Flipboard

MAY 20, 2025

The end-to-end workflow features a supervisor agent at the center, classification and conversion agents branching off, a humanintheloop step, and Amazon Simple Storage Service (Amazon S3) as the final unstructured data lake destination. Make sure that every incoming data eventually lands, along with its metadata, in the S3 data lake.

Data Lakes 126

Data Lakes AWS Analytics Analytics 126

AWS Machine Learning Blog

NOVEMBER 14, 2024

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. Implement a tagging strategy A tag is a label you assign to an AWS resource. The AWS reserved prefix aws: tags provide additional metadata tracked by AWS.

ML 107

ML ML AWS Machine Learning 107

Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

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AWS Data Warehouse ETL SQL 134

AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. Communication between the two systems was established through Kerberized Apache Livy (HTTPS) connections over AWS PrivateLink. Applying for a mortgage can be complex and time-consuming.

Data Science 74

Data Science AWS Hadoop Data Scientist 74

Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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AWS Cloud Computing Data Lakes Database 138

Flipboard

NOVEMBER 27, 2024

In the context of enterprise data asset search powered by a metadata catalog hosted on services such Amazon DataZone, AWS Glue, and other third-party catalogs, knowledge graphs can help integrate this linked data and also enable a scalable search paradigm that integrates metadata that evolves over time.

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AWS Database ML ML 143

AWS Machine Learning Blog

NOVEMBER 15, 2023

Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on their mission to make financial security accessible for all. They are processing data across channels, including recorded contact center interactions, emails, chat and other digital channels.

AWS 117

AWS Analytics Analytics ML 117

Flipboard

MAY 14, 2025

Among these, four primary use cases have emerged as especially prominent: intelligent process automation, anomaly detection, analytics, and operational assistance. Different types of data typically require different tools to access them. AWS IAM Identity Center must be configured in your preferred Region.

AWS 137

AWS AI Database AI 137

AWS Machine Learning Blog

FEBRUARY 21, 2025

Lets assume that the question What date will AWS re:invent 2024 occur? The corresponding answer is also input as AWS re:Invent 2024 takes place on December 26, 2024. If the question was Whats the schedule for AWS events in December?, This setup uses the AWS SDK for Python (Boto3) to interact with AWS services.

AWS 122

AWS Natural Language Processing Machine Learning Machine Learning 122

Dataconomy

JUNE 18, 2025

This ensures that all stakeholders have access to accurate and timely data, fostering collaboration and efficiency across departments. What is data integration? Data integration involves the systematic combination of data from multiple sources to create cohesive sets for operational and analytical purposes.

Data Warehouse 91

Data Warehouse Data Silos ETL Big Data 91

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Run the AWS Glue ML transform job.

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AWS ML ML ETL 123

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data.

SQL 155

SQL AWS Data Lakes AI 155

AWS Machine Learning Blog

DECEMBER 7, 2023

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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AWS Algorithm Data Science Machine Learning 128

AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. This capability of predictive analytics, particularly the accurate forecast of product categories, has proven invaluable.

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AWS Predictive Analytics ML ML 121

AWS Machine Learning Blog

MARCH 8, 2023

This solution helps market analysts design and perform data-driven bidding strategies optimized for power asset profitability. In this post, you will learn how Marubeni is optimizing market decisions by using the broad set of AWS analytics and ML services, to build a robust and cost-effective Power Bid Optimization solution.

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AWS Machine Learning Machine Learning Analytics 98

AWS Machine Learning Blog

NOVEMBER 22, 2023

Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! are the sessions dedicated to AWS DeepRacer ! Generative AI is at the heart of the AWS Village this year. You marked your calendars, you booked your hotel, and you even purchased the airfare. And last but not least (and always fun!)

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AWS ML ML AI 136

AWS Machine Learning Blog

DECEMBER 3, 2024

Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content (such as PDFs, Word documents, and HTML pages), and structured data (real-time data and reports stored in databases or data lakes).

AWS 98

AWS Database Data Silos Data Lakes 98

AWS Machine Learning Blog

SEPTEMBER 27, 2024

Amazon Simple Storage Service (Amazon S3) stores the model artifacts and creates a data lake to host the inference output, document analysis output, and other datasets in CSV format. About the authors Scott Patterson is a Senior Solutions Architect at AWS. The sunburst graph below is a visualization of this classification.

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AWS Data Lakes ML ML 119

AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale.

ML 131

ML ML AWS Data Lakes 131

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Data Science Dojo

JULY 6, 2023

Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS). Amazon Redshift allows data engineers to analyze large datasets quickly using massively parallel processing (MPP) architecture. It supports batch processing and is widely used for data-intensive tasks.

Data Engineering 195

Data Engineering Data Engineering Data Engineering Data Engineer 195

AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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AWS AI AI K-nearest Neighbors 127

AWS Machine Learning Blog

SEPTEMBER 5, 2023

In this post, we show how the Carrier and AWS teams applied ML to predict faults across large fleets of equipment using a single model. We first highlight how we use AWS Glue for highly parallel data processing. This dramatically reduces the size of data while capturing features that characterize the equipment’s behavior.

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AWS ML ML Machine Learning 121

Flipboard

MARCH 7, 2023

This post presents a solution that uses a workflow and AWS AI and machine learning (ML) services to provide actionable insights based on those transcripts. We use multiple AWS AI/ML services, such as Contact Lens for Amazon Connect and Amazon SageMaker , and utilize a combined architecture.

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ML ML AWS AI 123

AWS Machine Learning Blog

NOVEMBER 12, 2024

You may check out additional reference notebooks on aws-samples for how to use Meta’s Llama models hosted on Amazon Bedrock. You can implement these steps either from the AWS Management Console or using the latest version of the AWS Command Line Interface (AWS CLI). Solutions Architect at AWS. Varun Mehta is a Sr.

SQL 112

SQL AWS AI AI 112

IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. Let’s delve into the database portfolio from IBM available on AWS. 

AWS 93

AWS Database ETL AI 93

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

AWS Machine Learning Blog

JUNE 5, 2023

Canvas provides connectors to AWS data sources such as Amazon Simple Storage Service (Amazon S3), Athena, and Amazon Redshift. In this post, we describe how to query Parquet files with Athena using AWS Lake Formation and use the output Canvas to train a model. Use the imported Parquet data to build ML models with Canvas.

Machine Learning 96

Machine Learning Machine Learning AWS Data Lakes 96

AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

SQL 125

SQL Data Lakes Data Analyst AWS 125

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. AWS Propelling Hybrid Cloud Environments. The Problem with Hybrid Cloud Environments.

Data Lakes 52

Data Lakes Cloud Data AWS Tableau 52

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Data Science 101

NOVEMBER 11, 2019

Azure Synapse Analytics This is the future of data warehousing. It combines data warehousing and data lakes into a simple query interface for a simple and fast analytics service. If you are at a University or non-profit, you can ask for cash and/or AWS credits. Google Cloud.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It is because you usually see Kafka producers publish data or push it towards a Kafka topic so that the application can consume the data.

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Apache Kafka ETL Data Lakes AWS 130

AWS Machine Learning Blog

JUNE 22, 2023

Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to stream telemetry and machine health data from roughly half a million electronic gaming machines distributed across its casino customer base globally when LnW Connect reaches its full potential.

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AWS ML ML Machine Learning 109

Flipboard

NOVEMBER 17, 2023

Specify the AWS Lambda function that will interact with MongoDB Atlas and the LLM to provide responses. As always, AWS welcomes feedback. About the authors Igor Alekseev is a Senior Partner Solution Architect at AWS in Data and Analytics domain. Choose Build and after the build is successful, choose Test.

K-nearest Neighbors 168

K-nearest Neighbors AWS Clustering Database 168

Flipboard

NOVEMBER 24, 2023

In this post, we will talk about how BMW Group, in collaboration with AWS Professional Services, built its Jupyter Managed (JuMa) service to address these challenges. For example, teams using these platforms missed an easy migration of their AI/ML prototypes to the industrialization of the solution running on AWS.

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ML ML AWS AI 148