AWS Machine Learning Blog

Category: Amazon Athena

You already know how to use Amazon Athena to transform data in Amazon S3 using simple SQL commands

Translate, redact, and analyze text using SQL functions with Amazon Athena, Amazon Translate, and Amazon Comprehend

Update April 5th 2021: Post updated per Amazon Athena UDF SQL syntax updates. You have Amazon Simple Storage Service (Amazon S3) buckets full of files containing incoming customer chats, product reviews, and social media feeds, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing happy […]

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For an existing data lake registered with Lake Formation, the following diagram illustrates the proposed implementation.

Control and audit data exploration activities with Amazon SageMaker Studio and AWS Lake Formation

Certain industries are required to audit all access to their data. This includes auditing exploratory activities performed by data scientists, who usually query data from within machine learning (ML) notebooks. This post walks you through the steps to implement access control and auditing capabilities on a per-user basis, using Amazon SageMaker Studio notebooks and AWS […]

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Data visualization and anomaly detection using Amazon Athena and Pandas from Amazon SageMaker

Many organizations use Amazon SageMaker for their machine learning (ML) requirements and source data from a data lake stored on Amazon Simple Storage Service (Amazon S3). The petabyte scale source data on Amazon S3 may not always be clean because data lakes ingest data from several source systems, such as like flat files, external feeds, […]

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Automating the analysis of multi-speaker audio files using Amazon Transcribe and Amazon Athena

In an effort to drive customer service improvements, many companies record the phone conversations between their customers and call center representatives. These call recordings are typically stored as audio files and processed to uncover insights such as customer sentiment, product or service issues, and agent effectiveness. To provide an accurate analysis of these audio files, […]

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Detecting and visualizing telecom network outages from tweets with Amazon Comprehend

In today’s world, social media has become a place where customers share their experiences with services that they consume. Every telecom provider wants to have the ability to understand their customer pain points as soon as possible and to do this carriers frequently establish a social media team within their NOC (network operation center). This […]

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Exploring images on social media using Amazon Rekognition and Amazon Athena

If you’re like most companies, you wish to better understand your customers and your brand image. You’d like to track the success of your marketing campaigns, and the topics of interest—or frustration—for your customers. Social media promises to be a rich source of this kind of information, and many companies are beginning to collect, aggregate, […]

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Shopper Sentiment: Analyzing in-store customer experience

Retailers have been using in-store video to analyze customer behaviors and demographics for many years.  Separate systems are commonly used for different tasks.  For example, one system would count the number of customers moving through a store, in which part of the store those customers linger and near which products.  Another system will hold the store layout, whilst yet […]

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Run SQL queries from your SageMaker notebooks using Amazon Athena

The volume, velocity and variety of data has been ever increasing since the advent of the internet. The problem many enterprises face is managing this “big data” and trying to make sense out of it to yield the most desirable outcome. Siloes in enterprises, continuous ingestion of data in numerous formats, and the ever-changing technology […]

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Detect sentiment from customer reviews using Amazon Comprehend

In today’s world, public content has never been more relevant. Data from customer reviews is being used as a tool to gain insight into consumption-related decisions as the understanding of its associated sentiment grants businesses invaluable market awareness and the ability to proactively address issues early. Sentiment analysis uses a process to computationally determine whether […]

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Build a social media dashboard using machine learning and BI services

In this blog post we’ll show you how you can use Amazon Translate, Amazon Comprehend, Amazon Kinesis, Amazon Athena, and Amazon QuickSight to build a natural-language-processing (NLP)-powered social media dashboard for tweets. Social media interactions between organizations and customers deepen brand awareness. These conversations are a low-cost way to acquire leads, improve website traffic, develop […]

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