Category: Analytics

AWS is excited to announce the general availability of Amazon SageMaker integration in QuickSight. You can now integrate your own Amazon SageMaker ML models with QuickSight to analyze the augmented data and use it directly in your business intelligence dashboards. As a business analyst, data engineer, or data scientist, you can perform ML inference in […]

As technology is advancing, your business is collecting more and more data from different sources. After collecting so many data points, it is often challenging to find the right insights to help your business grow. Dashboards are great at visualizing your data, based upon how you built them, but not always great at finding hidden […]

You’ve rolled out a conversational interface powered by Amazon Lex, with a goal of improving the user experience for your customers. Now you want to track how well it’s working. Are your customers finding it helpful? How are they using it? Do they like it enough to come back? How can you analyze their interactions […]

Thanks to cloud services such as Amazon SageMaker and AWS Data Exchange, machine learning (ML) is now easier than ever. This post explains how to build a model that predicts restaurant grades of NYC restaurants using AWS Data Exchange and Amazon SageMaker. We use a dataset of 23,372 restaurant inspection grades and scores from AWS […]

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, […]

We’re excited to announce an end-to-end solution that leverages natural language processing to analyze and visualize unstructured text in your Amazon Elasticsearch Service domain with Amazon Comprehend in the AWS Cloud. You can deploy this solution in minutes with an AWS CloudFormation template and visualize your data in a Kibana dashboard. Amazon Elasticsearch Service (Amazon ES) […]

Are you a data scientist with data warehouse tables that you’d like to explore in your machine learning (ML) environment? If so, read on. In this post, I show you how to perform exploratory analysis on large datasets stored in your data warehouse and cataloged in your AWS Glue Data Catalog from your Amazon SageMaker […]

We are excited to announce the launch of the Amazon Kinesis Video Streams Inference Template (KIT) for Amazon SageMaker. This capability enables customers to attach Kinesis Video streams to Amazon SageMaker endpoints in minutes. This drives real-time inferences without having to use any other libraries or write custom software to integrate the services. The KIT comprises […]

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 […]

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 […]