Gain in-depth knowledge and best practices for migrating commercial data warehouses to Amazon Redshift using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT). We use an example based on an Oracle data warehouse, and we discuss approaches to migrate it to Amazon Redshift. We also discuss some of the common challenges, limitations, and workarounds, as well as the option of using AWS Snowball to migrate very large data warehouses to Amazon Redshift.
Learning Objectives:
- Learn the common use-cases for using Athena, AWS' interactive query service on S3
- Learn best practices for creating tables and partitions and performance optimizations
- Learn how Athena handles security, authorization, and authentication
by Darin Briskman, Technical Evangelist, AWS
Database Freedom means being able to use the database engine that’s right for you as your needs evolve. Being locked into a specific technology can prevent you from achieving your mission. Fortunately, AWS Database Migration Service makes it easy to switch between different database engines. We’ll look at how to use Schema Migration Tool with DMS to switch from a commercial database to open source. You’ll need a laptop with a Firefox or Chrome browser.
In this session, we introduce AWS Glue, provide an overview of its components, and share how you can use AWS Glue to automate discovering your data, cataloging it, and preparing it for analysis.
More and more enterprise companies are migrating to the AWS Cloud and there are a number of reasons why. While every organization is going to have their own unique motivations, common drivers include exiting data centers, increasing business agility, improving workforce productivity, gaining transparency in operational costs and reducing risk.
The AWS Migration Acceleration Program (MAP) is designed to help enterprises that are committed to a migration journey achieve a range of these business benefits by migrating existing workloads to Amazon Web Services. In this session, you will learn about proven migration patterns, methods and tools that AWS has delivered successfully to hundreds of enterprise customers globally that will help you accelerate migrations, reduce risk and quickly realize value.
Learning Objectives:
- Learn the common use-cases for using Athena, AWS' interactive query service on S3
- Learn best practices for creating tables and partitions and performance optimizations
- Learn how Athena handles security, authorization, and authentication
by Darin Briskman, Technical Evangelist, AWS
Database Freedom means being able to use the database engine that’s right for you as your needs evolve. Being locked into a specific technology can prevent you from achieving your mission. Fortunately, AWS Database Migration Service makes it easy to switch between different database engines. We’ll look at how to use Schema Migration Tool with DMS to switch from a commercial database to open source. You’ll need a laptop with a Firefox or Chrome browser.
In this session, we introduce AWS Glue, provide an overview of its components, and share how you can use AWS Glue to automate discovering your data, cataloging it, and preparing it for analysis.
More and more enterprise companies are migrating to the AWS Cloud and there are a number of reasons why. While every organization is going to have their own unique motivations, common drivers include exiting data centers, increasing business agility, improving workforce productivity, gaining transparency in operational costs and reducing risk.
The AWS Migration Acceleration Program (MAP) is designed to help enterprises that are committed to a migration journey achieve a range of these business benefits by migrating existing workloads to Amazon Web Services. In this session, you will learn about proven migration patterns, methods and tools that AWS has delivered successfully to hundreds of enterprise customers globally that will help you accelerate migrations, reduce risk and quickly realize value.
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
Delta Lake delivers reliability, security and performance to data lakes. Join this session to learn how customers have achieved 48x faster data processing, leading to 50% faster time to insight after implementing Delta Lake. You’ll also learn how Delta Lake provides the perfect foundation for a cost-effective, highly scalable lakehouse architecture.
How will my on-premises data migrate to the cloud? How can I make it transparent to my users? Afterwards, how will on-premises and cloud data interact? In this session you will learn about the AWS Database Migration Service (DMS) and the AWS Schema Migration Tool (SCT). You can use these tools to convert your commercial database and database warehouse to open-source engines or AWS-native services, such as Amazon Aurora and Redshift.
Speakers:
Saurabh Saxena - Principal Technical Account Manager, AWS
Chris England - Sr. Technical Account Manager, AWS
Migrating Your Oracle Database to PostgreSQL - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the capabilities of the PostgreSQL database
- Learn about PostgreSQL offerings on AWS
- Learn how to migrate from Oracle to PostgreSQL with minimal disruption
In this full-day workshop, you will learn strategies for planning and migrating existing workloads to the AWS Cloud, including basic knowledge of planning for a migration, Application Discovery Service, AWS Migration Hub, Migration Tools e.g. CloudEndure, how to do data transfer, and last but not least, AWS Database Migration Services. There are altogether 5 modules, each represents a deep dive on the topics suggested. The first half provides an overview of migration planning principles and best practices, and the second part focuses on migration design, tools and implementation, with hands-on labs to reinforce concepts.
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.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
In this webinar, we’ll show you how Cloudera SDX reduces the complexity in your data management environment and lets you deliver diverse analytics with consistent security, governance, and lifecycle management against a shared data catalog.
Introducing Delta Live Tables: Make Reliable ETL Easy on Delta LakeDatabricks
As the size and complexity of data grows, building reliable data pipelines is increasingly important, but also complex and challenging. Learn how Delta Live Tables simplifies the ETL lifecycle on Delta Lake, helping data engineering teams greatly simplify ETL development and ongoing management to improve data quality, scale operations, and reduce cost.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
How to build a data lake with aws glue data catalog (ABD213-R) re:Invent 2017Amazon Web Services
As data volumes grow and customers store more data on AWS, they often have valuable data that is not easily discoverable and available for analytics. The AWS Glue Data Catalog provides a central view of your data lake, making data readily available for analytics. We introduce key features of the AWS Glue Data Catalog and its use cases. Learn how crawlers can automatically discover your data, extract relevant metadata, and add it as table definitions to the AWS Glue Data Catalog. We will also explore the integration between AWS Glue Data Catalog and Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Lambda Architecture in the Cloud with Azure Databricks with Andrei VaranovichDatabricks
The term “Lambda Architecture” stands for a generic, scalable and fault-tolerant data processing architecture. As the hyper-scale now offers a various PaaS services for data ingestion, storage and processing, the need for a revised, cloud-native implementation of the lambda architecture is arising.
In this talk we demonstrate the blueprint for such an implementation in Microsoft Azure, with Azure Databricks — a PaaS Spark offering – as a key component. We go back to some core principles of functional programming and link them to the capabilities of Apache Spark for various end-to-end big data analytics scenarios.
We also illustrate the “Lambda architecture in use” and the associated tread-offs using the real customer scenario – Rijksmuseum in Amsterdam – a terabyte-scale Azure-based data platform handles data from 2.500.000 visitors per year.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. You can create and run an ETL job with a few clicks in the AWS Management Console. You simply point AWS Glue to your data stored on AWS, and AWS Glue discovers your data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, your data is immediately searchable, queryable, and available for ETL. AWS Glue generates the code to execute your data transformations and data loading processes.
Level: Intermediate
Speakers:
Ryan Malecky - Solutions Architect, EdTech, AWS
Rajakumar Sampathkumar - Sr. Technical Account Manager, AWS
Accelerate Oracle to Aurora PostgreSQL Migration (GPSTEC313) - AWS re:Invent ...Amazon Web Services
There is a lot of interest these days in migrating data from commercial relational databases to open-source relational databases. PostgreSQL is a great choice for migration, offering advanced features, high performance, rock-solid data integrity, and a flexible open-source license. PostgreSQL is compliant with ANSI SQL. It supports drivers for nearly all development languages, and it has a strong community of active committers and companies to provide support. In this talk, we demonstrate an overall approach for migrating an application from your current Oracle database to an Amazon Aurora PostgreSQL database.
An Overview of Best Practices for Large Scale Migrations - AWS Transformation...Amazon Web Services
Whether you are moving a small application or entire datacenters, migrating to the cloud can be a complex process. In this session, we will share some of the common challenges that our customers face on their journey to the cloud and discuss how these challenges can be overcome. We will outline the patterns of success that we have observed from partnering with hundreds of customers on their large-scale migrations as well as highlight the mechanisms we have created to help our customers migrate faster.
About the Event:
AWS Transformation Day is designed for enterprise organizations migrating to the cloud to become more responsive, agile and innovative, while staying secure and compliant. Join us for this one-day event and we’ll share our experiences of helping enterprise customers accelerate the pace of migration and adoption of strategic services.
Who should attend?
This event is recommended for IT and business leaders who are looking to create sustainable benefits and a competitive advantage by using the AWS Cloud. CIOs, CTOs, CISOs, CDOs, CFOs, IT leaders and IT professionals, enterprise developers, business decision makers, and finance executives.
AWS Cost Management Workshop at the San Francisco Loft
AWS offers a number of products that allow you to access, organize, understand, optimize, and control your AWS costs and usage. This workshop will help you get started using AWS Cost Explorer to visualize your usage patterns and identify your underlying cost drivers. From there, you can take action on your insights by learning how to set custom cost and usage budgets and receive alerts via email or Amazon SNS topic using AWS Budgets.
Amazon Athena is a new serverless query service that makes it easy to analyze data in Amazon S3, using standard SQL. With Athena, there is no infrastructure to setup or manage, and you can start analyzing your data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3.
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Toronto ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases across the world. This includes homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Atlanta ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases all over the world. This includes homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB, and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
Delta Lake delivers reliability, security and performance to data lakes. Join this session to learn how customers have achieved 48x faster data processing, leading to 50% faster time to insight after implementing Delta Lake. You’ll also learn how Delta Lake provides the perfect foundation for a cost-effective, highly scalable lakehouse architecture.
How will my on-premises data migrate to the cloud? How can I make it transparent to my users? Afterwards, how will on-premises and cloud data interact? In this session you will learn about the AWS Database Migration Service (DMS) and the AWS Schema Migration Tool (SCT). You can use these tools to convert your commercial database and database warehouse to open-source engines or AWS-native services, such as Amazon Aurora and Redshift.
Speakers:
Saurabh Saxena - Principal Technical Account Manager, AWS
Chris England - Sr. Technical Account Manager, AWS
Migrating Your Oracle Database to PostgreSQL - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the capabilities of the PostgreSQL database
- Learn about PostgreSQL offerings on AWS
- Learn how to migrate from Oracle to PostgreSQL with minimal disruption
In this full-day workshop, you will learn strategies for planning and migrating existing workloads to the AWS Cloud, including basic knowledge of planning for a migration, Application Discovery Service, AWS Migration Hub, Migration Tools e.g. CloudEndure, how to do data transfer, and last but not least, AWS Database Migration Services. There are altogether 5 modules, each represents a deep dive on the topics suggested. The first half provides an overview of migration planning principles and best practices, and the second part focuses on migration design, tools and implementation, with hands-on labs to reinforce concepts.
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.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
In this webinar, we’ll show you how Cloudera SDX reduces the complexity in your data management environment and lets you deliver diverse analytics with consistent security, governance, and lifecycle management against a shared data catalog.
Introducing Delta Live Tables: Make Reliable ETL Easy on Delta LakeDatabricks
As the size and complexity of data grows, building reliable data pipelines is increasingly important, but also complex and challenging. Learn how Delta Live Tables simplifies the ETL lifecycle on Delta Lake, helping data engineering teams greatly simplify ETL development and ongoing management to improve data quality, scale operations, and reduce cost.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
How to build a data lake with aws glue data catalog (ABD213-R) re:Invent 2017Amazon Web Services
As data volumes grow and customers store more data on AWS, they often have valuable data that is not easily discoverable and available for analytics. The AWS Glue Data Catalog provides a central view of your data lake, making data readily available for analytics. We introduce key features of the AWS Glue Data Catalog and its use cases. Learn how crawlers can automatically discover your data, extract relevant metadata, and add it as table definitions to the AWS Glue Data Catalog. We will also explore the integration between AWS Glue Data Catalog and Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Lambda Architecture in the Cloud with Azure Databricks with Andrei VaranovichDatabricks
The term “Lambda Architecture” stands for a generic, scalable and fault-tolerant data processing architecture. As the hyper-scale now offers a various PaaS services for data ingestion, storage and processing, the need for a revised, cloud-native implementation of the lambda architecture is arising.
In this talk we demonstrate the blueprint for such an implementation in Microsoft Azure, with Azure Databricks — a PaaS Spark offering – as a key component. We go back to some core principles of functional programming and link them to the capabilities of Apache Spark for various end-to-end big data analytics scenarios.
We also illustrate the “Lambda architecture in use” and the associated tread-offs using the real customer scenario – Rijksmuseum in Amsterdam – a terabyte-scale Azure-based data platform handles data from 2.500.000 visitors per year.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. You can create and run an ETL job with a few clicks in the AWS Management Console. You simply point AWS Glue to your data stored on AWS, and AWS Glue discovers your data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, your data is immediately searchable, queryable, and available for ETL. AWS Glue generates the code to execute your data transformations and data loading processes.
Level: Intermediate
Speakers:
Ryan Malecky - Solutions Architect, EdTech, AWS
Rajakumar Sampathkumar - Sr. Technical Account Manager, AWS
Accelerate Oracle to Aurora PostgreSQL Migration (GPSTEC313) - AWS re:Invent ...Amazon Web Services
There is a lot of interest these days in migrating data from commercial relational databases to open-source relational databases. PostgreSQL is a great choice for migration, offering advanced features, high performance, rock-solid data integrity, and a flexible open-source license. PostgreSQL is compliant with ANSI SQL. It supports drivers for nearly all development languages, and it has a strong community of active committers and companies to provide support. In this talk, we demonstrate an overall approach for migrating an application from your current Oracle database to an Amazon Aurora PostgreSQL database.
An Overview of Best Practices for Large Scale Migrations - AWS Transformation...Amazon Web Services
Whether you are moving a small application or entire datacenters, migrating to the cloud can be a complex process. In this session, we will share some of the common challenges that our customers face on their journey to the cloud and discuss how these challenges can be overcome. We will outline the patterns of success that we have observed from partnering with hundreds of customers on their large-scale migrations as well as highlight the mechanisms we have created to help our customers migrate faster.
About the Event:
AWS Transformation Day is designed for enterprise organizations migrating to the cloud to become more responsive, agile and innovative, while staying secure and compliant. Join us for this one-day event and we’ll share our experiences of helping enterprise customers accelerate the pace of migration and adoption of strategic services.
Who should attend?
This event is recommended for IT and business leaders who are looking to create sustainable benefits and a competitive advantage by using the AWS Cloud. CIOs, CTOs, CISOs, CDOs, CFOs, IT leaders and IT professionals, enterprise developers, business decision makers, and finance executives.
AWS Cost Management Workshop at the San Francisco Loft
AWS offers a number of products that allow you to access, organize, understand, optimize, and control your AWS costs and usage. This workshop will help you get started using AWS Cost Explorer to visualize your usage patterns and identify your underlying cost drivers. From there, you can take action on your insights by learning how to set custom cost and usage budgets and receive alerts via email or Amazon SNS topic using AWS Budgets.
Amazon Athena is a new serverless query service that makes it easy to analyze data in Amazon S3, using standard SQL. With Athena, there is no infrastructure to setup or manage, and you can start analyzing your data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3.
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Toronto ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases across the world. This includes homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Atlanta ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases all over the world. This includes homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB, and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Chicago ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases across the world. This includes homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB, and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
Convert and Migrate Your NoSQL Database or Data Warehouse to AWS - July 2017Amazon Web Services
Learning Objectives:
- Understand the use cases for migrating or replicating databases to the cloud
- Learn about the benefits of cloud-native databases for performance and costs reduction
- See how AWS Database Migration Service helps with your migration and how AWS Schema Conversion Tool makes conversions simple and quick
Moving or replicating your databases to the cloud should be simple and inexpensive. AWS has recently enhanced the AWS Database Migration Service and the AWS Schema Conversion Tool with new data sources to increase your migration options. You can now export from MongoDB databases and Greenplum, IBM Netezza, HPE Vertica, Teradata, Oracle DW and Microsoft SQL Server data warehouses to AWS. Learn how to export and migrate your data and procedural code with minimal downtime to the cloud database of your choice, including cloud-native offerings such as Amazon Aurora, Amazon DynamoDB and Amazon Redshift.
Convert and Migrate Your NoSQL Database or Data Warehouse to AWS - May 2017 A...Amazon Web Services
Learning Objectives:
- Understand the use cases for migrating or replicating databases to the cloud
- Learn about the benefits of cloud-native databases for performance and costs reduction
- See how AWS Database Migration Service helps with your migration
- See how AWS Schema Conversion Tool makes conversions simple and quick
Moving or replicating your databases to the cloud should be simple and inexpensive. AWS has recently enhanced the AWS Database Migration Service and the AWS Schema Conversion Tool with new data sources to increase your migration options. You can now export from MongoDB databases and Greenplum, IBM Netezza, HPE Vertica, Teradata, Oracle DW and Microsoft SQL Server data warehouses to AWS. Learn how to export and migrate your data and procedural code with minimal downtime to the cloud database of your choice, including cloud-native offerings such as Amazon Aurora, Amazon DynamoDB and Amazon Redshift.
Running SQL Server on Amazon RDS and Migrating to MySQL (DAT306-R1) - AWS re:...Amazon Web Services
If you'd like to move your SQL Server databases to the cloud, this workshop is for you. We review the basics of Amazon Relational Database Service (Amazon RDS) and how SQL Server databases run in Amazon RDS. We then leverage the combination of AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS), and we show you how to migrate your databases to Amazon Aurora MySQL. We provide an AWS CloudFormation template to set up the entire environment for the lab. You need a laptop with a Firefox or Chrome browser and a working AWS account.
Customers are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop, Spark, and data warehouse appliances from on-premise deployments to AWS in order to save costs, increase availability, and improve performance. AWS offers a broad set of analytics services, including solutions for batch processing, stream processing, machine learning, data workflow orchestration, and data warehousing. This session will focus on identifying the components and workflows in your current environment; and providing the best practices to migrate these workloads to the right AWS data analytics product. We will cover services such as Amazon EMR, Amazon Athena, Amazon Redshift, Amazon Kinesis, and more. We will also feature Vanguard, an American investment management company based in Malvern, Pennsylvania with over $4.4 trillion in assets under management. Ritesh Shah, Sr. Program Manager for Cloud Analytics Program at Vanguard, will describe how they orchestrated their migration to AWS analytics services, including Hadoop and Spark workloads to Amazon EMR. Ritesh will highlight the technical challenges they faced and overcame along the way, as well as share common recommendations and tuning tips to accelerate the time to production.
Your data has value for multiple business functions in your organization. Shorten your time to analytics and take faster, better decisions based on data.
In this session you will learn how you can access your data from a myriad of tools such as multiple EMR clusters, Athena & Redshift.
SQL Server to Amazon Aurora Migration, Step by Step (DAT405) - AWS re:Invent ...Amazon Web Services
In this session, learn best practices and tips for migrating SQL Server databases to Amazon Aurora. We use a combination of automated tools such as AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS), manual procedures, and DBA know-how. We take questions on Amazon Aurora architecture and capabilities, how they compare to Microsoft technologies, and how to migrate core SQL Server features, capabilities, and schema objects to their AWS equivalent counterparts.
Using data lakes to quench your analytics fire - AWS Summit Cape Town 2018Amazon Web Services
Speaker: Shafreen Sayyed, AWS
Level: 200
Traditional data storage and analytic tools no longer provide the agility and flexibility required to deliver relevant business insights. We are seeing more and more organisations shift to a data lake solution. This approach allows you to store massive amounts of data in a central location so its readily available to be categorized, processed, analyzed, and consumed by diverse organizational groups. In this session, we’ll assemble a data lake using services such as Amazon S3, Amazon Kinesis, Amazon Athena, Amazon EMR, AWS Glue and integration with Amazon Redshift Spectrum.
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
Migrating Databases to the Cloud with AWS Database Migration Service (DAT207)...Amazon Web Services
Learn how to convert and migrate your relational databases, nonrelational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) can help with homogeneous migrations as well as migrations between different database engines, such as Oracle or SQL Server, to Amazon Aurora. Hear from Verizon about how they intend to migrate critical databases to Amazon Aurora with PostgreSQL compatibility from their current on-premises Oracle databases, and learn how they intend to deal with challenges such as conversion of legacy code and complex data types, supporting business resiliency, and maintaining data synchronization during the transition phase.
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
Migrating Your Oracle Database to PostgreSQL - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the capabilities of the PostgreSQL database
- Learn about PostgreSQL offerings on AWS
- Learn how to migrate from Oracle to PostgreSQL with minimal disruption
Migrating Databases to the Cloud: Introduction to AWS DMS - SRV215 - Anaheim ...Amazon Web Services
In this introductory session, we cover how to convert and migrate your relational databases, non-relational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) have been used to migrate tens of thousands of databases across the world, including homogeneous migrations, such as PostgreSQL to PostgreSQL, and heterogeneous migrations between different database engines, such as Oracle or SQL Server to Amazon Aurora, Amazon DynamoDB, and Amazon Redshift. Learn how to quickly and securely migrate your data and procedural code, enjoy flexibility and cost savings, and minimize the downtime of your applications.
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.
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.
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
Replicate & Manage Data Using Managed Databases & Serverless Technologies (DA...Amazon Web Services
Organizations often have disparate datasets and find it challenging to replicate and analyze the data to drive positive business outcomes. This workshop leverages AWS managed database services and serverless technologies to help replicate, manage, and analyze data using an MLB dataset. We replicate a SQL Server database to Amazon Aurora Serverless using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool. At the same time, we use AWS Glue, a serverless ETL service, to transform and load the data to Amazon S3. We then use Amazon Athena to interactively analyze data using SQL to enable better business decisions. In the course of this workshop, we use: Amazon EC2, Amazon Aurora Serverless, AWS DMS, Amazon Athena, AWS Glue, and Amazon S3. Have an AWS account and some experience with databases and SQL. Bring your own laptop
Similar to Migrating Your Data Warehouse to Amazon Redshift (DAT337) - AWS re:Invent 2018 (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.