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.
Apache Mesos, Apache Hadoop, Apache Spark + Custom Enterprise Applications: This stack combined is greater than the sum of each of the pieces of this stack. Mesos can manage resources across an entire data center, Hadoop provides a distributed data store and scalable data processing, and Spark delivers great in-memory and disk-based performance of data processing as well as streaming capabilities. Couple all of that with custom enterprise applications, and the data center turns into a well-oiled machine. When combined, this software stack delivers unlimited flexibility for the entire data center.
Jim Scott, Director of Architecture and Enterprise Strategy | Strata + Hadoop World | Barcelona, Spain, November 2014
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?
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
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.
Consolidate your data marts for fast, flexible analytics 5.24.18Cloudera, Inc.
In this webinar, Cloudera and AtScale will showcase:
How a company can modernize their analytic architecture to deliver flexibility and agility to more end-users.
How using AtScale’s Universal Semantic layer can end the data chaos and allow business users to use the data in the modern platform.
Highlight the performance of AtScale and Cloudera’s analytic database with newly completed TPC-DS standard benchmarking.
Best practices for migrating from legacy appliances.
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.
Data Engineering: Elastic, Low-Cost Data Processing in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud: What’s the same and what’s different?
*Benefits of data processing in the cloud
*Best practices and architectural considerations
Apache Mesos, Apache Hadoop, Apache Spark + Custom Enterprise Applications: This stack combined is greater than the sum of each of the pieces of this stack. Mesos can manage resources across an entire data center, Hadoop provides a distributed data store and scalable data processing, and Spark delivers great in-memory and disk-based performance of data processing as well as streaming capabilities. Couple all of that with custom enterprise applications, and the data center turns into a well-oiled machine. When combined, this software stack delivers unlimited flexibility for the entire data center.
Jim Scott, Director of Architecture and Enterprise Strategy | Strata + Hadoop World | Barcelona, Spain, November 2014
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?
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
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.
Consolidate your data marts for fast, flexible analytics 5.24.18Cloudera, Inc.
In this webinar, Cloudera and AtScale will showcase:
How a company can modernize their analytic architecture to deliver flexibility and agility to more end-users.
How using AtScale’s Universal Semantic layer can end the data chaos and allow business users to use the data in the modern platform.
Highlight the performance of AtScale and Cloudera’s analytic database with newly completed TPC-DS standard benchmarking.
Best practices for migrating from legacy appliances.
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.
Data Engineering: Elastic, Low-Cost Data Processing in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud: What’s the same and what’s different?
*Benefits of data processing in the cloud
*Best practices and architectural considerations
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.
Machine Learning in the Enterprise 2019 Timothy Spann
Machine Learning in the Enterprise 2019. These are the slides for my upcoming demo on integrating Machine Learning and Streaming with Apache NiFi and Cloudera Data Science Workbench. This is for the February 12th, 2019 Future of Data Princeton meetup.
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformCloudera, Inc.
Machine learning and analytics applications are exploding in the enterprise; driving use cases for preventative maintenance, delivering new desirable product offers to customers at the right time, and combating insider threats to your business.
But each of these high-value use cases rely on a variety of data analysis capabilities working in concert to combine data from different sources into a single coherent picture. Cloudera SDX delivers a “shared data experience” that makes applications easier to develop, less expensive to deploy and more consistently secure.
3 things to learn:
* Why multi-function applications are difficult to build and secure
* How shared catalog, governance, management, and security applied consistently everywhere can deliver a “shared data experience”
* How enterprise customers are building new, high-value applications with SDX
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.
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.
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
Part 1: Cloudera’s Analytic Database: BI & SQL Analytics in a Hybrid Cloud WorldCloudera, Inc.
3 Things to Learn About:
* On-premises versus the cloud: What’s the same and what’s different?
* Design and benefits of analytics in the cloud
* Best practices and architectural considerations
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...Cloudera, Inc.
For self-service BI and exploratory analytic workloads, the cloud can provide a number of key benefits, but the move to the cloud isn’t all-or-nothing. Gartner predicts nearly 80 percent of businesses will adopt a hybrid strategy. Learn how a modern analytic database can power your business-critical workloads across multi-cloud and hybrid environments, while maintaining data portability. We'll also discuss how to best leverage the increased agility cloud provides, while maintaining peak performance.
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.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
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.
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...DataStax
Today’s customers want experiences that are contextual, always on, and above all — delightful. To be able to provide this, enterprises need a distributed, hybrid cloud-ready database that can easily crunch massive volumes of data from disparate sources while offering data autonomy and operational simplicity. Don’t miss this webinar, where you’ll learn how DataStax Enterprise 6 maintains hybrid cloud flexibility with all the benefits of a distributed cloud database, delivers all the advantages of Apache Cassandra with none of the complexities, doubles performance, and provides additional capabilities around robust transactional analytics, graph, search, and more.
View recording: https://youtu.be/tuiWAt2jwBw
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
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.
New Performance Benchmarks: Apache Impala (incubating) Leads Traditional Anal...Cloudera, Inc.
Recording Link: http://bit.ly/LSImpala
Author: Greg Rahn, Cloudera Director of Product Management
In this session, we'll review the recent set of benchmark tests the Apache Impala (incubating) performance team completed that compare Apache Impala to a traditional analytic database (Greenplum), as well as to other SQL-on-Hadoop engines (Hive LLAP, Spark SQL, and Presto). We'll go over the methodology and results, and we'll also discuss some of the performance features and best practices that make this performance possible in Impala. Lastly, we'll look at some recent advancements in in Impala over the past few releases.
Driving Better Products with Customer Intelligence Cloudera, Inc.
In today’s fast moving world, the ability to capture and process massive amounts of data and make valuable insights is key to gaining a competitive advantage. For RingCentral, a leader in Unified Communications, this is very true since they work with over 350,000 organizations worldwide. With such scale, it can be difficult to address quality issues when they appear while supporting additional calls.
Big data journey to the cloud maz chaudhri 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.
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.
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.
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.
Machine Learning in the Enterprise 2019 Timothy Spann
Machine Learning in the Enterprise 2019. These are the slides for my upcoming demo on integrating Machine Learning and Streaming with Apache NiFi and Cloudera Data Science Workbench. This is for the February 12th, 2019 Future of Data Princeton meetup.
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformCloudera, Inc.
Machine learning and analytics applications are exploding in the enterprise; driving use cases for preventative maintenance, delivering new desirable product offers to customers at the right time, and combating insider threats to your business.
But each of these high-value use cases rely on a variety of data analysis capabilities working in concert to combine data from different sources into a single coherent picture. Cloudera SDX delivers a “shared data experience” that makes applications easier to develop, less expensive to deploy and more consistently secure.
3 things to learn:
* Why multi-function applications are difficult to build and secure
* How shared catalog, governance, management, and security applied consistently everywhere can deliver a “shared data experience”
* How enterprise customers are building new, high-value applications with SDX
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.
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.
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
Part 1: Cloudera’s Analytic Database: BI & SQL Analytics in a Hybrid Cloud WorldCloudera, Inc.
3 Things to Learn About:
* On-premises versus the cloud: What’s the same and what’s different?
* Design and benefits of analytics in the cloud
* Best practices and architectural considerations
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...Cloudera, Inc.
For self-service BI and exploratory analytic workloads, the cloud can provide a number of key benefits, but the move to the cloud isn’t all-or-nothing. Gartner predicts nearly 80 percent of businesses will adopt a hybrid strategy. Learn how a modern analytic database can power your business-critical workloads across multi-cloud and hybrid environments, while maintaining data portability. We'll also discuss how to best leverage the increased agility cloud provides, while maintaining peak performance.
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.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
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.
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...DataStax
Today’s customers want experiences that are contextual, always on, and above all — delightful. To be able to provide this, enterprises need a distributed, hybrid cloud-ready database that can easily crunch massive volumes of data from disparate sources while offering data autonomy and operational simplicity. Don’t miss this webinar, where you’ll learn how DataStax Enterprise 6 maintains hybrid cloud flexibility with all the benefits of a distributed cloud database, delivers all the advantages of Apache Cassandra with none of the complexities, doubles performance, and provides additional capabilities around robust transactional analytics, graph, search, and more.
View recording: https://youtu.be/tuiWAt2jwBw
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Topics including: The transformative value of real-time data and analytics, and current barriers to adoption. The importance of an end-to-end solution for data-in-motion that includes ingestion, processing, and serving. Apache Kudu’s role in simplifying real-time architectures.
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.
New Performance Benchmarks: Apache Impala (incubating) Leads Traditional Anal...Cloudera, Inc.
Recording Link: http://bit.ly/LSImpala
Author: Greg Rahn, Cloudera Director of Product Management
In this session, we'll review the recent set of benchmark tests the Apache Impala (incubating) performance team completed that compare Apache Impala to a traditional analytic database (Greenplum), as well as to other SQL-on-Hadoop engines (Hive LLAP, Spark SQL, and Presto). We'll go over the methodology and results, and we'll also discuss some of the performance features and best practices that make this performance possible in Impala. Lastly, we'll look at some recent advancements in in Impala over the past few releases.
Driving Better Products with Customer Intelligence Cloudera, Inc.
In today’s fast moving world, the ability to capture and process massive amounts of data and make valuable insights is key to gaining a competitive advantage. For RingCentral, a leader in Unified Communications, this is very true since they work with over 350,000 organizations worldwide. With such scale, it can be difficult to address quality issues when they appear while supporting additional calls.
Big data journey to the cloud maz chaudhri 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.
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.
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.
3 Things to Learn About:
* How Sparklyr supports a complete backend for dplyr, a popular tool for working with data frame objects both in memory and out of memory
* How Sparklyr llows data scientists to use dplyr to translate R code into Spark SQL
* How Sparklyr supports MLlib so data scientists can run classifiers, regressions, and many other machine learning algorithms in Spark
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.
A deep dive into running data analytic workloads in the cloudCloudera, Inc.
Aishwarya Venkataraman, Jason Wang, Mala Ramakrishnan, Stefan Salandy, and Vinithra Varadharajan lead a deep dive into running data analytic workloads in a managed service capacity in the public cloud and highlight cloud infrastructure best practices.
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.
Cloudera GoDataFest Deploying Cloudera in the CloudGoDataDriven
Cloud can offer flexibility and agility to your clusters. Learn more about how to deploy Cloudera in the cloud, the best practices for long-running clusters and transient clusters. And see how easy it is to spin up both kind of clusters in the cloud with Altus and Director.
Hadoop Essentials -- The What, Why and How to Meet Agency ObjectivesCloudera, Inc.
This session will provide an executive overview of the Apache Hadoop ecosystem, its basic concepts, and its real-world applications. Attendees will learn how organizations worldwide are using the latest tools and strategies to harness their enterprise information to solve business problems and the types of data analysis commonly powered by Hadoop. Learn how various projects make up the Apache Hadoop ecosystem and the role each plays to improve data storage, management, interaction, and analysis. This is a valuable opportunity to gain insights into Hadoop functionality and how it can be applied to address compelling business challenges in your agency.
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.
Cloudera Director: Unlock the Full Potential of Hadoop in the CloudCloudera, Inc.
Cloud environments are increasingly becoming a popular deployment option for Hadoop. Enterprises can take advantage of the added flexibility and elasticity of the cloud for both long-running clusters, temporary deployments or for spikey workloads. However, as more and more users choose cloud environments for critical Hadoop workloads, they are often forced to compromise on key aspects of their data platform.
Cloudera Director enables the full fidelity of the Enterprise Data Hub in the cloud, without compromises. Announced with the recent 5.2 release, Cloudera Director is the simple, reliable way to deploy and scale Hadoop in the cloud, while maintaining an open and neutral platform with enterprise-grade capabilities.
During this webinar, Tushar Shanbhag, Director of Product Management, will look at why Hadoop cloud environments are becoming so popular and some of the challenges around Hadoop in the cloud. He will then provide an in-depth overview of Cloudera Director, its key features, and how it alleviates these common challenges. Finally, he will discuss some key use cases and provide insight into what’s next for Cloudera and Hadoop in the cloud.
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).
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.
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.
Part 3: Models in Production: A Look From Beginning to EndCloudera, Inc.
3 Things to Learn About:
-How to uplevel your existing analytics stack with a collaborative environment that supports the latest open source languages and libraries.
-How to get better use of your core data management investments while opening up new supported tools for data science.
-How to expand data science outside of silo’d environments and enable self-service data science access.
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?
Join Cloudera, StreamSets, and Arcadia Data as we show you first hand how we have made it easier to get your first use case up and running. During this session you will learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
3 things to learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
Doug Cutting discusses:
- A brief history of Spark and its rise in popularity across developers and enterprises
- Spark's advantages over MapReduce
- The One Platform Initiative and the roadmap for Spark
- The future of data processing in Hadoop
3 Things to Learn:
How to deploy community defined open data models to break vendor lock-in and gain complete enterprise visibility
How to open up application flexibility while building on a future proofed architecture
How to infinitely scale data storage, access, and machine learning
Similar to Cloudera Analytics and Machine Learning Platform - Optimized for Cloud (20)
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas