This document provides an overview and best practices for using Amazon Redshift and Redshift Spectrum for data warehousing. It covers the history and development of Redshift, key concepts like columnar storage, compression, sorting and distribution styles. It provides examples and recommendations for table design, workload management, and query optimization techniques.
This webinar discussed strategies to help save money in the AWS Cloud. From turning systems off at night, to implementing bidding strategies on the spot market, there are many ways in which you can manage and your reduce costs with AWS.
This webinar dived into the differences between instance types; explain how you can reduce costs with Reserved Instances, the spot market and by architecting to reduce costs. It also discussed how to combine on-demand pricing with spot pricing to perform cost effective big data analysis, and introduce customer examples to illustrate how AWS customers gain the most from AWS whilst at the same time managing their spend.
Migrate from Oracle to Amazon Aurora using AWS Schema Conversion Tool & AWS D...Amazon Web Services
• Understand the issues with commercial database pricing and licensing.
• Learn about the benefits of Amazon Aurora for improving performance and decreasing costs.
• See how AWS Database Migration Service helps with your migration.
• See how AWS Schema Conversion Tool makes conversions simple and quick.
If you’re looking to improve application performance and availability and decrease database costs, it’s time to replace your expensive Oracle databases with an open-source compatible solution. Amazon Aurora is a MySQL-compatible relational database that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. You'll learn how to use the AWS Database Migration Service to migrate your data with minimal downtime, and how the AWS Schema Conversion Tool converts your Oracle schemas and procedural code into Amazon Aurora. We’ll follow with a quick demo of the entire process.
AWS 101 Webinar: Journey to the AWS Cloud - Introduction to Cloud Computing w...Amazon Web Services
Whether you are running applications that share photos or support critical operations of your business, you need rapid access to flexible and low cost IT resources. The term "cloud computing" refers to the on-demand delivery of IT resources via the Internet with pay-as-you-go pricing. Whether you are a start-up who wants to accelerate growth without a big upfront investment in cash or time for technology or an Enterprise looking for IT innovation, agility and resiliency while reducing costs, the AWS Cloud provides a complete set of web services at zero upfront costs which are available with a few clicks and within minutes. In this session learn more about the benefits of Cloud Computing with AWS.
ABD201-Big Data Architectural Patterns and Best Practices on AWSAmazon Web Services
In this session, we simplify big data processing as a data bus comprising various stages: collect, store, process, analyze, and visualize. Next, we discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Amazon WorkSpaces: Desktop Computing in the Cloud (ENT104) | AWS re:Invent 2013Amazon Web Services
Desktop virtualization has long held the promise of productivity and security benefits, but has been held back by large CapEx requirements and complicated installation and management. In this session, we provide a detailed introduction to Amazon WorkSpaces, a new AWS service that combines the benefits of desktop virtualization and a cloud-based, pay-as-you-go model. You learn about the key steps for setting up and delivering a secure cloud-based workspace accessed through purpose-built client applications.
Top 5 Ways to Optimize for Cost Efficiency with the CloudAmazon Web Services
This session covers the Top 5 ways you can reduce the cost of your workloads in the AWS Cloud including high-level architectures and when to use and our numerous pricing options for components of those architectures.
We walk through several examples to illustrate when to use each feature, configuration or pricing option. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending.
Reasons to attend:
Learn about Reserved Instances, On-Demand Instances and Spot Instances.
Discover ways of running more for less in Amazon EC2.
If you are already running a workload in AWS, attend this webinar to learn how to run the same workload at reduced costs.
This webinar discussed strategies to help save money in the AWS Cloud. From turning systems off at night, to implementing bidding strategies on the spot market, there are many ways in which you can manage and your reduce costs with AWS.
This webinar dived into the differences between instance types; explain how you can reduce costs with Reserved Instances, the spot market and by architecting to reduce costs. It also discussed how to combine on-demand pricing with spot pricing to perform cost effective big data analysis, and introduce customer examples to illustrate how AWS customers gain the most from AWS whilst at the same time managing their spend.
Migrate from Oracle to Amazon Aurora using AWS Schema Conversion Tool & AWS D...Amazon Web Services
• Understand the issues with commercial database pricing and licensing.
• Learn about the benefits of Amazon Aurora for improving performance and decreasing costs.
• See how AWS Database Migration Service helps with your migration.
• See how AWS Schema Conversion Tool makes conversions simple and quick.
If you’re looking to improve application performance and availability and decrease database costs, it’s time to replace your expensive Oracle databases with an open-source compatible solution. Amazon Aurora is a MySQL-compatible relational database that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. You'll learn how to use the AWS Database Migration Service to migrate your data with minimal downtime, and how the AWS Schema Conversion Tool converts your Oracle schemas and procedural code into Amazon Aurora. We’ll follow with a quick demo of the entire process.
AWS 101 Webinar: Journey to the AWS Cloud - Introduction to Cloud Computing w...Amazon Web Services
Whether you are running applications that share photos or support critical operations of your business, you need rapid access to flexible and low cost IT resources. The term "cloud computing" refers to the on-demand delivery of IT resources via the Internet with pay-as-you-go pricing. Whether you are a start-up who wants to accelerate growth without a big upfront investment in cash or time for technology or an Enterprise looking for IT innovation, agility and resiliency while reducing costs, the AWS Cloud provides a complete set of web services at zero upfront costs which are available with a few clicks and within minutes. In this session learn more about the benefits of Cloud Computing with AWS.
ABD201-Big Data Architectural Patterns and Best Practices on AWSAmazon Web Services
In this session, we simplify big data processing as a data bus comprising various stages: collect, store, process, analyze, and visualize. Next, we discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Amazon WorkSpaces: Desktop Computing in the Cloud (ENT104) | AWS re:Invent 2013Amazon Web Services
Desktop virtualization has long held the promise of productivity and security benefits, but has been held back by large CapEx requirements and complicated installation and management. In this session, we provide a detailed introduction to Amazon WorkSpaces, a new AWS service that combines the benefits of desktop virtualization and a cloud-based, pay-as-you-go model. You learn about the key steps for setting up and delivering a secure cloud-based workspace accessed through purpose-built client applications.
Top 5 Ways to Optimize for Cost Efficiency with the CloudAmazon Web Services
This session covers the Top 5 ways you can reduce the cost of your workloads in the AWS Cloud including high-level architectures and when to use and our numerous pricing options for components of those architectures.
We walk through several examples to illustrate when to use each feature, configuration or pricing option. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending.
Reasons to attend:
Learn about Reserved Instances, On-Demand Instances and Spot Instances.
Discover ways of running more for less in Amazon EC2.
If you are already running a workload in AWS, attend this webinar to learn how to run the same workload at reduced costs.
by Manish Mohite, Solutions Architect, AWS
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
LG 이노텍 - Amazon Redshift Serverless를 활용한 데이터 분석 플랫폼 혁신 과정 - 발표자: 유재상 선임, LG이노...Amazon Web Services Korea
LG 이노텍은 세계 시장을 선도하는 글로벌 소재·부품기업으로, Amazon Redshift 을 데이터 분석 플랫폼의 핵심 서비스로 활용하고 있습니다.지속적인 데이터 증가와 업무 확대에 따른 유연한 아키텍처 개선의 필요성에 대처하기 위해, 2022년에 AWS 에서 발표된 Redshift Serverless 를 활용한, 비용 최적화된 아키텍처 개선 과정의 실사례를 엿볼수 있는 기회가 됩니다.
Amazon DynamoDB is a fully managed, highly scalable NoSQL database service. We will deep dive into how DynamoDB scaling and partitioning works, how to do data modeling based on access patterns using primitives such as hash/range keys, secondary indexes, conditional writes and query filters. We will also discuss how to use DynamoDB Streams to build cross-region replication and integrate with other services (such as Amazon S3, Amazon CloudSearch, Amazon ElastiCache, Amazon Redshift) to enable logging, search, analytics and caching. You will learn design patterns and best practices on how to use DynamoDB to build highly scalable applications, with the right performance characteristics at the right cost.
[Keynote] 슬기로운 AWS 데이터베이스 선택하기 - 발표자: 강민석, Korea Database SA Manager, WWSO, A...Amazon Web Services Korea
오랫동안 관계형 데이터베이스가 가장 많이 사용되었으며 거의 모든 애플리케이션에서 널리 사용되었습니다. 따라서 애플리케이션 아키텍처에서 데이터베이스를 선택하기가 더 쉬웠지만, 구축할 수 있는 애플리케이션의 유형이 제한적이었습니다. 관계형 데이터베이스는 스위스 군용 칼과 같아서 많은 일을 할 수 있지만 특정 업무에는 완벽하게 적합하지는 않습니다. 클라우드 컴퓨팅의 등장으로 경제적인 방식으로 더욱 탄력적이고 확장 가능한 애플리케이션을 구축할 수 있게 되면서 기술적으로 가능한 일이 달라졌습니다. 이러한 변화는 전용 데이터베이스의 부상으로 이어졌습니다. 개발자는 더 이상 기본 관계형 데이터베이스를 사용할 필요가 없습니다. 개발자는 애플리케이션의 요구 사항을 신중하게 고려하고 이러한 요구 사항에 맞는 데이터베이스를 선택할 수 있습니다.
Database Migration Using AWS DMS and AWS SCT (GPSCT307) - AWS re:Invent 2018Amazon Web Services
Database migrations are an important step in any journey to AWS. In this session, we show you how to get started with AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) to quickly and securely migrate your databases to AWS. Learn how to simplify your database migrations by using this service to migrate your data to and from commercial and open-source databases. We also explain how you can perform homogenous migrations such as MySQL to MySQL, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora.
In this session, you get an overview of Amazon Redshift, a fast, fully-managed, petabyte-scale data warehouse service. We'll cover how Amazon Redshift uses columnar technology, optimized hardware, and massively parallel processing to deliver fast query performance on data sets ranging in size from hundreds of gigabytes to a petabyte or more. We'll also discuss new features, architecture best practices, and share how customers are using Amazon Redshift for their Big Data workloads.
Amazon RDS allows you to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you to focus on your applications and business.
Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. AWS Database Migration Service helps you migrate databases to AWS easily and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
Presented by: Danilo Poccia, Technical Evangelist, Amazon Web Services
KB국민카드 - 클라우드 기반 분석 플랫폼 혁신 여정 - 발표자: 박창용 과장, 데이터전략본부, AI혁신부, KB카드│강병억, Soluti...Amazon Web Services Korea
온프레미스 분석 플랫폼에는 자원 증설 비용, 자원 관리 비용, 신규 자원 도입 및 환경 설정의 리드타임 등 다양한 측면에서의 한계가 존재합니다. 이에 KB국민카드에서는 기존 분석 플랫폼의 한계를 극복함과 동시에 시너지를 낼 수 있는 클라우드 기반 분석 플랫폼을 설계 및 도입하였습니다. 본 사례 소개는 KB국민카드의 데이터 혁신 여정과 노하우를 소개합니다.
Streaming ETL for Data Lakes using Amazon Kinesis Firehose - May 2017 AWS Onl...Amazon Web Services
Learning Objectives:
- Understand key requirements for collecting, preparing, and loading streaming data into data lakes
- Get an overview of transmitting data using Amazon Kinesis Firehose
- Learn how to perform data transformations with Amazon Kinesis Firehose
Data lakes enable your employees across the organization to access and analyze massive amounts of unstructured and structured data from disparate data sources, many of which generate data continuously and rapidly. Making this data available in a timely fashion for analysis requires a streaming solution that can durably and cost-effectively ingest this data into your data lake. Amazon Kinesis Firehose is a fully managed service that makes it easy to prepare and load streaming data into AWS. In this tech talk, we will provide an overview of Amazon Kinesis Firehose and dive deep into how you can use the service to collect, transform, batch, compress, and load real-time streaming data into your Amazon S3 data lakes.
(BIZ305) Case Study: Migrating Oracle E-Business Suite to AWS | AWS re:Invent...Amazon Web Services
With the maturity and breadth of cloud solutions, more enterprises are moving mission-critical workloads to the cloud. American Commercial Lines (ACL) recently migrated their Oracle ERP to AWS. ERP solutions such as Oracle E-Business Suite require specific knowledge in mapping AWS infrastructure to the specific configurations and needs of running these workloads. In this session, Apps Associates and ACL walk through the considerations for running Oracle E-Business Suite on AWS, including deployment architectures, concurrent processing, load balanced forms and web services, varying database transactional workloads, and performance requirements, as well as security and monitoring aspects. ACL shares their experiences and business drivers in making this transition to AWS.
발표 다시보기: https://youtu.be/V6g1SE4DkK4?list=PLORxAVAC5fUWg_jFcq8hNJEMzELtAD6kc
Oracle, SQL Server 등과 같은 상업용 데이터베이스로부터 AWS 관리형 데이터베이스 서비스로 이동함으로써 많은 비용을 절감할 수 있습니다. 본 세션에서는 AWS가 제공하고 있는 관리형 데이터베이스 서비스의 종류 및 특징에 대해서 알아보도록 하겠습니다.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze big data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.
Best Practices for Migrating Legacy Data Warehouses into Amazon RedshiftAmazon Web Services
Migrating your data warehouse to Amazon Redshift can substantially improve query and data load performance, increase scalability, and save costs. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost effective to analyze data using your existing business intelligence tools. AWS Database Migration Service and AWS Schema Conversion Tool make it easier to migrate your schema and data from your Oracle data warehouse to Amazon Redshift, without disrupting the applications that rely on the data source.
by Manish Mohite, Solutions Architect, AWS
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
LG 이노텍 - Amazon Redshift Serverless를 활용한 데이터 분석 플랫폼 혁신 과정 - 발표자: 유재상 선임, LG이노...Amazon Web Services Korea
LG 이노텍은 세계 시장을 선도하는 글로벌 소재·부품기업으로, Amazon Redshift 을 데이터 분석 플랫폼의 핵심 서비스로 활용하고 있습니다.지속적인 데이터 증가와 업무 확대에 따른 유연한 아키텍처 개선의 필요성에 대처하기 위해, 2022년에 AWS 에서 발표된 Redshift Serverless 를 활용한, 비용 최적화된 아키텍처 개선 과정의 실사례를 엿볼수 있는 기회가 됩니다.
Amazon DynamoDB is a fully managed, highly scalable NoSQL database service. We will deep dive into how DynamoDB scaling and partitioning works, how to do data modeling based on access patterns using primitives such as hash/range keys, secondary indexes, conditional writes and query filters. We will also discuss how to use DynamoDB Streams to build cross-region replication and integrate with other services (such as Amazon S3, Amazon CloudSearch, Amazon ElastiCache, Amazon Redshift) to enable logging, search, analytics and caching. You will learn design patterns and best practices on how to use DynamoDB to build highly scalable applications, with the right performance characteristics at the right cost.
[Keynote] 슬기로운 AWS 데이터베이스 선택하기 - 발표자: 강민석, Korea Database SA Manager, WWSO, A...Amazon Web Services Korea
오랫동안 관계형 데이터베이스가 가장 많이 사용되었으며 거의 모든 애플리케이션에서 널리 사용되었습니다. 따라서 애플리케이션 아키텍처에서 데이터베이스를 선택하기가 더 쉬웠지만, 구축할 수 있는 애플리케이션의 유형이 제한적이었습니다. 관계형 데이터베이스는 스위스 군용 칼과 같아서 많은 일을 할 수 있지만 특정 업무에는 완벽하게 적합하지는 않습니다. 클라우드 컴퓨팅의 등장으로 경제적인 방식으로 더욱 탄력적이고 확장 가능한 애플리케이션을 구축할 수 있게 되면서 기술적으로 가능한 일이 달라졌습니다. 이러한 변화는 전용 데이터베이스의 부상으로 이어졌습니다. 개발자는 더 이상 기본 관계형 데이터베이스를 사용할 필요가 없습니다. 개발자는 애플리케이션의 요구 사항을 신중하게 고려하고 이러한 요구 사항에 맞는 데이터베이스를 선택할 수 있습니다.
Database Migration Using AWS DMS and AWS SCT (GPSCT307) - AWS re:Invent 2018Amazon Web Services
Database migrations are an important step in any journey to AWS. In this session, we show you how to get started with AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) to quickly and securely migrate your databases to AWS. Learn how to simplify your database migrations by using this service to migrate your data to and from commercial and open-source databases. We also explain how you can perform homogenous migrations such as MySQL to MySQL, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora.
In this session, you get an overview of Amazon Redshift, a fast, fully-managed, petabyte-scale data warehouse service. We'll cover how Amazon Redshift uses columnar technology, optimized hardware, and massively parallel processing to deliver fast query performance on data sets ranging in size from hundreds of gigabytes to a petabyte or more. We'll also discuss new features, architecture best practices, and share how customers are using Amazon Redshift for their Big Data workloads.
Amazon RDS allows you to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you to focus on your applications and business.
Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. AWS Database Migration Service helps you migrate databases to AWS easily and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
Presented by: Danilo Poccia, Technical Evangelist, Amazon Web Services
KB국민카드 - 클라우드 기반 분석 플랫폼 혁신 여정 - 발표자: 박창용 과장, 데이터전략본부, AI혁신부, KB카드│강병억, Soluti...Amazon Web Services Korea
온프레미스 분석 플랫폼에는 자원 증설 비용, 자원 관리 비용, 신규 자원 도입 및 환경 설정의 리드타임 등 다양한 측면에서의 한계가 존재합니다. 이에 KB국민카드에서는 기존 분석 플랫폼의 한계를 극복함과 동시에 시너지를 낼 수 있는 클라우드 기반 분석 플랫폼을 설계 및 도입하였습니다. 본 사례 소개는 KB국민카드의 데이터 혁신 여정과 노하우를 소개합니다.
Streaming ETL for Data Lakes using Amazon Kinesis Firehose - May 2017 AWS Onl...Amazon Web Services
Learning Objectives:
- Understand key requirements for collecting, preparing, and loading streaming data into data lakes
- Get an overview of transmitting data using Amazon Kinesis Firehose
- Learn how to perform data transformations with Amazon Kinesis Firehose
Data lakes enable your employees across the organization to access and analyze massive amounts of unstructured and structured data from disparate data sources, many of which generate data continuously and rapidly. Making this data available in a timely fashion for analysis requires a streaming solution that can durably and cost-effectively ingest this data into your data lake. Amazon Kinesis Firehose is a fully managed service that makes it easy to prepare and load streaming data into AWS. In this tech talk, we will provide an overview of Amazon Kinesis Firehose and dive deep into how you can use the service to collect, transform, batch, compress, and load real-time streaming data into your Amazon S3 data lakes.
(BIZ305) Case Study: Migrating Oracle E-Business Suite to AWS | AWS re:Invent...Amazon Web Services
With the maturity and breadth of cloud solutions, more enterprises are moving mission-critical workloads to the cloud. American Commercial Lines (ACL) recently migrated their Oracle ERP to AWS. ERP solutions such as Oracle E-Business Suite require specific knowledge in mapping AWS infrastructure to the specific configurations and needs of running these workloads. In this session, Apps Associates and ACL walk through the considerations for running Oracle E-Business Suite on AWS, including deployment architectures, concurrent processing, load balanced forms and web services, varying database transactional workloads, and performance requirements, as well as security and monitoring aspects. ACL shares their experiences and business drivers in making this transition to AWS.
발표 다시보기: https://youtu.be/V6g1SE4DkK4?list=PLORxAVAC5fUWg_jFcq8hNJEMzELtAD6kc
Oracle, SQL Server 등과 같은 상업용 데이터베이스로부터 AWS 관리형 데이터베이스 서비스로 이동함으로써 많은 비용을 절감할 수 있습니다. 본 세션에서는 AWS가 제공하고 있는 관리형 데이터베이스 서비스의 종류 및 특징에 대해서 알아보도록 하겠습니다.
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze big data for a fraction of the cost of traditional data warehouses. In this session, we take an in-depth look at data warehousing with Amazon Redshift for big data analytics. We cover best practices to take advantage of Amazon Redshift's columnar technology and parallel processing capabilities to deliver high throughput and query performance. We also discuss how to design optimal schemas, load data efficiently, and use work load management.
Best Practices for Migrating Legacy Data Warehouses into Amazon RedshiftAmazon Web Services
Migrating your data warehouse to Amazon Redshift can substantially improve query and data load performance, increase scalability, and save costs. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost effective to analyze data using your existing business intelligence tools. AWS Database Migration Service and AWS Schema Conversion Tool make it easier to migrate your schema and data from your Oracle data warehouse to Amazon Redshift, without disrupting the applications that rely on the data source.
by Andre Hass, Specialist Technical Account Manager, AWS
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Speakers:
Karan Desai - Solutions Architect, AWS
Neel Mitra - Solutions Architect, AWS
by Taz Sayed, Sr Technical Account Manager AWS and Marie Yap, Enterprise Solutions Architect AWS
AWS Data & Analytics Week is an opportunity to learn about Amazon’s family of managed analytics services. These services provide easy, scalable, reliable, and cost-effective ways to manage your data in the cloud. We explain the fundamentals and take a technical deep dive into Amazon Redshift data warehouse; Data Lake services including Amazon EMR, Amazon Athena, & Amazon Redshift Spectrum; Log Analytics with Amazon Elasticsearch Service; and data preparation and placement services with AWS Glue and Amazon Kinesis. You'll will learn how to get started, how to support applications, and how to scale.
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Level: Beginner
Speakers:
Jay Formosa - Solutions Architect, AWS
Aser Moustafa - Data Warehouse Specialist Solutions Architect, AWS
Data Warehousing with Amazon Redshift: Data Analytics Week SFAmazon Web Services
Data Analytics Week at the San Francisco Loft
Data Warehousing with Amazon Redshift
Asser Moustafa - Data Warehouse Specialist Solutions Architect, AWSA closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Speakers:
Jay Formosa - Solutions Architect, AWS
Asser Moustafa - Data Warehouse Specialist Solutions Architect, AWS
by Marie Yap, Enterprise Solutions Architect, AWS
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Data Warehousing with Amazon Redshift: Data Analytics Week at the SF LoftAmazon Web Services
Data Warehousing with Amazon Redshift: Data Analytics Week at the San Francisco Loft
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Level: Beginner
Speakers:
Jay Formosa - Solutions Architect, AWS
Sudhir Gupta - Partner Solutions Architect, Redshift Specialist, AWS
This spring, the data warehouse team at Ancestry, flawlessly migrated and validated nearly half a trillion records from Actian Matrix to Amazon Redshift. During this session, the Ancestry team will describe how they orchestrated the entire migration in less than four months, the technical challenges they faced and overcame along the way, as well as share tips and tricks to break through common pitfalls of data warehouse migrations. They will also highlight how they tuned and optimized the Amazon Redshift environment, adopted Redshift Spectrum, and how they leverage their collaboration with Amazon to deliver a powerful customer experience.
by Peter Dalton, Principal Consultant AWS and Taz Sayed, Sr Technical Account Manager AWS
AWS Data & Analytics Week is an opportunity to learn about Amazon’s family of managed analytics services. These services provide easy, scalable, reliable, and cost-effective ways to manage your data in the cloud. We explain the fundamentals and take a technical deep dive into Amazon Redshift data warehouse; Data Lake services including Amazon EMR, Amazon Athena, & Amazon Redshift Spectrum; Log Analytics with Amazon Elasticsearch Service; and data preparation and placement services with AWS Glue and Amazon Kinesis. You'll will learn how to get started, how to support applications, and how to scale.
Loading Data into Redshift: Data Analytics Week at the SF LoftAmazon Web Services
Loading Data into Redshift: Data Analytics Week at the San Francisco Loft
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Level: Intermediate
Speakers:
Aser Moustafa - Data Warehouse Specialist Solutions Architect, AWS
Vikram Gangulavoipalyam - Enterprise Solutions Architect, AWS
AWS SSA Webinar 20 - Getting Started with Data Warehouses on AWSCobus Bernard
In this session, we will take you through setting up an Amazon Redshift cluster and at the ways you can populate it with data. We will start by using AWS DMS to replicate the data as-is as well as doing some ETL on it. This will be followed by AWS Glue where you can do more advanced ETL operations. Lastly, we will look at how you can use Amazon Kinesis Firehose to stream event directly to the Redshift cluster.
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Level: Intermediate
Speakers:
Jay Formosa - Solutions Architect, AWS
Aser Moustafa - Data Warehouse Specialist Solutions Architect, AWS
Data Analytics Week at the San Francisco Loft
Loading Data Into Redshift
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Speakers:
Jay Formosa - Solutions Architect, AWS
Asser Moustafa - Data Warehouse Specialist Solutions Architect, AWS
by Ben Willett, Solutions Architect, AWS
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Speakers:
Natalie Rabinovich- Solutions Architect, AWS
Gareth Eagar - Solutions Architect, AWS
Analyzing big data quickly and efficiently requires a data warehouse optimized to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyze big data for a fraction of the cost of traditional data warehouses. By following a few best practices, you can take advantage of Amazon Redshift’s columnar technology and parallel processing capabilities to minimize I/O and deliver high throughput and query performance. This webinar will cover techniques to load data efficiently, design optimal schemas, and use work load management.
Learning Objectives:
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to migrate from existing data warehouses, optimize schemas, and load data efficiently
• Learn best practices for managing workload, tuning your queries, and using Amazon Redshift's interleaved sorting features
Who Should Attend:
• Data Warehouse Developers, Big Data Architects, BI Managers, and Data Engineers
Best Practices for Migrating your Data Warehouse to Amazon RedshiftAmazon Web Services
You can gain substantially more business insights and save costs by migrating your existing data warehouse to Amazon Redshift. This session will cover the key benefits of migrating to Amazon Redshift, migration strategies, and tools and resources that can help you in the process.
Similar to ABD304-R-Best Practices for Data Warehousing with Amazon Redshift & Spectrum (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.