Manage Microservices & Fast Data Systems on One Platform w/ DC/OSMesosphere Inc.
This document provides an overview of Mesosphere DC/OS and its benefits. It begins with an introduction to the challenges of building data-intensive applications at scale. It then outlines how Mesosphere DC/OS provides a unified platform for containers and data services across infrastructure with automation and architectural control. Key benefits highlighted include speed, cost savings, and ensuring necessary skills. The document concludes with examples of how Mesosphere is powering industry leaders and a demo.
There is increased interest in using Kubernetes, the open-source container orchestration system for modern, stateful Big Data analytics workloads. The promised land is a unified platform that can handle cloud native stateless and stateful Big Data applications. However, stateful, multi-service Big Data cluster orchestration brings unique challenges. This session will delve into the technical gaps and considerations for Big Data on Kubernetes.
Containers offer significant value to businesses; including increased developer agility, and the ability to move applications between on-premises servers, cloud instances, and across data centers. Organizations have embarked on this journey to containerization with an emphasis on stateless workloads. Stateless applications are usually microservices or containerized applications that don’t “store” data. Web services (such as front end UIs and simple, content-centric experiences) are often great candidates as stateless applications since HTTP is stateless by nature. There is no dependency on the local container storage for the stateless workload.
Stateful applications, on the other hand, are services that require backing storage and keeping state is critical to running the service. Hadoop, Spark and to lesser extent, noSQL platforms such as Cassandra, MongoDB, Postgres, and mySQL are great examples. They require some form of persistent storage that will survive service restarts...
Speakers
Anant Chintamaneni, VP Products, BlueData
Nanda Vijaydev, Director Solutions, BlueData
SQL Server 2017 on Linux
- SQL Server 2017 will run natively on Linux
- It provides the same features and capabilities as SQL Server on Windows
- It supports the same editions as Windows and can be licensed with the same license
- It has the same database engine and core services as Windows
- Some advanced features like PolyBase and Stretch Database are not yet supported on Linux
- It uses a new platform abstraction layer to run on Linux
Partha Seetala is the CTO of Robin Systems, which provides a Kubernetes platform for running big data, NoSQL, database, and AI/ML workloads. Robin addresses challenges with containerizing these applications, such as resource management and storage and networking issues. Robin's solution allows applications to drive infrastructure configuration for improved user experience with capabilities like one-click provisioning, scaling, cloning, backup, and migration of applications across clouds.
MySQL Cluster - Latest Developments (up to and including MySQL Cluster 7.4)Andrew Morgan
MySQL Cluster is the distributed, shared-nothing version of MySQL. It’s typically used for applications that need any combination of high availability, real-time performance, and scaling of reads and writes. After a brief introduction to the technology, its uses, and the new features added in MySQL Cluster 7.3, this session focuses on the very latest developments happening in MySQL Cluster 7.4. As you’d expect from a real-time, scalable, distributed, in-memory database, performance continues to be a top priority, as do simplicity of use and robustness. Come hear firsthand what’s being done to make sure MySQL Cluster continues to dominate in mission-critical, high-performance applications.
Insights into Real-world Data Management ChallengesDataWorks Summit
Oracle began with the belief that the foundation of IT was managing information. The Oracle Cloud Platform for Big Data is a natural extension of our belief in the power of data. Oracle’s Integrated Cloud is one cloud for the entire business, meeting everyone’s needs. It’s about Connecting people to information through tools which help you combine and aggregate data from any source.
This session will explore how organizations can transition to the cloud by delivering fully managed and elastic Hadoop and Real-time Streaming cloud services to built robust offerings that provide measurable value to the business. We will explore key data management trends and dive deeper into pain points we are hearing about from our customer base.
Apache Spark is a fast, general-purpose, and easy-to-use cluster computing system for large-scale data processing. It provides APIs in Scala, Java, Python, and R. Spark is versatile and can run on YARN/HDFS, standalone, or Mesos. It leverages in-memory computing to be faster than Hadoop MapReduce. Resilient Distributed Datasets (RDDs) are Spark's abstraction for distributed data. RDDs support transformations like map and filter, which are lazily evaluated, and actions like count and collect, which trigger computation. Caching RDDs in memory improves performance of subsequent jobs on the same data.
Data Streaming with Apache Kafka & MongoDB - EMEAAndrew Morgan
A new generation of technologies is needed to consume and exploit today's real time, fast moving data sources. Apache Kafka, originally developed at LinkedIn, has emerged as one of these key new technologies.
This webinar explores the use-cases and architecture for Kafka, and how it integrates with MongoDB to build sophisticated data-driven applications that exploit new sources of data.
Ozone is an object store for Hadoop. Ozone solves the small file problem of HDFS, which allows users to store trillions of files in Ozone and access them as if there are on HDFS. Ozone plugs into existing Hadoop deployments seamlessly, and programs like Hive, LLAP, and Spark work without any modifications. This talk looks at the architecture, reliability, and performance of Ozone.
In this talk, we will also explore Hadoop distributed storage layer, a block storage layer that makes this scaling possible, and how we plan to use the Hadoop distributed storage layer for scaling HDFS.
We will demonstrate how to install an Ozone cluster, how to create volumes, buckets, and keys, how to run Hive and Spark against HDFS and Ozone file systems using federation, so that users don’t have to worry about where the data is stored. In other words, a full user primer on Ozone will be part of this talk.
Speakers
Anu Engineer, Software Engineer, Hortonworks
Xiaoyu Yao, Software Engineer, Hortonworks
This document discusses remote monitoring of scientific instruments. It describes connecting instruments to a cloud platform for remote monitoring. Key aspects covered include collecting instrument data streams, storing the data in databases like Redis and Redshift, and building applications to allow remote monitoring and control. The document discusses different architecture designs, performance tests, and how Redis provided better performance than other approaches for real-time visualization of instrument data streams.
From Insights to Value - Building a Modern Logical Data Lake to Drive User Ad...DataWorks Summit
Businesses often have to interact with different data sources to get a unified view of the business or to resolve discrepancies. These EDW data repositories are often large and complex, are business critical, and cannot afford downtime. This session will share best practices and lessons learned for building a Data Fabric on Spark / Hadoop / HIVE/ NoSQL that provides a unified view, enables a simplified access to the data repositories, resolves technical challenges and adds business value. Businesses often have to interact with different data sources to get a unified view of the business or to resolve discrepancies. These EDW data repositories are often large and complex, are business critical, and cannot afford downtime. This session will share best practices and lessons learned for building a Data Fabric on Spark / Hadoop / HIVE/ NoSQL that provides a unified view, enables a simplified access to the data repositories, resolves technical challenges and adds business value.
Building a modern end-to-end open source Big Data reference applicationDataWorks Summit
In this talk, Edgar Orendain walks through a modern real-time streaming application serving as a reference framework for developing a big data pipeline, complete with a broad range of use cases and powerful reusable core components.
Modern applications can ingest data and leverage analytics in real-time. These analytics are based on machine learning models typically built using historical big data. This reference application provides examples of connecting data-in-motion analytics to your application based on Big Data.
We review code, best practices and considerations involved when integrating different components into a complete data platform. From IoT sensor data collection, to flow management, real-time stream processing and analytics, through to machine learning and prediction, this reference project aims to help developers seed their own open source solutions – fast.
This document summarizes Netflix's migration from Oracle to Cassandra. It discusses how Netflix moved its backend database from Oracle to Cassandra to gain scalability and reduce costs. The migration strategy involved dual writes to both databases, fork lifting the existing Oracle dataset, and a consistency checker. Challenges included security, denormalization, and engineering effort. Real use cases like APIs and viewing history are discussed along with lessons learned around data modeling, performance testing, and thinking of Cassandra as just storage.
Red Hat Ceph Storage is a massively scalable, software-defined storage platform that provides block, object, and file storage using a single, unified storage infrastructure. It offers several advantages over traditional proprietary storage, including lower costs, greater scalability, simplified maintenance, and an open source development model. Red Hat Ceph Storage 2 includes new capabilities like enhanced object storage integration, multi-site replication, and a new storage management console.
Druid is a high performance, column-oriented distributed data store that is widely used at Oath for big data analysis. Druid has a JSON schema as its query language, making it difficult for new users unfamiliar with the schema to start querying Druid quickly. The JSON schema is designed to work with the data ingestion methods of Druid, so it can provide high performance features such as data aggregations in JSON, but many are unable to utilize such features, because they not familiar with the specifics of how to optimize Druid queries. However, most new Druid users at Yahoo are already very familiar with SQL, and the queries they want to write for Druid can be converted to concise SQL.
We found that our data analysts wanted an easy way to issue ad-hoc Druid queries and view the results in a BI tool in a way that's presentable to nontechnical stakeholders. In order to achieve this, we had to bridge the gap between Druid, SQL, and our BI tools such as Apache Superset. In this talk, we will explore different ways to query a Druid datasource in SQL and discuss which methods were most appropriate for our use cases. We will also discuss our open source contributions so others can utilize our work. GURUGANESH KOTTA, Software Dev Eng, Oath and JUNXIAN WU, Software Engineer, Oath Inc.
Big data security challenges are bit different from traditional client-server applications and are distributed in nature, introducing unique security vulnerabilities. Cloud Security Alliance (CSA) has categorized the different security and privacy challenges into four different aspects of the big data ecosystem. These aspects are infrastructure security, data privacy, data management and, integrity and reactive security. Each of these aspects are further divided into following security challenges:
1. Infrastructure security
a. Secure distributed processing of data
b. Security best practices for non-relational data stores
2. Data privacy
a. Privacy-preserving analytics
b. Cryptographic technologies for big data
c. Granular access control
3. Data management
a. Secure data storage and transaction logs
b. Granular audits
c. Data provenance
4. Integrity and reactive security
a. Endpoint input validation/filtering
b. Real-time security/compliance monitoring
In this talk, we are going to refer above classification and identify existing security controls, best practices, and guidelines. We will also paint a big picture about how collective usage of all discussed security controls (Kerberos, TDE, LDAP, SSO, SSL/TLS, Apache Knox, Apache Ranger, Apache Atlas, Ambari Infra, etc.) can address fundamental security and privacy challenges that encompass the entire Hadoop ecosystem. We will also discuss briefly recent security incidents involving Hadoop systems.
Speakers
Krishna Pandey, Staff Software Engineer, Hortonworks
Kunal Rajguru, Premier Support Engineer, Hortonworks
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
SQL Server on Linux will provide the SQL Server database engine running natively on Linux. It allows customers choice in deploying SQL Server on the platform of their choice, including Linux, Windows, and containers. The public preview of SQL Server on Linux is available now, with the general availability target for 2017. It brings the full power of SQL Server to Linux, including features like In-Memory OLTP, Always Encrypted, and PolyBase.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
RedisConf18 - Redis Enterprise on Cloud Native Platforms Redis Labs
This document provides an introduction to cloud-native platforms and Kubernetes, and demonstrates how Redis Enterprise can run on these platforms. It discusses how Kubernetes provides orchestration of containers and manages the application lifecycle. It then demonstrates deploying Redis Enterprise on Kubernetes, showing how it uses a custom Kubernetes controller and operator to provide auto-bootstrapping of Redis clusters within Kubernetes pods. The demo shows creating a Redis database, service discovery, and benchmarking tool deployment on the Kubernetes-hosted Redis Enterprise clusters.
MANTL Data Platform, Microservices and BigData ServicesCisco DevNet
The document discusses using Mantl, an open source platform, to deploy multiple services together in a shared cluster for better utilization and data sharing. It describes how Mesos provides resource isolation and scalability to run both complex services and microservices together. Examples are given of deploying Riak, Zoomdata, Streamsets, and other services on Mantl to take advantage of shared infrastructure and data. The goal is to maximize efficiency through a unified service platform that can run in hybrid cloud environments.
Xiaomi is a Chinese technology company, it sells more than 100 million smartphones worldwide in 2018, and also owns one of the world's largest IoT device platforms. Xiaomi builds dozens of mobile apps and Internet services based on intelligent devices, including Ads, news feeds, finance service, game, music, video, personal cloud service and so on. The rapid growth of business results in exponential growth of the data analytics infrastructure. The amount of data has roared more than 20 times in the past 3 years, which renders us big challenges on the HDFS scalability
In this talk, we introduce how we scale HDFS to support hundreds of PB data with thousands nodes:
1. How Xiaomi use Hadoop and the characteristic of our usage
2. We made HDFS federation cluster to be used like a single cluster, most applications don't need to change any code to migrate from a single cluster to a federation cluster. Our works include a wrapper FileSystem compatible with DistributedFileSystem, supporting rename among different name spaces and zookeeper-based mount table renewer.
3. Experience of tuning NameNode to improve scalability
4. How to maintain hundreds of HDFS clusters and the optimization we did on client-side to make user and programs access these clusters easily with high performance
Implementing Security on a Large Multi-Tenant Cluster the Right WayDataWorks Summit
Raise your hands if you are deploying Kerberos and other Hadoop security components after deploying Hadoop to the enterprise. We will present the best practices and challenges of implementing security on a large multi-tenant Hadoop cluster spanning multiple data centers. Additionally, we will outline our authentication & authorization security architecture, how we reduced complexity through planning, and how we worked with multiple teams and organizations to implement security the right way the first time. We will share lessons learned and takeaways for implementing security at your company.
We will walk through the implementation and its impacts to the user, development, support and security communities and will highlight the pitfalls that we navigated to achieve success. Protecting your customers and information assets is critical to success. If you are planning to introduce Hadoop security to your ecosystem, don’t miss this in depth discussion on a very important and necessary component to enterprise big data.
Exploring microservices in a Microsoft landscapeAlex Thissen
Presentation for Dutch Microsoft TechDays 2015 with Marcel de Vries:
During this session we will take a look at how to realize a Microservices architecture (MSA) using the latest Microsoft technologies available. We will discuss some fundamental theories behind MSA and show you how this can actually be realized with Microsoft technologies such as Azure Service Fabric. This session is a real must-see for any developer that wants to stay ahead of the curve in modern architectures.
Startup Case Study: Leveraging the Broad Hadoop Ecosystem to Develop World-Fi...DataWorks Summit
Back in 2014, our team set out to change the way the world exchanges and collaborates with data. Our vision was to build a single tenant environment for multiple organisations to securely share and consume data. And we did just that, leveraging multiple Hadoop technologies to help our infrastructure scale quickly and securely.
Today Data Republic’s technology delivers a trusted platform for hundreds of enterprise level companies to securely exchange, commercialise and collaborate with large datasets.
Join Head of Engineering, Juan Delard de Rigoulières and Senior Solutions Architect, Amin Abbaspour as they share key lessons from their team’s journey with Hadoop:
* How a startup leveraged a clever combination of Hadoop technologies to build a secure data exchange platform
* How Hadoop technologies helped us deliver key solutions around governance, security and controls of data and metadata
* An evaluation on the maturity and usefulness of some Hadoop technologies in our environment: Hive, HDFS, Spark, Ranger, Atlas, Knox, Kylin: we've use them all extensively.
* Our bold approach to expose APIs directly to end users; as well as the challenges, learning and code we created in the process
* Learnings from the front-line: How our team coped with code changes, performance tuning, issues and solutions while building our data exchange
Whether you’re an enterprise level business or a start-up looking to scale - this case study discussion offers behind-the-scenes lessons and key tips when using Hadoop technologies to manage data governance and collaboration in the cloud.
Speakers:
Juan Delard De Rigoulieres, Head of Engineering, Data Republic Pty Ltd
Amin Abbaspour, Senior Solutions Architect, Data Republic
Running Analytics at the Speed of Your BusinessRedis Labs
The speed at which you can extract insights from your data is increasingly a competitive edge for your business. Data and analytics have to be at lightning fast speeds to seriously impact your user acquisition.
Join this webinar featuring Forrester analyst Noel Yuhanna and Leena Joshi, VP Product Marketing at Redis Labs to learn how you can glean insights faster with new open source data processing frameworks like Spark and Redis.
In this webinar you will learn:
* Why analytics has to run at the real time speed of business
* How this can be achieved with next generation Big Data tools
* How data structures can optimize your hybrid transaction-analytics processing scenarios
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.
This presentation provides a clear overview of how Oracle Database In-Memory optimizes both analytics and mixed workloads, delivering outstanding performance while supporting real-time analytics, business intelligence, and reporting. It provides details on what you can expect from Database In-Memory in both Oracle Database 12.1.0.2 and 12.2.
Data Streaming with Apache Kafka & MongoDB - EMEAAndrew Morgan
A new generation of technologies is needed to consume and exploit today's real time, fast moving data sources. Apache Kafka, originally developed at LinkedIn, has emerged as one of these key new technologies.
This webinar explores the use-cases and architecture for Kafka, and how it integrates with MongoDB to build sophisticated data-driven applications that exploit new sources of data.
Ozone is an object store for Hadoop. Ozone solves the small file problem of HDFS, which allows users to store trillions of files in Ozone and access them as if there are on HDFS. Ozone plugs into existing Hadoop deployments seamlessly, and programs like Hive, LLAP, and Spark work without any modifications. This talk looks at the architecture, reliability, and performance of Ozone.
In this talk, we will also explore Hadoop distributed storage layer, a block storage layer that makes this scaling possible, and how we plan to use the Hadoop distributed storage layer for scaling HDFS.
We will demonstrate how to install an Ozone cluster, how to create volumes, buckets, and keys, how to run Hive and Spark against HDFS and Ozone file systems using federation, so that users don’t have to worry about where the data is stored. In other words, a full user primer on Ozone will be part of this talk.
Speakers
Anu Engineer, Software Engineer, Hortonworks
Xiaoyu Yao, Software Engineer, Hortonworks
This document discusses remote monitoring of scientific instruments. It describes connecting instruments to a cloud platform for remote monitoring. Key aspects covered include collecting instrument data streams, storing the data in databases like Redis and Redshift, and building applications to allow remote monitoring and control. The document discusses different architecture designs, performance tests, and how Redis provided better performance than other approaches for real-time visualization of instrument data streams.
From Insights to Value - Building a Modern Logical Data Lake to Drive User Ad...DataWorks Summit
Businesses often have to interact with different data sources to get a unified view of the business or to resolve discrepancies. These EDW data repositories are often large and complex, are business critical, and cannot afford downtime. This session will share best practices and lessons learned for building a Data Fabric on Spark / Hadoop / HIVE/ NoSQL that provides a unified view, enables a simplified access to the data repositories, resolves technical challenges and adds business value. Businesses often have to interact with different data sources to get a unified view of the business or to resolve discrepancies. These EDW data repositories are often large and complex, are business critical, and cannot afford downtime. This session will share best practices and lessons learned for building a Data Fabric on Spark / Hadoop / HIVE/ NoSQL that provides a unified view, enables a simplified access to the data repositories, resolves technical challenges and adds business value.
Building a modern end-to-end open source Big Data reference applicationDataWorks Summit
In this talk, Edgar Orendain walks through a modern real-time streaming application serving as a reference framework for developing a big data pipeline, complete with a broad range of use cases and powerful reusable core components.
Modern applications can ingest data and leverage analytics in real-time. These analytics are based on machine learning models typically built using historical big data. This reference application provides examples of connecting data-in-motion analytics to your application based on Big Data.
We review code, best practices and considerations involved when integrating different components into a complete data platform. From IoT sensor data collection, to flow management, real-time stream processing and analytics, through to machine learning and prediction, this reference project aims to help developers seed their own open source solutions – fast.
This document summarizes Netflix's migration from Oracle to Cassandra. It discusses how Netflix moved its backend database from Oracle to Cassandra to gain scalability and reduce costs. The migration strategy involved dual writes to both databases, fork lifting the existing Oracle dataset, and a consistency checker. Challenges included security, denormalization, and engineering effort. Real use cases like APIs and viewing history are discussed along with lessons learned around data modeling, performance testing, and thinking of Cassandra as just storage.
Red Hat Ceph Storage is a massively scalable, software-defined storage platform that provides block, object, and file storage using a single, unified storage infrastructure. It offers several advantages over traditional proprietary storage, including lower costs, greater scalability, simplified maintenance, and an open source development model. Red Hat Ceph Storage 2 includes new capabilities like enhanced object storage integration, multi-site replication, and a new storage management console.
Druid is a high performance, column-oriented distributed data store that is widely used at Oath for big data analysis. Druid has a JSON schema as its query language, making it difficult for new users unfamiliar with the schema to start querying Druid quickly. The JSON schema is designed to work with the data ingestion methods of Druid, so it can provide high performance features such as data aggregations in JSON, but many are unable to utilize such features, because they not familiar with the specifics of how to optimize Druid queries. However, most new Druid users at Yahoo are already very familiar with SQL, and the queries they want to write for Druid can be converted to concise SQL.
We found that our data analysts wanted an easy way to issue ad-hoc Druid queries and view the results in a BI tool in a way that's presentable to nontechnical stakeholders. In order to achieve this, we had to bridge the gap between Druid, SQL, and our BI tools such as Apache Superset. In this talk, we will explore different ways to query a Druid datasource in SQL and discuss which methods were most appropriate for our use cases. We will also discuss our open source contributions so others can utilize our work. GURUGANESH KOTTA, Software Dev Eng, Oath and JUNXIAN WU, Software Engineer, Oath Inc.
Big data security challenges are bit different from traditional client-server applications and are distributed in nature, introducing unique security vulnerabilities. Cloud Security Alliance (CSA) has categorized the different security and privacy challenges into four different aspects of the big data ecosystem. These aspects are infrastructure security, data privacy, data management and, integrity and reactive security. Each of these aspects are further divided into following security challenges:
1. Infrastructure security
a. Secure distributed processing of data
b. Security best practices for non-relational data stores
2. Data privacy
a. Privacy-preserving analytics
b. Cryptographic technologies for big data
c. Granular access control
3. Data management
a. Secure data storage and transaction logs
b. Granular audits
c. Data provenance
4. Integrity and reactive security
a. Endpoint input validation/filtering
b. Real-time security/compliance monitoring
In this talk, we are going to refer above classification and identify existing security controls, best practices, and guidelines. We will also paint a big picture about how collective usage of all discussed security controls (Kerberos, TDE, LDAP, SSO, SSL/TLS, Apache Knox, Apache Ranger, Apache Atlas, Ambari Infra, etc.) can address fundamental security and privacy challenges that encompass the entire Hadoop ecosystem. We will also discuss briefly recent security incidents involving Hadoop systems.
Speakers
Krishna Pandey, Staff Software Engineer, Hortonworks
Kunal Rajguru, Premier Support Engineer, Hortonworks
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
SQL Server on Linux will provide the SQL Server database engine running natively on Linux. It allows customers choice in deploying SQL Server on the platform of their choice, including Linux, Windows, and containers. The public preview of SQL Server on Linux is available now, with the general availability target for 2017. It brings the full power of SQL Server to Linux, including features like In-Memory OLTP, Always Encrypted, and PolyBase.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
RedisConf18 - Redis Enterprise on Cloud Native Platforms Redis Labs
This document provides an introduction to cloud-native platforms and Kubernetes, and demonstrates how Redis Enterprise can run on these platforms. It discusses how Kubernetes provides orchestration of containers and manages the application lifecycle. It then demonstrates deploying Redis Enterprise on Kubernetes, showing how it uses a custom Kubernetes controller and operator to provide auto-bootstrapping of Redis clusters within Kubernetes pods. The demo shows creating a Redis database, service discovery, and benchmarking tool deployment on the Kubernetes-hosted Redis Enterprise clusters.
MANTL Data Platform, Microservices and BigData ServicesCisco DevNet
The document discusses using Mantl, an open source platform, to deploy multiple services together in a shared cluster for better utilization and data sharing. It describes how Mesos provides resource isolation and scalability to run both complex services and microservices together. Examples are given of deploying Riak, Zoomdata, Streamsets, and other services on Mantl to take advantage of shared infrastructure and data. The goal is to maximize efficiency through a unified service platform that can run in hybrid cloud environments.
Xiaomi is a Chinese technology company, it sells more than 100 million smartphones worldwide in 2018, and also owns one of the world's largest IoT device platforms. Xiaomi builds dozens of mobile apps and Internet services based on intelligent devices, including Ads, news feeds, finance service, game, music, video, personal cloud service and so on. The rapid growth of business results in exponential growth of the data analytics infrastructure. The amount of data has roared more than 20 times in the past 3 years, which renders us big challenges on the HDFS scalability
In this talk, we introduce how we scale HDFS to support hundreds of PB data with thousands nodes:
1. How Xiaomi use Hadoop and the characteristic of our usage
2. We made HDFS federation cluster to be used like a single cluster, most applications don't need to change any code to migrate from a single cluster to a federation cluster. Our works include a wrapper FileSystem compatible with DistributedFileSystem, supporting rename among different name spaces and zookeeper-based mount table renewer.
3. Experience of tuning NameNode to improve scalability
4. How to maintain hundreds of HDFS clusters and the optimization we did on client-side to make user and programs access these clusters easily with high performance
Implementing Security on a Large Multi-Tenant Cluster the Right WayDataWorks Summit
Raise your hands if you are deploying Kerberos and other Hadoop security components after deploying Hadoop to the enterprise. We will present the best practices and challenges of implementing security on a large multi-tenant Hadoop cluster spanning multiple data centers. Additionally, we will outline our authentication & authorization security architecture, how we reduced complexity through planning, and how we worked with multiple teams and organizations to implement security the right way the first time. We will share lessons learned and takeaways for implementing security at your company.
We will walk through the implementation and its impacts to the user, development, support and security communities and will highlight the pitfalls that we navigated to achieve success. Protecting your customers and information assets is critical to success. If you are planning to introduce Hadoop security to your ecosystem, don’t miss this in depth discussion on a very important and necessary component to enterprise big data.
Exploring microservices in a Microsoft landscapeAlex Thissen
Presentation for Dutch Microsoft TechDays 2015 with Marcel de Vries:
During this session we will take a look at how to realize a Microservices architecture (MSA) using the latest Microsoft technologies available. We will discuss some fundamental theories behind MSA and show you how this can actually be realized with Microsoft technologies such as Azure Service Fabric. This session is a real must-see for any developer that wants to stay ahead of the curve in modern architectures.
Startup Case Study: Leveraging the Broad Hadoop Ecosystem to Develop World-Fi...DataWorks Summit
Back in 2014, our team set out to change the way the world exchanges and collaborates with data. Our vision was to build a single tenant environment for multiple organisations to securely share and consume data. And we did just that, leveraging multiple Hadoop technologies to help our infrastructure scale quickly and securely.
Today Data Republic’s technology delivers a trusted platform for hundreds of enterprise level companies to securely exchange, commercialise and collaborate with large datasets.
Join Head of Engineering, Juan Delard de Rigoulières and Senior Solutions Architect, Amin Abbaspour as they share key lessons from their team’s journey with Hadoop:
* How a startup leveraged a clever combination of Hadoop technologies to build a secure data exchange platform
* How Hadoop technologies helped us deliver key solutions around governance, security and controls of data and metadata
* An evaluation on the maturity and usefulness of some Hadoop technologies in our environment: Hive, HDFS, Spark, Ranger, Atlas, Knox, Kylin: we've use them all extensively.
* Our bold approach to expose APIs directly to end users; as well as the challenges, learning and code we created in the process
* Learnings from the front-line: How our team coped with code changes, performance tuning, issues and solutions while building our data exchange
Whether you’re an enterprise level business or a start-up looking to scale - this case study discussion offers behind-the-scenes lessons and key tips when using Hadoop technologies to manage data governance and collaboration in the cloud.
Speakers:
Juan Delard De Rigoulieres, Head of Engineering, Data Republic Pty Ltd
Amin Abbaspour, Senior Solutions Architect, Data Republic
Running Analytics at the Speed of Your BusinessRedis Labs
The speed at which you can extract insights from your data is increasingly a competitive edge for your business. Data and analytics have to be at lightning fast speeds to seriously impact your user acquisition.
Join this webinar featuring Forrester analyst Noel Yuhanna and Leena Joshi, VP Product Marketing at Redis Labs to learn how you can glean insights faster with new open source data processing frameworks like Spark and Redis.
In this webinar you will learn:
* Why analytics has to run at the real time speed of business
* How this can be achieved with next generation Big Data tools
* How data structures can optimize your hybrid transaction-analytics processing scenarios
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.
This presentation provides a clear overview of how Oracle Database In-Memory optimizes both analytics and mixed workloads, delivering outstanding performance while supporting real-time analytics, business intelligence, and reporting. It provides details on what you can expect from Database In-Memory in both Oracle Database 12.1.0.2 and 12.2.
Streaming Solutions for Real time problemsAbhishek Gupta
The document is a presentation on streaming solutions for real-time problems using Apache Kafka, Kafka Streams, and Redis. It begins with an introduction and overview of the technologies. It then presents a sample monitoring application using metrics from multiple machines as a use case. The presentation demonstrates how to implement this application using Kafka as the event store, Kafka Streams for processing, and Redis as the state store. It also shows how to deploy the application components on Oracle Cloud.
Oracle NoSQL Database -- Big Data Bellevue Meetup - 02-18-15Dave Segleau
The document is a presentation on NoSQL databases given by Dave Segleau, Director of Product Management at Oracle. It discusses why organizations use NoSQL databases, provides an overview of Oracle NoSQL Database including its features and architecture. It also covers common use cases for NoSQL databases in industries like finance, manufacturing, and telecom. Finally, it discusses some of the challenges of using NoSQL databases and how Oracle NoSQL Database addresses issues of scalability, reliability and manageability.
Oracle Database Appliance Portfolio overview. #ODA @OralceODA.
This deck will show the benefits of the ODA as your Engineered System best optimised to run the Oracle Database.
To learn more contact: [email protected]
(ODA Account Manager- UK Market)
These are the *updated* slides (InnoDB clusters and MySQL Enterprise Monitor 3.4 are now GA) from the following webinar, which you can now watch on demand:
https://www.mysql.com/news-and-events/web-seminars/why-mysql-high-availability-matters/
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MySQL high availability matters because your data matters. If your database goes down, whether due to human error, catastrophic network failure, or planned maintenance, the accessibility and accuracy of your data can be compromised with disastrous results. We'll examine the critical elements of a high availability solution, including:
- Data redundancy
- Data consistency
- Automatic fault detection and resolution
- No single point of failure
And how you can achieve these things more easily than ever before using MySQL's new native HA solution.
The document is a presentation on Oracle NoSQL Database that discusses its use cases, Oracle's NoSQL and big data strategy, technical features of Oracle NoSQL Database, and customer references. The presentation covers how Oracle NoSQL Database can be used for real-time event processing, sensor data acquisition, fraud detection, recommendations, and globally distributed databases. It also discusses Oracle's approach to integrating NoSQL, Hadoop, and relational databases. Customer references are provided for Airbus's use of Oracle NoSQL Database for flight test sensor data storage and analysis.
Slides presented at Great Indian Developer Summit 2016 at the session MySQL: What's new on April 29 2016.
Contains information about the new MySQL Document Store released in April 2016.
The document provides a roadmap for Oracle Coherence, including upcoming versions, new capabilities, and use cases. Key points include:
- Coherence 19 will support JDK 8 and 11 and include new development, runtime, and cloud capabilities.
- Common use cases for Coherence include as a web application platform, fast data platform, and for offloading backend/legacy systems.
- New features in recent/upcoming versions include persistence, federated caching, security improvements, and leveraging Java 8 features like lambdas and streams.
This overview provides insight into the ODA Engineered System. It outlines how the ODA is: Simple, Optimsed and Affordable to implement for all organisations.
Contact me to find out more:
E-mail:[email protected]
Phone: +441189244490
Twitter: @daryllwhyte
LinkedIn: https://ie.linkedin.com/in/daryllwhyte
Website- Oracle ODA: https://www.oracle.com/oda
MySQL in oracle_environments(Part 2): MySQL Enterprise Monitor & Oracle Enter...OracleMySQL
This document discusses how Oracle Enterprise Manager can be used to manage MySQL databases. It provides an overview of how MySQL Enterprise Monitor and Oracle Enterprise Manager integrate to provide monitoring of MySQL performance metrics, configuration monitoring, replication monitoring, query analysis, security management, and other capabilities from a single dashboard. It also discusses how to install and set up both MySQL Enterprise Monitor and the Oracle Enterprise Manager MySQL plugin.
Recent advances in Postgres have propelled the database forward to meet today’s data challenges. At some of the world’s largest companies, Postgres plays a major role in controlling costs and reducing dependence on traditional providers.
This presentation addresses:
* What workloads are best suited for introducing Postgres into your environment
* The success milestones for evaluating the ‘when and how’ of expanding Postgres deployments
* Key advances in recent Postgres releases that support new data types and evolving data challenges
This presentation is intended for strategic IT and Business Decision-Makers involved in data infrastructure decisions and cost-savings.
Connector/J Beyond JDBC: the X DevAPI for Java and MySQL as a Document StoreFilipe Silva
The document discusses Connector/J Beyond JDBC and the X DevAPI for Java and MySQL as a Document Store. It provides an agenda that includes an introduction to MySQL as a document store, an overview of the X DevAPI, and how the X DevAPI is implemented in Connector/J. The presentation aims to demonstrate the X DevAPI for developing CRUD-based applications and using MySQL as both a relational database and document store.
This document summarizes Oracle's Database Appliance X7-2, a purpose-built system for managing Oracle Database. It comes in three configurations (X7-2S, X7-2M, X7-2-HA) with varying processor, memory, storage, and high availability capabilities. The appliance is simple and optimized to deploy Oracle Database quickly while reducing costs through its integrated infrastructure and Oracle licensing model. It also offers a path to integrating databases on-premises with Oracle Cloud.
This document discusses data management trends and Oracle's unified data management solution. It provides a high-level comparison of HDFS, NoSQL, and RDBMS databases. It then describes Oracle's Big Data SQL which allows SQL queries to be run across data stored in Hadoop. Oracle Big Data SQL aims to provide easy access to data across sources using SQL, unified security, and fast performance through smart scans.
Oracle Database 19c - poslední z rodiny 12.2 a co přináší novéhoMarketingArrowECS_CZ
The document provides an overview of Oracle Database 19c, highlighting its key features and capabilities. It notes that Oracle Database 19c is Oracle's recommended release for all database upgrades. New features in 19c include fast data ingestion support for IoT workloads, SQL statement quarantine, and enhancements to JSON and high availability functionality.
MySQL 8.0 includes several new features and enhancements to improve performance, security, and flexibility for developers. Key updates include support for JSON and Unicode, window functions and common table expressions for data analysis, and security features like SQL roles and dynamic privileges. The new release also aims to make applications more scalable, stable, and mobile-friendly.
MySQL 8.0 includes several new features and enhancements to improve performance, security, and flexibility for developers. Key updates include support for JSON and Unicode, window functions and common table expressions for data analysis, and security features like SQL roles and dynamic privileges. The new release also aims to make applications more scalable, mobile-friendly, and cloud-ready.
The document summarizes Oracle's Big Data Appliance and solutions. It discusses the Big Data Appliance hardware which includes 18 servers with 48GB memory, 12 Intel cores, and 24TB storage per node. The software includes Oracle Linux, Apache Hadoop, Oracle NoSQL Database, Oracle Data Integrator, and Oracle Loader for Hadoop. Oracle Loader for Hadoop can be used to load data from Hadoop into Oracle Database in online or offline mode. The Big Data Appliance provides an optimized platform for storing and analyzing large amounts of data and is integrated with Oracle Exadata.
This document discusses InfiniGuard's data protection solution and its advantages over other backup appliances. It highlights InfiniGuard's ability to provide fast restore times even for large datasets through its use of InfiniBox storage technology. The document also covers how InfiniGuard addresses modern threats like ransomware through immutable snapshots, logical air-gapping of backups, and a isolated forensic network to enable fast recovery from cyber attacks.
Využijte svou Oracle databázi na maximum!
Ondřej Buršík
Senior Presales, Oracle
Arrow / Oracle
The document discusses maximizing the use of Oracle databases. It covers topics such as resilience, performance and agility, security and risk management, and cost optimization. It promotes Oracle Database editions and features, as well as Oracle Engineered Systems like Exadata, which are designed to provide high performance, availability, security and manageability for databases.
Prezentace z webináře dne 10.3.2022
Prezentovali:
Jaroslav Malina - Senior Channel Sales Manager, Oracle
Josef Krejčí - Technology Sales Consultant, Oracle
Josef Šlahůnek - Cloud Systems sales Consultant, Oracle
Prezentace z webináře ze dne 9.2.2022
Prezentovali:
Jaroslav Malina - Senior Channel Sales Manager, Oracle
Josef Krejčí - Technology Sales Consultant, Oracle
Josef Šlahůnek - Cloud Systems Sales Consultant, Oracle
The document discusses Oracle Database Appliance (ODA) high availability and disaster recovery solutions. It compares Oracle Real Application Clusters (RAC), RAC One Node, and Standard Edition High Availability (SEHA). RAC provides automatic restart and failover capabilities for load balancing across nodes. RAC One Node and SEHA provide restart and failover, but no load balancing. SEHA is suitable for Standard Edition databases if up to 16 sessions are adequate and a few minutes of reconnection time is acceptable without data loss during failover.
This document discusses InfiniGuard, a data protection solution from Infinidat. It highlights challenges with current backup solutions including slow restore times. InfiniGuard addresses this by leveraging InfiniBox storage technology to achieve restore objectives. It provides fast, scalable backup and restore performance. InfiniGuard also discusses threats from server-side encryption attacks and how its immutable snapshots and isolated backup environment help provide cyber resilience against such threats.
This document discusses Infinidat's scale-out storage solutions. It highlights Infinidat's unique software-driven architecture with over 100 patents. Infinidat systems can scale to over 7 exabytes deployed globally across various industries. Analyst reviews show Infinidat receiving higher ratings than Dell EMC, HPE, NetApp, and others. The InfiniBox systems offer multi-petabyte scale in a single rack with high performance, reliability, and efficiency.
This document discusses Oracle Database 19c and the concept of a converged database. It begins with an overview of new features in Oracle Database 19c, including direct upgrade paths, new in-memory capabilities, and improvements to multitenant architecture. It then discusses the concept of a converged database that can support multiple data types and workloads within a single database compared to using separate single-purpose databases. The document argues that a converged database approach avoids issues with data consistency, security, availability and manageability between separate databases. It notes Oracle Database's support for transactions, analytics, machine learning, IoT and other workloads within a single database. The document concludes with an overview of Oracle Database Performance Health Checks.
The document discusses Infinidat's scale-out storage solutions. It highlights Infinidat's unique software-driven architecture with over 100 patents. Infinidat solutions can scale to multi-petabyte capacity in a single rack and provide high performance, reliability, and cost-effectiveness compared to other storage vendors. The document also covers Infinidat's flexible business models, replication capabilities, and easy management tools.
The document discusses Oracle's Database Options Initiative and how it can help organizations address challenges in a post-pandemic world. It outlines bundles focused on security & risk resilience, operational resiliency, cost optimization, and performance & agility. Each bundle contains various Oracle database products and capabilities designed to provide benefits like reduced costs, increased availability, faster performance, and enhanced security. The document also provides information on specific products and how they address needs such as disaster recovery, data protection, database management, and query optimization.
Oracle's Data Protection Solutions Will Help You Protect Your Business Interests
The document discusses Oracle's data protection solutions, specifically the Oracle Recovery Appliance. The Recovery Appliance provides continuous data protection for Oracle databases with recovery points of less than one second. It offers faster restore performance compared to generic data protection appliances. The Recovery Appliance fully integrates with Oracle databases and offers features like real-time data validation and monitoring of data loss exposure.
The document discusses strategies for protecting data, including:
1. Implementing a well-defined data protection architecture using Oracle Database security controls and services like Data Safe to assess risks, discover sensitive data, and audit activities.
2. Using high availability technologies like Oracle Real Application Clusters and disaster recovery options like Data Guard and GoldenGate to ensure redundancy and meet recovery objectives.
3. Addressing challenges with traditional backup and restore approaches and the need for a new solution given critical failures and costs of $2.5M per year to correct.
OCI Storage Services provides different types of storage for various use cases:
- Local NVMe SSD storage provides high-performance temporary storage that is not persistent.
- Block Volume storage provides durable block-level storage for applications requiring SAN-like features through iSCSI. Volumes can be resized, backed up, and cloned.
- File Storage Service provides shared file systems accessible over NFSv3 that are durable and suitable for applications like EBS and HPC workloads.
This document discusses Oracle Cloud Infrastructure compute options including bare metal instances, virtual machine instances, and dedicated hosts. It provides details on instance types, images, volumes, instance configurations and pools, autoscaling, metadata, and lifecycle. Key points covered include the differences between bare metal, VM, and dedicated host instances, bringing your own images, customizing boot volumes, using instance configurations and pools for management and autoscaling, and accessing instance metadata.
Exadata z pohledu zákazníka a novinky generace X8M - 1. částMarketingArrowECS_CZ
Oracle's Exadata X8M is a new database platform that provides the best performance for running Oracle Database. It uses a scale-out architecture with optimized compute, storage, and networking resources. New features include shared persistent memory that provides latency of 19 microseconds and speeds up log writes by 8x. Exadata X8M also delivers 3x more throughput, 2x more IOPS, and 5x lower latency than competing all-flash arrays. It offers the highest database performance scaling linearly with additional racks.
Oracle Cloud Infrastructure (OCI) provides Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) through a global network of 29 regions. OCI offers high-performance computing resources, storage, networking, security, and edge services to support traditional and cloud-native workloads. Pricing for OCI is consistently lower than other major cloud providers for equivalent services, with flexible payment models and usage-based pricing.
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell
With expertise in data architecture, performance tracking, and revenue forecasting, Andrew Marnell plays a vital role in aligning business strategies with data insights. Andrew Marnell’s ability to lead cross-functional teams ensures businesses achieve sustainable growth and operational excellence.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
Noah Loul Shares 5 Steps to Implement AI Agents for Maximum Business Efficien...Noah Loul
Artificial intelligence is changing how businesses operate. Companies are using AI agents to automate tasks, reduce time spent on repetitive work, and focus more on high-value activities. Noah Loul, an AI strategist and entrepreneur, has helped dozens of companies streamline their operations using smart automation. He believes AI agents aren't just tools—they're workers that take on repeatable tasks so your human team can focus on what matters. If you want to reduce time waste and increase output, AI agents are the next move.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungenpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/
HCL Nomad Web wird als die nächste Generation des HCL Notes-Clients gefeiert und bietet zahlreiche Vorteile, wie die Beseitigung des Bedarfs an Paketierung, Verteilung und Installation. Nomad Web-Client-Updates werden “automatisch” im Hintergrund installiert, was den administrativen Aufwand im Vergleich zu traditionellen HCL Notes-Clients erheblich reduziert. Allerdings stellt die Fehlerbehebung in Nomad Web im Vergleich zum Notes-Client einzigartige Herausforderungen dar.
Begleiten Sie Christoph und Marc, während sie demonstrieren, wie der Fehlerbehebungsprozess in HCL Nomad Web vereinfacht werden kann, um eine reibungslose und effiziente Benutzererfahrung zu gewährleisten.
In diesem Webinar werden wir effektive Strategien zur Diagnose und Lösung häufiger Probleme in HCL Nomad Web untersuchen, einschließlich
- Zugriff auf die Konsole
- Auffinden und Interpretieren von Protokolldateien
- Zugriff auf den Datenordner im Cache des Browsers (unter Verwendung von OPFS)
- Verständnis der Unterschiede zwischen Einzel- und Mehrbenutzerszenarien
- Nutzung der Client Clocking-Funktion
Role of Data Annotation Services in AI-Powered ManufacturingAndrew Leo
From predictive maintenance to robotic automation, AI is driving the future of manufacturing. But without high-quality annotated data, even the smartest models fall short.
Discover how data annotation services are powering accuracy, safety, and efficiency in AI-driven manufacturing systems.
Precision in data labeling = Precision on the production floor.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
TrsLabs - Fintech Product & Business ConsultingTrs Labs
Hybrid Growth Mandate Model with TrsLabs
Strategic Investments, Inorganic Growth, Business Model Pivoting are critical activities that business don't do/change everyday. In cases like this, it may benefit your business to choose a temporary external consultant.
An unbiased plan driven by clearcut deliverables, market dynamics and without the influence of your internal office equations empower business leaders to make right choices.
Getting things done within a budget within a timeframe is key to Growing Business - No matter whether you are a start-up or a big company
Talk to us & Unlock the competitive advantage