadata search

Swiftly Search Metadata with an Amazon S3 Serverless Architecture

As you increase the number of objects in Amazon Simple Storage Service (Amazon S3), you’ll need the ability to search through them and quickly find the information you need. In this blog post, we offer you a cost-effective solution that uses a serverless architecture to search through your metadata. Using a serverless architecture helps you […]

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Figure 2. Architecture to view Security Hub findings using AWS serverless analytics services

Visualize AWS Security Hub Findings using Analytics and Business Intelligence Tools

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. To improve the security posture in your organization, you first must have a comprehensive view of your security, operations, and compliance data. AWS Security Hub gives you a thorough view of your security alerts and security posture across all your […]

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Figure 2. Building Lake House architectures with AWS Glue

How to Accelerate Building a Lake House Architecture with AWS Glue

Customers are building databases, data warehouses, and data lake solutions in isolation from each other, each having its own separate data ingestion, storage, management, and governance layers. Often these disjointed efforts to build separate data stores end up creating data silos, data integration complexities, excessive data movement, and data consistency issues. These issues are preventing […]

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Figure 1. Notional architecture for improving forecasting accuracy solution and SAP integration

Improving Retail Forecast Accuracy with Machine Learning

The global retail market continues to grow larger and the influx of consumer data increases daily. The rise in volume, variety, and velocity of data poses challenges with demand forecasting and inventory planning. Outdated systems generate inaccurate demand forecasts. This results in multiple challenges for retailers. They are faced with over-stocking and lost sales, and […]

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How to redact confidential information in your ML pipeline

Integrating Redaction of FinServ Data into a Machine Learning Pipeline

Financial companies process hundreds of thousands of documents every day. These include loan and mortgage statements that contain large amounts of confidential customer information. Data privacy requires that sensitive data be redacted to protect the customer and the institution. Redacting digital and physical documents is time-consuming and labor-intensive. The accidental or inadvertent release of personal information […]

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Figure 2. Fraud detection using machine learning architecture on AWS

Analyze Fraud Transactions using Amazon Fraud Detector and Amazon Athena

Organizations with online businesses have to be on guard constantly for fraudulent activity, such as fake accounts or payments made with stolen credit cards. One way they try to identify fraudsters is by using fraud detection applications. Some of these applications use machine learning (ML). A common challenge with ML is the need for a […]

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Fitness functions provide feedback to engineers via metrics

Using Cloud Fitness Functions to Drive Evolutionary Architecture

“It is not the strongest of the species that survives, nor the most intelligent. It is the one that is most adaptable to change.” – often attributed to Charles Darwin One common strategy for businesses that operate in dynamic market conditions (and thus need to continuously correct their course) is to aim for smaller, independent […]

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Figure 1. Architecture diagram depicting enterprise vertical integration with Amazon EventBridge

Vertical Integration Strategy Powered by Amazon EventBridge

Over the past few years, midsize and large enterprises have adopted vertical integration as part of their strategy to optimize operations and profitability. Vertical integration consists of separating different stages of the production line from other related departments, such as marketing and logistics. Enterprises implement such strategy to gain full control of their value chain: from the […]

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