databricks

OCTOBER 13, 2023

Today, we are excited to announce the general availability of the Databricks SQL Statement Execution API on AWS and Azure, with support for.

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AWS Machine Learning Blog

DECEMBER 11, 2024

Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. Field Advisor serves four primary use cases: AWS-specific knowledge search With Amazon Q Business, weve made internal data sources as well as public AWS content available in Field Advisors index.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. On AWS, you can use the fully managed Amazon Bedrock Agents or tools of your choice such as LangChain agents or LlamaIndex agents.

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Analytics Vidhya

APRIL 25, 2022

The post AWS Redshift: Cloud Data Warehouse Service appeared first on Analytics Vidhya. Companies may store petabytes of data in easy-to-access “clusters” that can be searched in parallel using the platform’s storage system. The datasets range in size from a few 100 megabytes to a petabyte. […].

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Data Warehouse Cloud Data AWS Clustering 291

Analytics Vidhya

MARCH 5, 2023

Introduction Amazon Athena is an interactive query tool supplied by Amazon Web Services (AWS) that allows you to use conventional SQL queries to evaluate data stored in Amazon S3. Athena is a serverless service. Thus there are no servers to operate, and you pay for the queries you perform.

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databricks

APRIL 17, 2024

The next generation of Databricks SQL dashboards, also known as Lakeview Dashboards, is now generally available on AWS and Azure. This new dashboarding experience is optimized for ease of use, scalable and secure distribution, governance, and performance.

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AWS Machine Learning Blog

MARCH 10, 2025

We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate , and Amazon OpenSearch Service. Along the way, it also simplified operations as Octus is an AWS shop more generally.

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Analytics Vidhya

MAY 20, 2022

Source: Link Introduction In this article, we are going to talk about a dynamo DB a No-SQL, and a very highly scalable database provided by Amazon AWS. This article was published as a part of the Data Science Blogathon. DynamoDB is a scalable hosted NoSQL database service that offers low latency and key-value pair databases.

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databricks

AUGUST 2, 2023

We're excited to share a new set of security controls and compliance certifications that can help with regulatory compliance on Azure Databricks and.

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Flipboard

NOVEMBER 27, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL, business intelligence (BI), and reporting tools. Choose the us-east-1 AWS Region in which to create the stack. Create dbt models in dbt Cloud.

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AWS Machine Learning Blog

APRIL 16, 2024

They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference. Previously, data scientists often found themselves juggling multiple tools to support SQL in their workflow, which hindered productivity.

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SQL AWS Database Data Scientist 118

AWS Machine Learning Blog

FEBRUARY 21, 2025

Communication between the two systems was established through Kerberized Apache Livy (HTTPS) connections over AWS PrivateLink. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. Rockets new data science solution architecture on AWS is shown in the following diagram.

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Data Science AWS Hadoop Data Scientist 72

Flipboard

JANUARY 24, 2025

Use the AWS generative AI scoping framework to understand the specific mix of the shared responsibility for the security controls applicable to your application. The following figure of the AWS Generative AI Security Scoping Matrix summarizes the types of models for each scope.

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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).

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AWS Machine Learning Blog

MAY 30, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. AWS Prototyping developed an AWS Cloud Development Kit (AWS CDK) stack for deployment following AWS best practices.

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AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.

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Data Science Dojo

OCTOBER 31, 2024

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Additionally, knowledge of cloud platforms (AWS, Google Cloud) and experience with deployment tools (Docker, Kubernetes) are highly valuable. Familiarity with machine learning, algorithms, and statistical modeling.

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AWS Machine Learning Blog

NOVEMBER 20, 2024

In this post, we explore how you can use Amazon Q Business , the AWS generative AI-powered assistant, to build a centralized knowledge base for your organization, unifying structured and unstructured datasets from different sources to accelerate decision-making and drive productivity. In this post, we use IAM Identity Center as the SAML 2.0-aligned

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AWS Machine Learning Blog

NOVEMBER 14, 2024

In this post, we save the data in JSON format, but you can also choose to store it in your preferred SQL or NoSQL database. Prerequisites To perform this solution, complete the following: Create and activate an AWS account. Make sure your AWS credentials are configured correctly. Install Python 3.7

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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. Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries.

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SQL Data Lakes Data Analyst AWS 123

AWS Machine Learning Blog

AUGUST 1, 2024

To address this challenge, AWS recently announced the preview of Amazon Bedrock Custom Model Import , a feature that you can use to import customized models created in other environments—such as Amazon SageMaker , Amazon Elastic Compute Cloud (Amazon EC2) instances, and on premises—into Amazon Bedrock.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Prerequisites Before you begin, make sure you have the following prerequisites in place: An AWS account and role with the AWS Identity and Access Management (IAM) privileges to deploy the following resources: IAM roles. Basic knowledge of a SQL query editor. A provisioned or serverless Amazon Redshift data warehouse.

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Data Science Blog

SEPTEMBER 19, 2023

The following Terraform script will create an Azure Resource Group, a SQL Server, and a SQL Database. AWS CloudFormation is a service offered by Amazon Web Services (AWS) that allows you to define cloud infrastructure in JSON or YAML templates. So why using IaC for Cloud Data Infrastructures?

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AWS Machine Learning Blog

JUNE 20, 2024

The data is stored in a data lake and retrieved by SQL using Amazon Athena. The following figure shows a search query that was translated to SQL and run. Data is normally stored in databases, and can be queried using the most common query language, SQL. Constructing SQL queries from natural language isn’t a simple task.

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SQL Database AWS Machine Learning 110

Flipboard

JUNE 26, 2023

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. Run the AWS Glue ML transform job.

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AWS Machine Learning Blog

MARCH 12, 2024

In this post, we explore what an audience overlap analysis is, discuss the current technical approaches and their challenges, and illustrate how you can run secure audience overlap analysis using AWS Clean Rooms. With AWS Clean Rooms, you can create a data clean room in minutes and collaborate with your partners to generate unique insights.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using Amazon Web Services (AWS) services without having to manage infrastructure. AWS Lambda The API is a Fastify application written in TypeScript.

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AWS Machine Learning Blog

DECEMBER 6, 2023

To overcome these limitations, we propose a solution that combines RAG with metadata and entity extraction, SQL querying, and LLM agents, as described in the following sections. Typically, these analytical operations are done on structured data, using tools such as pandas or SQL engines.

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SQL AWS Analytics Analytics 126

AWS Machine Learning Blog

SEPTEMBER 13, 2024

Managing cloud costs and understanding resource usage can be a daunting task, especially for organizations with complex AWS deployments. AWS Cost and Usage Reports (AWS CUR) provides valuable data insights, but interpreting and querying the raw data can be challenging.

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Flipboard

DECEMBER 11, 2024

Discover your data and put it to work using familiar AWS tools to complete end-to-end development workflows, including data analysis, data processing, model training, generative AI app building, and more, in a single governed environment. With the SQL editor, you can query data lakes, databases, data warehouses, and federated data sources.

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SQL AWS Data Lakes ML 158

Dataversity

MARCH 26, 2024

Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.

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Data Lakes AWS SQL ETL 64

AWS Machine Learning Blog

FEBRUARY 12, 2025

Prerequisites To build the solution yourself, there are the following prerequisites: You need an AWS account with an AWS Identity and Access Management (IAM) role that has permissions to manage resources created as part of the solution (for example AmazonSageMakerFullAccess and AmazonS3FullAccess ).

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AWS SQL AI AI 78

Hacker News

MARCH 6, 2025

High-performance, low-footprint SQL database written in C++. Process millions of rows per second from Kafka, Pulsar, or ClickHouse, and seamlessly write results back. Supports powerful features like JOIN, CDC, UPSERT, and LOOKUP, enabling real-time analytics and ETL at scale.

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ETL AWS SQL Database 105

Towards AI

APRIL 3, 2024

Photo by Caspar Camille Rubin on Unsplash AWS Athena is a serverless interactive query system. So if you are familiar with the Standard SQL queries, you are good to go!! Go to the AWS Glue Console. Athena Setup Go to the AWS management console and open Athena. Athena works with the data stored in S3. That is it!!

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AWS Database ETL Big Data 105

AWS Machine Learning Blog

SEPTEMBER 19, 2023

Implementing a multi-modal agent with AWS consolidates key insights from diverse structured and unstructured data on a large scale. All this is achieved using AWS services, thereby increasing the financial analyst’s efficiency to analyze multi-modal financial data (text, speech, and tabular data) holistically.

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AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. The primary goal is to automatically generate SQL queries from natural language text. What percentage of customers are from each region?”

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SQL Database AI AI 139

AWS Machine Learning Blog

SEPTEMBER 12, 2024

From a broad perspective, the complete solution can be divided into four distinct steps: text-to-SQL generation, SQL validation, data retrieval, and data summarization. A pre-configured prompt template is used to call the LLM and generate a valid SQL query. The following diagram illustrates this workflow.

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