This document discusses migrating a large 200+ TB database in less than one day using transportable tablespaces and RMAN incremental backups. It describes a case where a customer needed to migrate over 100 TB of data from an IBM AIX database to an Exadata database running Oracle Linux while having limited downtime of one weekend. Several challenges were encountered, such as backups exceeding file size limits, but solutions like splitting files were used to complete the migration on time.
Las nuevas arquitecturas, servicios y micro-servicios web, aplicaciones y apps, Bots, IoT, AI, etc., que demandan las organizaciones, necesitan cada vez más del talento y experiencia de los Administradores de Bases de Datos para dar consejos, sugerencias y respuestas que aporten un valor diferencial a los grupos de desarrollo y usuarios de negocio.
Te mostramos las claves del nuevo rol del DBA, que complementa la “A” de Administrar con: Analizar, Aconsejar, Automatizar y crear Arquitecturas eficientes y Autónomas para la gestión Avanzada de datos, colaborando con los desarrolladores y usuarios desde un conocimiento profundo de las base de datos.
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataHakka Labs
This document discusses Apache Kudu, an open source columnar storage system for analytics workloads on Hadoop. Kudu is designed to enable both fast analytics queries as well as real-time updates on fast changing data. It aims to fill gaps in the current Hadoop storage landscape by supporting simultaneous high throughput scans, low latency reads/writes, and ACID transactions. An example use case described is for real-time fraud detection on streaming financial data.
Discover & Migrate at Scale with AWS Migration Hub & Application Discovery Se...Amazon Web Services
Over the course of hundreds of mass migrations with our enterprise customers, we've seen migrations of one or more data centers into AWS, and the common theme is that tools are crucial for reliable and fast discovery and migration. In this workshop, you get hands on experience using AWS migration tools like AWS Migration Hub and Application Discovery Service to supercharge planning and execution of your migration and move more servers and databases in less time. Learn how to discover existing servers, analyze server dependencies, group your resources into applications, and automate migrations using AWS and partner migration tools.
IEEE International Conference on Data Engineering 2015Yousun Jeong
SK Telecom developed a Hadoop data warehouse (DW) solution to address the high costs and limitations of traditional DW systems for handling big data. The Hadoop DW provides a scalable architecture using Hadoop, Tajo and Spark to cost-effectively store and analyze over 30PB of data across 1000+ nodes. It offers SQL analytics through Tajo for faster querying and easier migration from RDBMS systems. The Hadoop DW has helped SK Telecom and other customers such as semiconductor manufacturers to more affordably store and process massive volumes of both structured and unstructured data for advanced analytics.
Migrate from Oracle to Aurora PostgreSQL: Best Practices, Design Patterns, & ...Amazon Web Services
In this session, we show you how to set the source Oracle database environment, the target PostgreSQL environment, and parameter group configuration. We also recommended database parameters to disable foreign keys and triggers. Finally, we discuss best practices for using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) and show you how to choose the instance type and configure AWS DMS.
The document discusses Oracle Real Application Clusters (RAC) and provides examples of how it has enabled scalability and high availability for many large customers. It describes how RAC allows databases to scale horizontally across multiple servers, provides several customer cases that have implemented RAC with 4+ nodes, and highlights how RAC provides scalability by design through its instance and global cache architecture.
The document discusses using data virtualization and masking to optimize database migrations to the cloud. It notes that traditional copying of data is inefficient for large environments and can incur high data transfer costs in the cloud. Using data virtualization allows creating virtual copies of production databases that only require a small storage footprint. Masking sensitive data before migrating non-production databases ensures security while reducing costs. Overall, data virtualization and masking enable simpler, more secure, and cost-effective migrations to cloud environments.
This document outlines the steps to execute a database platform migration using Zero Data Loss Recovery Appliance (ZDLRA). It discusses ZDLRA backup and restore strategies using incremental forever backups and virtual full backups for fast restore. The presentation covers both cross-endian and same-endian database migration processes using ZDLRA, including automating steps with the dbmigusera.pl tool. A customer case study shows how a semiconductor manufacturer consolidated databases to Exadata using ZDLRA for near-zero downtime migration.
Las nuevas arquitecturas, servicios y micro-servicios web, aplicaciones y apps, Bots, IoT, AI, etc., que demandan las organizaciones, necesitan cada vez más del talento y experiencia de los Administradores de Bases de Datos para dar consejos, sugerencias y respuestas que aporten un valor diferencial a los grupos de desarrollo y usuarios de negocio.
Te mostramos las claves del nuevo rol del DBA, que complementa la “A” de Administrar con: Analizar, Aconsejar, Automatizar y crear Arquitecturas eficientes y Autónomas para la gestión Avanzada de datos, colaborando con los desarrolladores y usuarios desde un conocimiento profundo de las base de datos.
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataHakka Labs
This document discusses Apache Kudu, an open source columnar storage system for analytics workloads on Hadoop. Kudu is designed to enable both fast analytics queries as well as real-time updates on fast changing data. It aims to fill gaps in the current Hadoop storage landscape by supporting simultaneous high throughput scans, low latency reads/writes, and ACID transactions. An example use case described is for real-time fraud detection on streaming financial data.
Discover & Migrate at Scale with AWS Migration Hub & Application Discovery Se...Amazon Web Services
Over the course of hundreds of mass migrations with our enterprise customers, we've seen migrations of one or more data centers into AWS, and the common theme is that tools are crucial for reliable and fast discovery and migration. In this workshop, you get hands on experience using AWS migration tools like AWS Migration Hub and Application Discovery Service to supercharge planning and execution of your migration and move more servers and databases in less time. Learn how to discover existing servers, analyze server dependencies, group your resources into applications, and automate migrations using AWS and partner migration tools.
IEEE International Conference on Data Engineering 2015Yousun Jeong
SK Telecom developed a Hadoop data warehouse (DW) solution to address the high costs and limitations of traditional DW systems for handling big data. The Hadoop DW provides a scalable architecture using Hadoop, Tajo and Spark to cost-effectively store and analyze over 30PB of data across 1000+ nodes. It offers SQL analytics through Tajo for faster querying and easier migration from RDBMS systems. The Hadoop DW has helped SK Telecom and other customers such as semiconductor manufacturers to more affordably store and process massive volumes of both structured and unstructured data for advanced analytics.
Migrate from Oracle to Aurora PostgreSQL: Best Practices, Design Patterns, & ...Amazon Web Services
In this session, we show you how to set the source Oracle database environment, the target PostgreSQL environment, and parameter group configuration. We also recommended database parameters to disable foreign keys and triggers. Finally, we discuss best practices for using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) and show you how to choose the instance type and configure AWS DMS.
The document discusses Oracle Real Application Clusters (RAC) and provides examples of how it has enabled scalability and high availability for many large customers. It describes how RAC allows databases to scale horizontally across multiple servers, provides several customer cases that have implemented RAC with 4+ nodes, and highlights how RAC provides scalability by design through its instance and global cache architecture.
The document discusses using data virtualization and masking to optimize database migrations to the cloud. It notes that traditional copying of data is inefficient for large environments and can incur high data transfer costs in the cloud. Using data virtualization allows creating virtual copies of production databases that only require a small storage footprint. Masking sensitive data before migrating non-production databases ensures security while reducing costs. Overall, data virtualization and masking enable simpler, more secure, and cost-effective migrations to cloud environments.
This document outlines the steps to execute a database platform migration using Zero Data Loss Recovery Appliance (ZDLRA). It discusses ZDLRA backup and restore strategies using incremental forever backups and virtual full backups for fast restore. The presentation covers both cross-endian and same-endian database migration processes using ZDLRA, including automating steps with the dbmigusera.pl tool. A customer case study shows how a semiconductor manufacturer consolidated databases to Exadata using ZDLRA for near-zero downtime migration.
The document discusses the history and evolution of Oracle Database from its beginnings in 1977 through version 12c. It describes how early versions introduced SQL and basic reliability features, and how subsequent versions added capabilities like distributed processing, transactions, PL/SQL, and Real Application Clusters. It also summarizes how new pluggable database and in-memory technologies in version 12c allow for more efficient consolidation of databases and management of storage.
The document discusses Oracle TimesTen In-Memory Database. It provides an overview of TimesTen Classic, which offers a relational database entirely in memory that provides microsecond response times, high throughput of millions of transactions per second, and high availability through active-standby replication with online rolling upgrades and no application downtime. Examples are given of telecom applications using TimesTen Classic to provide real-time transaction processing with response times under 100 milliseconds and throughput of hundreds of thousands of transactions per second.
Gruter TECHDAY 2014 Realtime Processing in TelcoGruter
Big Telco, Bigger real-time demands: Real-time processing in Telco
- Presented by Jung-ryong Lee, engineer manager at SK Telecom at Gruter TECHDAY 2014 Oct.29 Seoul, Korea
DC Migration and Hadoop Scale For Big Billion DaysRahul Agarwal
Deck from BigData MeetUp - Bangalore.
Presents challenges faced in Migrating Hadoop cluster with 200+ TB compressed data from one data centre to another, from baremetals to cloud, from DNS based systems to infra without DNS.
Hive 3 New Horizons DataWorks Summit Melbourne February 2019alanfgates
Hive 3 new SQL features including LLAP, workload management, SQL over Kafka and JDBC data sources, integration with Spark via Hive Warehouse Connector, ACID 2, and constraints and default values
Apache Hive is a rapidly evolving project which continues to enjoy great adoption in the big data ecosystem. As Hive continues to grow its support for analytics, reporting, and interactive query, the community is hard at work in improving it along with many different dimensions and use cases. This talk will provide an overview of the latest and greatest features and optimizations which have landed in the project over the last year. Materialized views, the extension of ACID semantics to non-ORC data, and workload management are some noteworthy new features.
We will discuss optimizations which provide major performance gains, including significantly improved performance for ACID tables. The talk will also provide a glimpse of what is expected to come in the near future.
Speaker: Alan Gates, Co-Founder, Hortonworks
Seamless replication and disaster recovery for Apache Hive WarehouseDataWorks Summit
As Apache Hadoop clusters become central to an organization’s operations, they have clusters in more than one data center. Historically, this has been largely driven by requirements of business continuity planning or geo localization. It has also recently been gaining a lot of interest from a hybrid cloud perspective, i.e. wherein people are trying to augment their traditional on-prem setup with cloud-based additions as well. A robust replication solution is a fundamental requirement in such cases.
Seamless disaster recovery has several challenges. Data, metadata, and transaction information need to be moved in sync. It should also be easy for the users and applications to reason about the state of the replica. The “hadoop scale” also brings unique challenges as bandwidth between clusters can be a limiting factor. The data transfer has to be minimized for replication, failover, as well as fail back scenarios.
In this talk we will discuss how the above challenges are addressed for supporting seamless replication and disaster recovery for Hive.
Speakers
Sankar Hariappan, Hortonworks, Staff Software Engineer
Anishek Agarwal, Hortonworks, Engineering Manager
Seamless Replication and Disaster Recovery for Apache Hive WarehouseSankar H
As Apache Hadoop clusters become central to an organization’s operations, they have clusters in more than one data center. Historically, this has been largely driven by requirements of business continuity planning or geo localization. It has also recently been gaining a lot of interest from a hybrid cloud perspective, i.e. wherein people are trying to augment their traditional on-prem setup with cloud-based additions as well. A robust replication solution is a fundamental requirement in such cases.
Seamless disaster recovery has several challenges. Data, metadata, and transaction information need to be moved in sync. It should also be easy for the users and applications to reason about the state of the replica. The “hadoop scale” also brings unique challenges as bandwidth between clusters can be a limiting factor. The data transfer has to be minimized for replication, failover, as well as fail back scenarios.
In this talk we will discuss how the above challenges are addressed for supporting seamless replication and disaster recovery for Hive.
Breakout: Hadoop and the Operational Data StoreCloudera, Inc.
As disparate data volumes continue to be operationalized across the enterprise, data will need to be processed, cleansed, transformed, and made available to end users at greater speeds. Traditional ODS systems run into issues when trying to process large data volumes causing operations to be backed up, data to be archived, and ETL/ ELT processes to fail. Join this breakout to learn how to battle these issues.
times ten in-memory database for extreme performanceOracle Korea
어디서나 업무가 가능한 모바일 시대가 되면서 비약적으로 데이터 사이즈가 커지고 이를 처리하기 위해서는 고성능의 빠른 Database가 필요하게 되었습니다. 이러한 요구사항을 반영하여 기존에 우리가 잘 사용하고있던 Database 들도 In-Memory 기술을 속속 도입하고 있습니다. In-Memory 기술은 이전부터 있었지만 하드웨어의 한계와 소프트웨어의 확정성의 부족으로 많이 사용되지 않았던 기술입니다.
Oracle TimesTen 18.1은 기존 In-Memory Database가 가지는 한계를 극복하고, 빠른 처리 속도와 확장(Scaleout)가능한 분산 아키텍처를 지원하는 In-Memory 관계형 Database 입니다.
본 세션에서는 Oracle TimesTen의 분산 아키텍처와 주요 Feature를 소개하고 TimesTen 최신버전인 18.1의 데모를 진행할 예정입니다. 또한 현재 TimesTen을 이용하여 국내 통신사의 서비스를 개발하고 있는 이루온의 실제 적용 사례 및 성능 테스트 결과를 공유하는 시간이 될 것입니다.
Best Practices for Running Oracle Databases on Amazon RDS (DAT317) - AWS re:I...Amazon Web Services
Amazon Relational Database Service (Amazon RDS) continues to be a popular choice for Oracle DBAs moving new and legacy workloads to the cloud. In this session, we discuss how Amazon RDS for Oracle helps DBAs focus their time where it matters most. We cover recent RDS Oracle features, and we go deep on key functionality that enables license optimization, performance, and high availability for Oracle databases. We also hear directly from an AWS customer about their journey to Amazon RDS and the best practices that helped make their move successful.
Apache Hive is a rapidly evolving project which continues to enjoy great adoption in the big data ecosystem. As Hive continues to grow its support for analytics, reporting, and interactive query, the community is hard at work in improving it along with many different dimensions and use cases. This talk will provide an overview of the latest and greatest features and optimizations which have landed in the project over the last year. Materialized views, the extension of ACID semantics to non-ORC data, and workload management are some noteworthy new features.
We will discuss optimizations which provide major performance gains, including significantly improved performance for ACID tables. The talk will also provide a glimpse of what is expected to come in the near future.
Exploring All options to move your Oracle Databases to the Oracle CloudAlex Zaballa
This document discusses various options for migrating Oracle databases to the Oracle Cloud. It begins with an introduction to Alex Zaballa and his background and experience. It then discusses Accenture Enkitec Group's capabilities in Oracle Engineered Systems implementations and Oracle technologies. The remainder of the document discusses specific methods for migrating databases to the Oracle Cloud, including using Oracle Database Cloud Service, choosing appropriate migration methods based on factors like database version and downtime tolerance, and techniques like using Oracle Database Cloud Backup Module or Data Pump to perform the migration.
Traditional data warehouses become expensive and slow down as the volume of your data grows. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it easy to analyze all of your data using existing business intelligence tools for 1/10th the traditional cost. This session will provide an introduction to Amazon Redshift and cover the essentials you need to deploy your data warehouse in the cloud so that you can achieve faster analytics and save costs. We’ll also cover the recently announced Redshift Spectrum, which allows you to query unstructured data directly from Amazon S3.
The document discusses transforming data management to the cloud. It describes how Oracle's database cloud services provide complete data management across multiple data types at any scale both on-premises and in the cloud. It highlights how the cloud offers lower costs through pay-as-you-go pricing and lower operational expenses, as well as increased agility through rapid provisioning and elastic scaling. Oracle 12c and new features in 12c Release 2 provide database consolidation, isolation at scale, and online operations for pluggable databases in the cloud.
Oracle RDBMS is the most widely used of the commercial relational databases. We’ll look at how to run Oracle on the AWS Cloud, with examples of organizations using it.
Galaxy Big Data with MariaDB 10 by Bernard Garros, Sandrine Chirokoff and Stéphane Varoqui.
Presented 26.6.2014 at the MariaDB Roadshow in Paris, France.
by Ben Willett, Solutions Architect, AWS
Database Week at the AWS Loft is an opportunity to learn about Amazon’s broad and deep family of managed database 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 RDS and Amazon Aurora relational databases, Amazon DynamoDB non-relational databases, Amazon Neptune graph databases, and Amazon ElastiCache managed Redis, along with options for database migration, caching, search and more. You'll will learn how to get started, how to support applications, and how to scale.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
The document discusses the history and evolution of Oracle Database from its beginnings in 1977 through version 12c. It describes how early versions introduced SQL and basic reliability features, and how subsequent versions added capabilities like distributed processing, transactions, PL/SQL, and Real Application Clusters. It also summarizes how new pluggable database and in-memory technologies in version 12c allow for more efficient consolidation of databases and management of storage.
The document discusses Oracle TimesTen In-Memory Database. It provides an overview of TimesTen Classic, which offers a relational database entirely in memory that provides microsecond response times, high throughput of millions of transactions per second, and high availability through active-standby replication with online rolling upgrades and no application downtime. Examples are given of telecom applications using TimesTen Classic to provide real-time transaction processing with response times under 100 milliseconds and throughput of hundreds of thousands of transactions per second.
Gruter TECHDAY 2014 Realtime Processing in TelcoGruter
Big Telco, Bigger real-time demands: Real-time processing in Telco
- Presented by Jung-ryong Lee, engineer manager at SK Telecom at Gruter TECHDAY 2014 Oct.29 Seoul, Korea
DC Migration and Hadoop Scale For Big Billion DaysRahul Agarwal
Deck from BigData MeetUp - Bangalore.
Presents challenges faced in Migrating Hadoop cluster with 200+ TB compressed data from one data centre to another, from baremetals to cloud, from DNS based systems to infra without DNS.
Hive 3 New Horizons DataWorks Summit Melbourne February 2019alanfgates
Hive 3 new SQL features including LLAP, workload management, SQL over Kafka and JDBC data sources, integration with Spark via Hive Warehouse Connector, ACID 2, and constraints and default values
Apache Hive is a rapidly evolving project which continues to enjoy great adoption in the big data ecosystem. As Hive continues to grow its support for analytics, reporting, and interactive query, the community is hard at work in improving it along with many different dimensions and use cases. This talk will provide an overview of the latest and greatest features and optimizations which have landed in the project over the last year. Materialized views, the extension of ACID semantics to non-ORC data, and workload management are some noteworthy new features.
We will discuss optimizations which provide major performance gains, including significantly improved performance for ACID tables. The talk will also provide a glimpse of what is expected to come in the near future.
Speaker: Alan Gates, Co-Founder, Hortonworks
Seamless replication and disaster recovery for Apache Hive WarehouseDataWorks Summit
As Apache Hadoop clusters become central to an organization’s operations, they have clusters in more than one data center. Historically, this has been largely driven by requirements of business continuity planning or geo localization. It has also recently been gaining a lot of interest from a hybrid cloud perspective, i.e. wherein people are trying to augment their traditional on-prem setup with cloud-based additions as well. A robust replication solution is a fundamental requirement in such cases.
Seamless disaster recovery has several challenges. Data, metadata, and transaction information need to be moved in sync. It should also be easy for the users and applications to reason about the state of the replica. The “hadoop scale” also brings unique challenges as bandwidth between clusters can be a limiting factor. The data transfer has to be minimized for replication, failover, as well as fail back scenarios.
In this talk we will discuss how the above challenges are addressed for supporting seamless replication and disaster recovery for Hive.
Speakers
Sankar Hariappan, Hortonworks, Staff Software Engineer
Anishek Agarwal, Hortonworks, Engineering Manager
Seamless Replication and Disaster Recovery for Apache Hive WarehouseSankar H
As Apache Hadoop clusters become central to an organization’s operations, they have clusters in more than one data center. Historically, this has been largely driven by requirements of business continuity planning or geo localization. It has also recently been gaining a lot of interest from a hybrid cloud perspective, i.e. wherein people are trying to augment their traditional on-prem setup with cloud-based additions as well. A robust replication solution is a fundamental requirement in such cases.
Seamless disaster recovery has several challenges. Data, metadata, and transaction information need to be moved in sync. It should also be easy for the users and applications to reason about the state of the replica. The “hadoop scale” also brings unique challenges as bandwidth between clusters can be a limiting factor. The data transfer has to be minimized for replication, failover, as well as fail back scenarios.
In this talk we will discuss how the above challenges are addressed for supporting seamless replication and disaster recovery for Hive.
Breakout: Hadoop and the Operational Data StoreCloudera, Inc.
As disparate data volumes continue to be operationalized across the enterprise, data will need to be processed, cleansed, transformed, and made available to end users at greater speeds. Traditional ODS systems run into issues when trying to process large data volumes causing operations to be backed up, data to be archived, and ETL/ ELT processes to fail. Join this breakout to learn how to battle these issues.
times ten in-memory database for extreme performanceOracle Korea
어디서나 업무가 가능한 모바일 시대가 되면서 비약적으로 데이터 사이즈가 커지고 이를 처리하기 위해서는 고성능의 빠른 Database가 필요하게 되었습니다. 이러한 요구사항을 반영하여 기존에 우리가 잘 사용하고있던 Database 들도 In-Memory 기술을 속속 도입하고 있습니다. In-Memory 기술은 이전부터 있었지만 하드웨어의 한계와 소프트웨어의 확정성의 부족으로 많이 사용되지 않았던 기술입니다.
Oracle TimesTen 18.1은 기존 In-Memory Database가 가지는 한계를 극복하고, 빠른 처리 속도와 확장(Scaleout)가능한 분산 아키텍처를 지원하는 In-Memory 관계형 Database 입니다.
본 세션에서는 Oracle TimesTen의 분산 아키텍처와 주요 Feature를 소개하고 TimesTen 최신버전인 18.1의 데모를 진행할 예정입니다. 또한 현재 TimesTen을 이용하여 국내 통신사의 서비스를 개발하고 있는 이루온의 실제 적용 사례 및 성능 테스트 결과를 공유하는 시간이 될 것입니다.
Best Practices for Running Oracle Databases on Amazon RDS (DAT317) - AWS re:I...Amazon Web Services
Amazon Relational Database Service (Amazon RDS) continues to be a popular choice for Oracle DBAs moving new and legacy workloads to the cloud. In this session, we discuss how Amazon RDS for Oracle helps DBAs focus their time where it matters most. We cover recent RDS Oracle features, and we go deep on key functionality that enables license optimization, performance, and high availability for Oracle databases. We also hear directly from an AWS customer about their journey to Amazon RDS and the best practices that helped make their move successful.
Apache Hive is a rapidly evolving project which continues to enjoy great adoption in the big data ecosystem. As Hive continues to grow its support for analytics, reporting, and interactive query, the community is hard at work in improving it along with many different dimensions and use cases. This talk will provide an overview of the latest and greatest features and optimizations which have landed in the project over the last year. Materialized views, the extension of ACID semantics to non-ORC data, and workload management are some noteworthy new features.
We will discuss optimizations which provide major performance gains, including significantly improved performance for ACID tables. The talk will also provide a glimpse of what is expected to come in the near future.
Exploring All options to move your Oracle Databases to the Oracle CloudAlex Zaballa
This document discusses various options for migrating Oracle databases to the Oracle Cloud. It begins with an introduction to Alex Zaballa and his background and experience. It then discusses Accenture Enkitec Group's capabilities in Oracle Engineered Systems implementations and Oracle technologies. The remainder of the document discusses specific methods for migrating databases to the Oracle Cloud, including using Oracle Database Cloud Service, choosing appropriate migration methods based on factors like database version and downtime tolerance, and techniques like using Oracle Database Cloud Backup Module or Data Pump to perform the migration.
Traditional data warehouses become expensive and slow down as the volume of your data grows. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it easy to analyze all of your data using existing business intelligence tools for 1/10th the traditional cost. This session will provide an introduction to Amazon Redshift and cover the essentials you need to deploy your data warehouse in the cloud so that you can achieve faster analytics and save costs. We’ll also cover the recently announced Redshift Spectrum, which allows you to query unstructured data directly from Amazon S3.
The document discusses transforming data management to the cloud. It describes how Oracle's database cloud services provide complete data management across multiple data types at any scale both on-premises and in the cloud. It highlights how the cloud offers lower costs through pay-as-you-go pricing and lower operational expenses, as well as increased agility through rapid provisioning and elastic scaling. Oracle 12c and new features in 12c Release 2 provide database consolidation, isolation at scale, and online operations for pluggable databases in the cloud.
Oracle RDBMS is the most widely used of the commercial relational databases. We’ll look at how to run Oracle on the AWS Cloud, with examples of organizations using it.
Galaxy Big Data with MariaDB 10 by Bernard Garros, Sandrine Chirokoff and Stéphane Varoqui.
Presented 26.6.2014 at the MariaDB Roadshow in Paris, France.
by Ben Willett, Solutions Architect, AWS
Database Week at the AWS Loft is an opportunity to learn about Amazon’s broad and deep family of managed database 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 RDS and Amazon Aurora relational databases, Amazon DynamoDB non-relational databases, Amazon Neptune graph databases, and Amazon ElastiCache managed Redis, along with options for database migration, caching, search and more. You'll will learn how to get started, how to support applications, and how to scale.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on automated letter generation for Bonterra Impact Management using Google Workspace or Microsoft 365.
Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfflufftailshop
When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟