Self-service Big Data Analytics on Microsoft AzureCloudera, Inc.
In this presentation Microsoft will join Cloudera to introduce a new Platform-as-a-Service (PaaS) offering that helps data engineers use on-demand cloud infrastructure to speed the creation and operation of data pipelines that power sophisticated, data-driven applications - without onerous administration.
How to Run Cloudera Enterprise on Microsoft AzureCloudera, Inc.
Once the primary architecture for running Hadoop pilots and dev/test applications, the cloud is fast becoming a preferred destination for enterprise big data workloads. Today enterprises are using Hadoop to deliver better products and services, improve their visibility and reduce risk, and they’re doing it at greater scale and efficiency in the cloud.
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Unlock Hadoop Success with Cloudera Navigator OptimizerCloudera, Inc.
Cloudera Navigator Optimizer analyzes existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop.
Learn how Cloudera is using our own platform to build the applications our support teams use every day to solve complex problems in Hadoop.
Recorded Webinar: http://www.cloudera.com/content/www/en-us/resources/recordedwebinar/data-driven-customer-support.html
How Big Data Can Enable Analytics from the Cloud (Technical Workshop)Cloudera, Inc.
In this workshop, we will look outside the box and help expand the problem space to include issues you may not have thought were possible before Big Data. From Near Real Time (NRT) recommendation engines, loan applications to churn detection, Big Data is answering new questions and providing organisations with a competitive edge through revenue increase, cost savings and risk mitigation. We will take a special look at the role the Cloud can play in elevating your analytics environment. We will discuss real world examples of how Big Data answers these questions and does it at a lower cost outlay.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
Big data journey to the cloud 5.30.18 asher bartchCloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Self-service Big Data Analytics on Microsoft AzureCloudera, Inc.
In this presentation Microsoft will join Cloudera to introduce a new Platform-as-a-Service (PaaS) offering that helps data engineers use on-demand cloud infrastructure to speed the creation and operation of data pipelines that power sophisticated, data-driven applications - without onerous administration.
How to Run Cloudera Enterprise on Microsoft AzureCloudera, Inc.
Once the primary architecture for running Hadoop pilots and dev/test applications, the cloud is fast becoming a preferred destination for enterprise big data workloads. Today enterprises are using Hadoop to deliver better products and services, improve their visibility and reduce risk, and they’re doing it at greater scale and efficiency in the cloud.
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Unlock Hadoop Success with Cloudera Navigator OptimizerCloudera, Inc.
Cloudera Navigator Optimizer analyzes existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop.
Learn how Cloudera is using our own platform to build the applications our support teams use every day to solve complex problems in Hadoop.
Recorded Webinar: http://www.cloudera.com/content/www/en-us/resources/recordedwebinar/data-driven-customer-support.html
How Big Data Can Enable Analytics from the Cloud (Technical Workshop)Cloudera, Inc.
In this workshop, we will look outside the box and help expand the problem space to include issues you may not have thought were possible before Big Data. From Near Real Time (NRT) recommendation engines, loan applications to churn detection, Big Data is answering new questions and providing organisations with a competitive edge through revenue increase, cost savings and risk mitigation. We will take a special look at the role the Cloud can play in elevating your analytics environment. We will discuss real world examples of how Big Data answers these questions and does it at a lower cost outlay.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
Big data journey to the cloud 5.30.18 asher bartchCloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Making Self-Service BI a Reality in the EnterpriseCloudera, Inc.
For most analysts, the pace of analytics and data science can be frustrating. The common waterfall approach works well for the fixed reports, but it can be a lengthy process to request additional data sets, create new reports, or serve new use cases. So it’s no surprise that organizations are looking to shift towards a self-service model, empowering business users to discover and iterate quickly.
However, it’s not just about opening up this access, but also ensuring the results are accurate and trusted. When there are petabytes of data, how does a user know which tables to use and which are most relevant? How do you strike the balance between discovery and agility, while still meeting enterprise governance standards to truly get more value from your data?
During this webinar, you’ll learn how to empower end-users to make self-service BI a reality within your organization while fostering governance collaboration between all data stakeholders. We’ll discuss and demo:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Collaboration and access outside of just SQL for data science and beyond
In addition, we will walk through best practices and considerations when developing your organizational strategy around self-service analytics, and highlight several real-world success stories from a wide range of industries.
3 things to learn:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Comment développer une stratégie Big Data dans le cloud public avec l'offre P...Cloudera, Inc.
Le cloud public est une proposition attractive pour les entreprises à la recherche d’agilité dans leurs projets big data, qu’il s’agisse de traiter des données en masse ou d’y exécuter des analyses complexes pour une meilleure prise de décision.
3 Things to Learn:
-How data is driving digital transformation to help businesses innovate rapidly
-How Choice Hotels (one of largest hoteliers) is using Cloudera Enterprise to gain meaningful insights that drive their business
-How Choice Hotels has transformed business through innovative use of Apache Hadoop, Cloudera Enterprise, and deployment in the cloud — from developing customer experiences to meeting IT compliance requirements
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Preparing data for analysis and insights is the foundation of any data-driven exercise. Moving workloads to a PaaS, be it data engineering, analytic database, or data science requires a two step leap of faith - in trusting the public cloud, and then your PaaS vendor. In this webinar we will discuss the architecture of a PaaS solution for data management and understand the nitty gritty details of what exactly this involves with the following:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
3 things to learn:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
How to Build Continuous Ingestion for the Internet of ThingsCloudera, Inc.
The Internet of Things is moving into the mainstream and this new world of data-driven products is transforming a vast number of industry sectors and technologies.
However, IoT creates a new challenge: how to build and operationalize continual data ingestion from such a wide and ever-changing array of endpoints so that the data arrives consumption-ready and can drive analysis and action within the business.
In this webinar, Sean Anderson from Cloudera and Kirit Busu, Director of Product Management at StreamSets, will discuss Hadoop's ecosystem and IoT capabilities and provide advice about common patterns and best practices. Using specific examples, they will demonstrate how to build and run end-to-end IOT data flows using StreamSets and Cloudera infrastructure.
Seeking Cybersecurity--Strategies to Protect the DataCloudera, Inc.
Agency professionals are responsible for protecting the data they collect, store, analyze, and share. While Hadoop has been especially popular for data analytics given its ability to handle volume, velocity, and variety of data, this flexibility and scale can present challenges for securing and governing the data. Plan to attend this session to understand the Hadoop Security Maturity Model—from the fundamentals to the latest developments--and how to ensure your data analytics cluster complies with the latest INFOSEC standards and audit requirements. Bring your experience and your questions to this informative and interactive cybersecurity session.
What’s New in Cloudera Enterprise 6.0: The Inside Scoop 6.14.18Cloudera, Inc.
Webinar on Cloudera Enterprise 6.0 where we will discuss how to build new applications on the modern platform for machine learning and analytics. This webinar will take a look at the latest software enhancements and how they’ll help you improve your productivity and innovate new analytics applications.
Building a Data Hub that Empowers Customer Insight (Technical Workshop)Cloudera, Inc.
We have seen the evolution with the Bi and Data Science fields from the structured data warehouse to data lake and finally, to the data hub. This session will cover the key steps required to building a data hub, examining how best to align and engage stakeholders and develop architectural sanction to enable your organisations to realise new customer insights and better enable you to achieve business objectives.
Cloudera GoDataFest Security and GovernanceGoDataDriven
The document discusses Cloudera's security and governance solutions for Hadoop. It describes how Cloudera provides comprehensive security through authentication, authorization, auditing, and compliance features. It also covers how Cloudera helps with data visibility and governance through tools that report on data usage and lineage. The overall goal is to help customers securely manage and govern their data on Hadoop clusters.
Big data journey to the cloud rohit pujari 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Kelley Blue Book Uses Big Data to Increase User Engagement Over 100%Cloudera, Inc.
Kelley Blue Book Customer Use Case In this webinar, you will learn how KBB has: - Experienced a 37% increase in ad spend efficiency - Drove an incremental 1 billion impressions from its target segments - Observed a 24% lift in website engagement
Hadoop Distributed File System (HDFS) Encryption with Cloudera Navigator Key ...Cloudera, Inc.
This document provides an overview of Cloudera's Navigator Key Trustee, which is a key management server that acts as a proxy between CDH components and an external key store. It discusses how Key Trustee uses encryption zone keys stored in an external hardware security module to encrypt data encryption keys, which are then used to encrypt data at rest in HDFS. The document also covers Key Trustee's architecture, deployment considerations, access control lists, and troubleshooting steps.
Data Science and Machine Learning for the EnterpriseCloudera, Inc.
Overview of Machine Learning and how the Cloudera Data Science Workbench provides full access to data while supporting IT SLAs. The presentation includes details on Fast Forward Labs and The Value of Interpretability in Models.
Managing Successful Data Projects: Technology Selection and Team BuildingCloudera, Inc.
Recent years have seen dramatic advancements in the technologies available for managing and processing data. While these technologies provide powerful tools to build data applications, they also require new skills. Ted Malaska and Jonathan Seidman explain how to evaluate these new technologies and build teams to effectively leverage these technologies and achieve ROI with your data initiatives.
Cloudera Data Science Workbench: sparklyr, implyr, and More - dplyr Interfac...Cloudera, Inc.
You like to use R, and you need to use big data. dplyr, one of the most popular packages for R, makes it easy to query large data sets in scalable processing engines like Apache Spark and Apache Impala.
But there can be pitfalls: dplyr works differently with different data sources—and those differences can bite you if you don’t know what you’re doing.
Ian Cook is a data scientist, an R contributor, and a curriculum developer at Cloudera University. In this webinar, Ian will show you exactly what you need to know about sparklyr (from RStudio) and the package implyr (from Cloudera). He will show you how to write dplyr code that works across these different interfaces. And, he will solve mysteries:
Do I need to know SQL to use dplyr?
When is a “tbl” not a “tibble”?
Why is 1 not always equal to 1?
When should you collect(), collapse(), and compute()?
How can you use dplyr to combine data stored in different systems?
3 things to learn:
Do I need to know SQL to use dplyr?
When should you collect(), collapse(), and compute()?
How can you use dplyr to combine data stored in different systems?
Multi-Tenant Operations with Cloudera 5.7 & BTCloudera, Inc.
One benefit of Apache Hadoop is the ability to power multiple workloads, across many different users and departments, all within a single, shared cluster. Hear how BT is doing this today and learn about new features in Cloudera Manager to provide better visibility for multi-tenant operations.
The 6th Wave of Automation: Automation of Decisions | Cloudera Analytics & Ma...Cloudera, Inc.
This presentation provides detail on how we are now in the 6th wave of automation, that is based on Machine Learning. In this 6th wave, Cloudera plays a critical role in providing the data platform for Machine Learning and Analytics built for the Cloud.
The Vision & Challenge of Applied Machine LearningCloudera, Inc.
Learn how Cloudera provides a unified platform that breaks down data silos commonly seen in organizations. By unifying the data needed for applied machine learning, organizations are better equipped to gather valuable insights from their data.
The document discusses running Hadoop clusters in the cloud and the challenges that presents. It introduces CloudFarmer, a tool that allows defining roles for VMs and dynamically allocating VMs to roles. This allows building agile Hadoop clusters in the cloud that can adapt as needs change without static configurations. CloudFarmer provides a web UI to manage roles and hosts.
Making Self-Service BI a Reality in the EnterpriseCloudera, Inc.
For most analysts, the pace of analytics and data science can be frustrating. The common waterfall approach works well for the fixed reports, but it can be a lengthy process to request additional data sets, create new reports, or serve new use cases. So it’s no surprise that organizations are looking to shift towards a self-service model, empowering business users to discover and iterate quickly.
However, it’s not just about opening up this access, but also ensuring the results are accurate and trusted. When there are petabytes of data, how does a user know which tables to use and which are most relevant? How do you strike the balance between discovery and agility, while still meeting enterprise governance standards to truly get more value from your data?
During this webinar, you’ll learn how to empower end-users to make self-service BI a reality within your organization while fostering governance collaboration between all data stakeholders. We’ll discuss and demo:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Collaboration and access outside of just SQL for data science and beyond
In addition, we will walk through best practices and considerations when developing your organizational strategy around self-service analytics, and highlight several real-world success stories from a wide range of industries.
3 things to learn:
Strategies of consolidating data across silos for fast, flexible access
Enabling easy discovery and exploration, including understanding which data to trust and where to start
New capabilities for intelligent query assistance as well as immediate performance optimizations and recommendations as-you-go
Comment développer une stratégie Big Data dans le cloud public avec l'offre P...Cloudera, Inc.
Le cloud public est une proposition attractive pour les entreprises à la recherche d’agilité dans leurs projets big data, qu’il s’agisse de traiter des données en masse ou d’y exécuter des analyses complexes pour une meilleure prise de décision.
3 Things to Learn:
-How data is driving digital transformation to help businesses innovate rapidly
-How Choice Hotels (one of largest hoteliers) is using Cloudera Enterprise to gain meaningful insights that drive their business
-How Choice Hotels has transformed business through innovative use of Apache Hadoop, Cloudera Enterprise, and deployment in the cloud — from developing customer experiences to meeting IT compliance requirements
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Preparing data for analysis and insights is the foundation of any data-driven exercise. Moving workloads to a PaaS, be it data engineering, analytic database, or data science requires a two step leap of faith - in trusting the public cloud, and then your PaaS vendor. In this webinar we will discuss the architecture of a PaaS solution for data management and understand the nitty gritty details of what exactly this involves with the following:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
3 things to learn:
An exploration of the architecture of Cloudera Altus PaaS - the industry’s first multi-function, multi-cloud data and analytic platform-as-a-service
A dive into use cases and a demo of Altus
The synergy between AWS and Altus to help you securely standardize on a combination of public cloud and data management
How to Build Continuous Ingestion for the Internet of ThingsCloudera, Inc.
The Internet of Things is moving into the mainstream and this new world of data-driven products is transforming a vast number of industry sectors and technologies.
However, IoT creates a new challenge: how to build and operationalize continual data ingestion from such a wide and ever-changing array of endpoints so that the data arrives consumption-ready and can drive analysis and action within the business.
In this webinar, Sean Anderson from Cloudera and Kirit Busu, Director of Product Management at StreamSets, will discuss Hadoop's ecosystem and IoT capabilities and provide advice about common patterns and best practices. Using specific examples, they will demonstrate how to build and run end-to-end IOT data flows using StreamSets and Cloudera infrastructure.
Seeking Cybersecurity--Strategies to Protect the DataCloudera, Inc.
Agency professionals are responsible for protecting the data they collect, store, analyze, and share. While Hadoop has been especially popular for data analytics given its ability to handle volume, velocity, and variety of data, this flexibility and scale can present challenges for securing and governing the data. Plan to attend this session to understand the Hadoop Security Maturity Model—from the fundamentals to the latest developments--and how to ensure your data analytics cluster complies with the latest INFOSEC standards and audit requirements. Bring your experience and your questions to this informative and interactive cybersecurity session.
What’s New in Cloudera Enterprise 6.0: The Inside Scoop 6.14.18Cloudera, Inc.
Webinar on Cloudera Enterprise 6.0 where we will discuss how to build new applications on the modern platform for machine learning and analytics. This webinar will take a look at the latest software enhancements and how they’ll help you improve your productivity and innovate new analytics applications.
Building a Data Hub that Empowers Customer Insight (Technical Workshop)Cloudera, Inc.
We have seen the evolution with the Bi and Data Science fields from the structured data warehouse to data lake and finally, to the data hub. This session will cover the key steps required to building a data hub, examining how best to align and engage stakeholders and develop architectural sanction to enable your organisations to realise new customer insights and better enable you to achieve business objectives.
Cloudera GoDataFest Security and GovernanceGoDataDriven
The document discusses Cloudera's security and governance solutions for Hadoop. It describes how Cloudera provides comprehensive security through authentication, authorization, auditing, and compliance features. It also covers how Cloudera helps with data visibility and governance through tools that report on data usage and lineage. The overall goal is to help customers securely manage and govern their data on Hadoop clusters.
Big data journey to the cloud rohit pujari 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Kelley Blue Book Uses Big Data to Increase User Engagement Over 100%Cloudera, Inc.
Kelley Blue Book Customer Use Case In this webinar, you will learn how KBB has: - Experienced a 37% increase in ad spend efficiency - Drove an incremental 1 billion impressions from its target segments - Observed a 24% lift in website engagement
Hadoop Distributed File System (HDFS) Encryption with Cloudera Navigator Key ...Cloudera, Inc.
This document provides an overview of Cloudera's Navigator Key Trustee, which is a key management server that acts as a proxy between CDH components and an external key store. It discusses how Key Trustee uses encryption zone keys stored in an external hardware security module to encrypt data encryption keys, which are then used to encrypt data at rest in HDFS. The document also covers Key Trustee's architecture, deployment considerations, access control lists, and troubleshooting steps.
Data Science and Machine Learning for the EnterpriseCloudera, Inc.
Overview of Machine Learning and how the Cloudera Data Science Workbench provides full access to data while supporting IT SLAs. The presentation includes details on Fast Forward Labs and The Value of Interpretability in Models.
Managing Successful Data Projects: Technology Selection and Team BuildingCloudera, Inc.
Recent years have seen dramatic advancements in the technologies available for managing and processing data. While these technologies provide powerful tools to build data applications, they also require new skills. Ted Malaska and Jonathan Seidman explain how to evaluate these new technologies and build teams to effectively leverage these technologies and achieve ROI with your data initiatives.
Cloudera Data Science Workbench: sparklyr, implyr, and More - dplyr Interfac...Cloudera, Inc.
You like to use R, and you need to use big data. dplyr, one of the most popular packages for R, makes it easy to query large data sets in scalable processing engines like Apache Spark and Apache Impala.
But there can be pitfalls: dplyr works differently with different data sources—and those differences can bite you if you don’t know what you’re doing.
Ian Cook is a data scientist, an R contributor, and a curriculum developer at Cloudera University. In this webinar, Ian will show you exactly what you need to know about sparklyr (from RStudio) and the package implyr (from Cloudera). He will show you how to write dplyr code that works across these different interfaces. And, he will solve mysteries:
Do I need to know SQL to use dplyr?
When is a “tbl” not a “tibble”?
Why is 1 not always equal to 1?
When should you collect(), collapse(), and compute()?
How can you use dplyr to combine data stored in different systems?
3 things to learn:
Do I need to know SQL to use dplyr?
When should you collect(), collapse(), and compute()?
How can you use dplyr to combine data stored in different systems?
Multi-Tenant Operations with Cloudera 5.7 & BTCloudera, Inc.
One benefit of Apache Hadoop is the ability to power multiple workloads, across many different users and departments, all within a single, shared cluster. Hear how BT is doing this today and learn about new features in Cloudera Manager to provide better visibility for multi-tenant operations.
The 6th Wave of Automation: Automation of Decisions | Cloudera Analytics & Ma...Cloudera, Inc.
This presentation provides detail on how we are now in the 6th wave of automation, that is based on Machine Learning. In this 6th wave, Cloudera plays a critical role in providing the data platform for Machine Learning and Analytics built for the Cloud.
The Vision & Challenge of Applied Machine LearningCloudera, Inc.
Learn how Cloudera provides a unified platform that breaks down data silos commonly seen in organizations. By unifying the data needed for applied machine learning, organizations are better equipped to gather valuable insights from their data.
The document discusses running Hadoop clusters in the cloud and the challenges that presents. It introduces CloudFarmer, a tool that allows defining roles for VMs and dynamically allocating VMs to roles. This allows building agile Hadoop clusters in the cloud that can adapt as needs change without static configurations. CloudFarmer provides a web UI to manage roles and hosts.
Packaging et déploiement d'une application avec Docker et Ansible @DevoxxFR 2015Stephane Manciot
This document discusses packaging and deploying a Java EE application using Docker and Ansible. It covers using Docker for portability, fast image building, and performance benefits compared to VMs. It discusses using Dockerfiles to package applications, exposing ports, mounting volumes, and setting default commands. It addresses challenges like service discovery and load balancing using an ambassador pattern. Ansible is covered for orchestration, provisioning, deployment, its advantages like being agentless and using YAML playbooks with roles and templates. The document provides examples of Dockerfiles, building images, running containers, and Ansible inventory, playbooks and roles to deploy applications on infrastructure.
PSUG #52 Dataflow and simplified reactive programming with Akka-streamsStephane Manciot
This document discusses using Akka streams for dataflow and reactive programming. It begins with an overview of dataflow concepts like nodes, arcs, graphs, and features such as push/pull data, mutable/immutable data, and compound nodes. It then covers Reactive Streams including back pressure, the asynchronous non-blocking protocol, and the publisher-subscriber interface. Finally, it details how to use Akka streams, including defining sources, sinks, and flows to create processing pipelines as well as working with more complex flow graphs. Examples are provided for bulk exporting data to Elasticsearch and finding frequent item sets from transaction data.
Spark and Mesos cluster optimization was discussed. The key points were:
1. Spark concepts like stages, tasks, and partitions were explained to understand application behavior and optimization opportunities around shuffling.
2. Application optimization focused on reducing shuffling through techniques like partitioning, reducing object sizes, and optimizing closures.
3. Memory tuning in Spark involved configuring storage and shuffling fractions to control memory usage between user data and Spark's internal data.
4. When running Spark on Mesos, coarse-grained and fine-grained allocation modes were described along with solutions like using Mesos roles to control resource allocation and dynamic allocation in coarse-grained mode.
Cette conférence a pour objet de partager avec les participants le processus d'intégration d'un système de Machine Learning (ML) dans une application Java / Scala. Elle s'adresse aux développeurs qui souhaitent inclure des services de recommandation en ligne, d'analyse de risque ou d'intelligence client mais qui n'ont pas de connaissances particulières en ML. Nous aborderons :
Le processus global : Choix des échantillons d'apprentissage et de test, sélection de l'algorithme de machine learning, évaluation et optimisation du modèle
La préparation de l'échantillon de données : Les critères de choix des données à collecter, le volume à injecter, les transformations à réaliser en amont de l'application de l'algorithme de ML
La sélection et la construction du modèle : Cette section parcoure les catégories d'algorithmes disponibles dans MLLib et présente les principales règles de sélection et d'ajustement en fonction de l'objectif.
L'évaluation et l'optimisation du modèle : Cette section présente les métriques d'évaluation de la performance prédictive des modèles ML ainsi que les diagrammes D3.js de visualisation adaptés.
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformCloudera, Inc.
The document discusses building multi-disciplinary analytics applications on a shared data platform. It describes challenges with traditional fragmented approaches using multiple data silos and tools. A shared data platform with Cloudera SDX provides a common data experience across workloads through shared metadata, security, and governance services. This approach optimizes key design goals and provides business benefits like increased insights, agility, and decreased costs compared to siloed environments. An example application of predictive maintenance is given to improve fleet performance.
Webinar - Sehr empfehlenswert: wie man aus Daten durch maschinelles Lernen We...Cloudera, Inc.
Unternehmen sind heutzutage in der Lage ihre Daten mit relativer Leichtigkeit aufzunehmen und zu verwalten. Die Herausforderung besteht nun darin, die verborgenen Muster in den Daten zu erkennen und diese zu verstehen, um einen Mehrwert zu generieren. Aufgrund der großen Datenmengen gelingt dies mit traditionelle Ansätzen zumeist nicht. Das Ergebnis: Organisationen kämpfen, um wirklich zu innovieren und sich zu differenzieren.
Cloudera - The Modern Platform for AnalyticsCloudera, Inc.
This presentation provides an overview of Cloudera and how a modern platform for Machine Learning and Analytics better enables a data-driven enterprise.
Multidisziplinäre Analyseanwendungen auf einer gemeinsamen Datenplattform ers...Cloudera, Inc.
Maschinelles Lernen und Analyseanwendungen explodieren im Unternehmen und ermöglichen Anwendungsfällen in Bereichen wie vorbeugende Wartung, Bereitstellung neuer, wünschenswerter Produktangebote für Kunden zum richtigen Zeitpunkt und Bekämpfung von Insider-Bedrohungen für Ihr Unternehmen.
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Cloudera Analytics and Machine Learning Platform - Optimized for Cloud Stefan Lipp
Take Data Management to the next level: Connect Analytics and Machine Learning in a single governed platform consisting of a curated protable open source stack. Run this platform on-prem, hybrid or multicloud, reuse code and models avoid lock-in.
In this webinar, we’ll show you how Cloudera SDX reduces the complexity in your data management environment and lets you deliver diverse analytics with consistent security, governance, and lifecycle management against a shared data catalog.
Cloudera Enterprise is a data platform that provides:
1) Data science and engineering capabilities for developing and serving predictive models.
2) An operational database for real-time insights.
3) A modern data warehouse.
It can be deployed across multiple cloud platforms and on-premises, and supports various analytic tools. Cloudera Enterprise also provides security, governance, and automation features.
Cloudera Altus: Big Data in der Cloud einfach gemachtCloudera, Inc.
Neueste Studien zeigen, dass Data Scientisten und Analysten bis zu 80% ihrer Zeit dafür nutzen, Daten zu reinigen und vorzubereiten.
Eine ohnehin schon zeitaufwändige Aufgabe kann in der Cloud noch weiter erschwert werden, da das Cluster Management und Operations die Komplexität noch erhöhen.
Nutzer wünschen sich daher, diese komplexen Workflows zu vereinheitlichen und zu vereinfachen.
Um Big Data und Machine Learning Initiativen voranzutreiben, benötigen Unternehmen eine skalierbare und überall verfügbare Plattform. Diese muss Self-Service ermöglichen und Datensilos eliminieren.
Cloudera GoDataFest Deploying Cloudera in the CloudGoDataDriven
This document discusses deploying Cloudera in the cloud using Cloudera Director and Cloudera Altus. Cloudera Director is a tool for managing the lifecycle of long-running Cloudera clusters in cloud environments, while Cloudera Altus is a platform-as-a-service for transient data engineering workloads like ETL and machine learning. The document provides an example of using Cloudera Altus for data processing and Cloudera Director for interactive querying, and demonstrates Altus and Director in a scenario of a data analyst using them to analyze website sales data.
This deck covers key considerations and provides advice for enterprises looking to run production-scale Cloudera on AWS. We touch on everything from security to governance to selecting the right instance type for your Hadoop workload (Spark, Impala, Search, etc).
It’s becoming clear that enterprises need more than one cloud. Hybrid enables enterprises to optimize how their business works – public cloud for elasticity and scale, multi-cloud for redundancy and choice, and on-premises for performance and privacy. Cloudera delivers a hybrid cloud solution that works where enterprises work, with the agility, security and governance enterprise IT needs, and the self-service analytics business people and enterprise data professionals demand. In this session, we will talk about how Cloudera helps deliver hybrid solutions for enterprises and will run a hands-on Cloudera PaaS demo to exhibit:
- Altus Environment Setup
- Configure Altus SDX
- Spin-up transient clusters with Altus
- Execute workload on Altus Data Engineering clusters
- Run interactive queries on object store with Altus Data Warehouse
- Job Analytics with Workload Experience Manager (WXM)
Speaker: Junaid Rao, Senior Cloud Sales Engineer, Cloudera
A deep dive into running data analytic workloads in the cloudCloudera, Inc.
This document discusses running data analytic workloads in the cloud using Cloudera Altus. It introduces Altus, which provides a platform-as-a-service for analyzing and processing data at scale in public clouds. The document outlines Altus features like low cost per-hour pricing, end-user focus, and cloud-native deployment. It then describes hands-on examples using Altus Data Engineering for ETL and the Altus Analytic Database for exploration and analytics. Workload analytics capabilities are also introduced for troubleshooting and optimizing jobs.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Cloud-Native Machine Learning: Emerging Trends and the Road AheadDataWorks Summit
Big data platforms are being asked to support an ever increasing range of workloads and compute environments, including large-scale machine learning and public and private clouds. In this talk, we will discuss some emerging capabilities around cloud-native machine learning and data engineering, including running machine learning and Spark workloads directly on Kubernetes, and share our vision of the road ahead for ML and AI in the cloud.
Big Data LDN 2018: CONSISTENT SECURITY, GOVERNANCE AND FLEXIBILITY FOR ALL WO...Matt Stubbs
The document discusses Cloudera's Shared Data Experience (SDX) which provides consistent security, governance and flexibility for workloads both on-premises and in the cloud. SDX offers a common set of services including security, governance, lifecycle management and data cataloging that can be shared across different workloads regardless of deployment location. This addresses challenges of managing multiple isolated clusters and allows for easier data sharing and reuse across applications. SDX provides a single source of truth for data through its shared services.
Securing Your CI Pipeline with HashiCorp Vault - P2Ashnikbiz
Today, CI/CD is becoming a practice for optimum software delivery in almost every organization. What is key is how you manage the secrets in your pipeline, especially in a large organization with multiple projects, across several teams.
Hashicorp Vault helps organizations to centrally manage secrets even in your CI/CD pipelines.
WEBINAR COVERS:
Why is it critical to secure your pipeline which needs to access a lot of important secrets in order to provision and deploy
How Vault provides a unified interface to any secret while providing tight access control and recording a detailed audit log
Customer use cases and scenarios
Demo: How to secure your CI pipeline with Vault
Watch on demand: https://bit.ly/35QCq0u
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Big Data LDN 2018: MICROSOFT AZURE AND CLOUDERA – FLEXIBLE CLOUD, WHATEVER TH...Matt Stubbs
Microsoft and Cloudera have partnered to help customers realize insights from big data using cloud services. With Cloudera Enterprise deployed on Azure, customers can visualize data with Power BI and gain insights within minutes. Cloudera provides solutions for data warehousing, data science, and hybrid deployments that fulfill enterprise requirements around flexibility, manageability, and security on Azure.
High-Performance Analytics in the Cloud with Apache ImpalaCloudera, Inc.
With more and more data being generated and stored in the cloud, you need a modern data platform that can extend to any environment so you can derive value from all your data. Cloudera Enterprise is the leading enterprise Hadoop platform for cloud deployments. It’s the easiest way to manage and secure Hadoop data across any cloud environment and includes component-level support for cloud-native object stores. This makes the platform uniquely suited to handle transient jobs like ETL and BI analytics, as well as persistent workloads like stream processing and advanced analytics.
With the recent release of Cloudera 5.8, Apache Impala (incubating) has added support for Amazon S3, enabling business analysts to get instant insights from all data through high-performance exploratory analytics and BI.
3 Things to learn:
Join David Tishgart, Director of Product Marketing, and James Curtis, Senior Analyst Data Platforms & Analytics at 451 Research, as they discuss:
* Best practices for analytic workloads in the cloud
* A live demo and real-world use cases
* What’s next for Cloudera and the cloud
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Similar to Enterprise Hadoop in the Cloud. In Minutes. | How to Run Cloudera Enterprise on Microsoft Azure (20)
The document discusses using Cloudera DataFlow to address challenges with collecting, processing, and analyzing log data across many systems and devices. It provides an example use case of logging modernization to reduce costs and enable security solutions by filtering noise from logs. The presentation shows how DataFlow can extract relevant events from large volumes of raw log data and normalize the data to make security threats and anomalies easier to detect across many machines.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
The document outlines the 2021 finalists for the annual Data Impact Awards program, which recognizes organizations using Cloudera's platform and the impactful applications they have developed. It provides details on the challenges, solutions, and outcomes for each finalist project in the categories of Data Lifecycle Connection, Cloud Innovation, Data for Enterprise AI, Security & Governance Leadership, Industry Transformation, People First, and Data for Good. There are multiple finalists highlighted in each category demonstrating innovative uses of data and analytics.
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
The document outlines the agenda for Cloudera's Enterprise Data Cloud event in Vienna. It includes welcome remarks, keynotes on Cloudera's vision and customer success stories. There will be presentations on the new Cloudera Data Platform and customer case studies, followed by closing remarks. The schedule includes sessions on Cloudera's approach to data warehousing, machine learning, streaming and multi-cloud capabilities.
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
The document discusses the benefits and trends of modernizing a data warehouse. It outlines how a modern data warehouse can provide deeper business insights at extreme speed and scale while controlling resources and costs. Examples are provided of companies that have improved fraud detection, customer retention, and machine performance by implementing a modern data warehouse that can handle large volumes and varieties of data from many sources.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
Workload Experience Manager (XM) gives you the visibility necessary to efficiently migrate, analyze, optimize, and scale workloads running in a modern data warehouse. In this recorded webinar we discuss common challenges running at scale with modern data warehouse, benefits of end-to-end visibility into workload lifecycles, overview of Workload XM and live demo, real-life customer before/after scenarios, and what's next for Workload XM.
Get started with Cloudera's cyber solutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.
We'll outline approaches for preprocessing, training, inference, and deployment across datasets (time series, audio, video, text, etc.) that leverage Spark, along with its extended ecosystem of libraries and deep learning frameworks using Cloudera's Data Science Workbench.
Cloud Data Warehousing with Cloudera Altus 7.24.18Cloudera, Inc.
This webinar will help you maximize the full potential of the cloud. Understand how to leverage cloud environments for different analytic workloads to empower business analysts and keep IT happy. An intricate, beautiful balance. The learn best practices in design, performance tuning, workload considerations, and hybrid or multi-cloud strategies.
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
Enhanced Screen Flows UI/UX using SLDS with Tom KittPeter Caitens
Join us for an engaging session led by Flow Champion, Tom Kitt. This session will dive into a technique of enhancing the user interfaces and user experiences within Screen Flows using the Salesforce Lightning Design System (SLDS). This technique uses Native functionality, with No Apex Code, No Custom Components and No Managed Packages required.
How Can Hiring A Mobile App Development Company Help Your Business Grow?ToXSL Technologies
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Alluxio Webinar | 10x Faster Trino Queries on Your Data PlatformAlluxio, Inc.
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
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Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
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Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
Transforming Product Development using OnePlan To Boost Efficiency and Innova...OnePlan Solutions
Ready to overcome challenges and drive innovation in your organization? Join us in our upcoming webinar where we discuss how to combat resource limitations, scope creep, and the difficulties of aligning your projects with strategic goals. Discover how OnePlan can revolutionize your product development processes, helping your team to innovate faster, manage resources more effectively, and deliver exceptional results.
Liberarsi dai framework con i Web Component.pptxMassimo Artizzu
In Italian
Presentazione sulle feature e l'utilizzo dei Web Component nell sviluppo di pagine e applicazioni web. Racconto delle ragioni storiche dell'avvento dei Web Component. Evidenziazione dei vantaggi e delle sfide poste, indicazione delle best practices, con particolare accento sulla possibilità di usare web component per facilitare la migrazione delle proprie applicazioni verso nuovi stack tecnologici.
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Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
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