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
Moving Beyond Lambda Architectures with Apache KuduCloudera, Inc.
-Kudu is a new storage layer for the Hadoop ecosystem that enables fast analytics on fast data; it splits the difference between the fast read/write of HBase and the fast scans of HDFS...while compromising minimally on performance. It can pair with Spark, Impala, or MapReduce.
-In the past, a lambda architecture was needed to run analytics on real-time data – that is, a complex architecture that created separate a “speed layer” for rapid availability/query/updates, and a “batch layer” for running analytics scans. This was complicated and took lots of tuning.
-With Kudu, the Apache ecosystem now has a simplified storage solution for analytic scans on rapidly updating data, eliminating the need for the aforementioned hybrid lambda architectures.
As data continues to pile up and departments find new ways to look at it, your datacenter needs a dense, powerful solution that can analyze this data quickly and scale resources as needed.
The Scalable Modular Server DX2000 from NEC processed big data quickly as we added server nodes and a second enclosure. In our k-means data cluster analysis test, a two-enclosure DX2000 solution running 85 Apache Spark executors and Red Hat Enterprise Linux OpenStack Platform processed 100 GB in just 46 seconds.
If you’re looking to expand your business through data analysis, the Scalable Modular Server DX2000 from NEC powered by Intel and running Apache Spark can help you unlock key big data insights.
Customer Best Practices: Optimizing Cloudera on AWSCloudera, Inc.
Join Cloudera’s Alex Moundalexis, who will discuss time-saving design and best practices for deploying Cloudera Enterprise clusters in AWS. He will also be joined by Josh Hammer, Partner Solutions Architect at Amazon Web Services who will highlight unique advantages of running Cloudera on AWS.
In this interactive webinar, we will hear from Celgene, a global biopharmaceutical company and we will explore best practices of running your Cloudera Enterprise cluster on AWS:
AWS components (EC2, S3, RDS, EBS, VPC, Direct Connect, Service Limits)
Deployment Topology
Roles & Instance Types
Networking, Connectivity and Security
Storage Configuration
Capacity Planning
Provisioning Instances
3 things to learn:
AWS components (EC2, S3, RDS, EBS, VPC, Direct Connect, Service Limits)
Networking, Connectivity and Security
Deployment Topology
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
Moving Beyond Lambda Architectures with Apache KuduCloudera, Inc.
-Kudu is a new storage layer for the Hadoop ecosystem that enables fast analytics on fast data; it splits the difference between the fast read/write of HBase and the fast scans of HDFS...while compromising minimally on performance. It can pair with Spark, Impala, or MapReduce.
-In the past, a lambda architecture was needed to run analytics on real-time data – that is, a complex architecture that created separate a “speed layer” for rapid availability/query/updates, and a “batch layer” for running analytics scans. This was complicated and took lots of tuning.
-With Kudu, the Apache ecosystem now has a simplified storage solution for analytic scans on rapidly updating data, eliminating the need for the aforementioned hybrid lambda architectures.
As data continues to pile up and departments find new ways to look at it, your datacenter needs a dense, powerful solution that can analyze this data quickly and scale resources as needed.
The Scalable Modular Server DX2000 from NEC processed big data quickly as we added server nodes and a second enclosure. In our k-means data cluster analysis test, a two-enclosure DX2000 solution running 85 Apache Spark executors and Red Hat Enterprise Linux OpenStack Platform processed 100 GB in just 46 seconds.
If you’re looking to expand your business through data analysis, the Scalable Modular Server DX2000 from NEC powered by Intel and running Apache Spark can help you unlock key big data insights.
Customer Best Practices: Optimizing Cloudera on AWSCloudera, Inc.
Join Cloudera’s Alex Moundalexis, who will discuss time-saving design and best practices for deploying Cloudera Enterprise clusters in AWS. He will also be joined by Josh Hammer, Partner Solutions Architect at Amazon Web Services who will highlight unique advantages of running Cloudera on AWS.
In this interactive webinar, we will hear from Celgene, a global biopharmaceutical company and we will explore best practices of running your Cloudera Enterprise cluster on AWS:
AWS components (EC2, S3, RDS, EBS, VPC, Direct Connect, Service Limits)
Deployment Topology
Roles & Instance Types
Networking, Connectivity and Security
Storage Configuration
Capacity Planning
Provisioning Instances
3 things to learn:
AWS components (EC2, S3, RDS, EBS, VPC, Direct Connect, Service Limits)
Networking, Connectivity and Security
Deployment Topology
Join Cloudian, Hortonworks and 451 Research for a panel-style Q&A discussion about the latest trends and technology innovations in Big Data and Analytics. Matt Aslett, Data Platforms and Analytics Research Director at 451 Research, John Kreisa, Vice President of Strategic Marketing at Hortonworks, and Paul Turner, Chief Marketing Officer at Cloudian, will answer your toughest questions about data storage, data analytics, log data, sensor data and the Internet of Things. Bring your questions or just come and listen!
Brian Brownlow is an experienced senior analyst programmer for Mayo Clinic. He is made a workshop presentation at the 2014 BDPA Technology Conference on the topic, 'Big Data Implementation - Mayo Clinic Case Study'. This presentation will show part of the Mayo Clinic story on the embarking of an exploration of the application of `Big Data' technologies. `Big Data' is seen as one set of tools that can be used to enhance medical research, medical education and practice management. Mayo Clinic is always searching for better, faster and cheaper ways to use its data to improve patient care and sustain financial outcomes in a challenging reimbursement environment. Our approach uses several components that are open source and combines them with data from various sources to provide information to decision makers in near real time. We have created a center of `Big Data' excellence using in-house staff and vendor engagements. `Big Data' is one element of our Enterprise Data Trust framework.
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
The Value of the Modern Data Architecture with Apache Hadoop and Teradata Hortonworks
This webinar discusses why Apache Hadoop most typically the technology underpinning "Big Data". How it fits in a modern data architecture and the current landscape of databases and data warehouses that are already in use.
10 Amazing Things To Do With a Hadoop-Based Data LakeVMware Tanzu
Greg Chase, Director, Product Marketing presents Big Data 10 A
mazing Things to do With A Hadoop-based Data Lake at the Strata Conference + Hadoop World 2014 in NYC.
Oncrawl elasticsearch meetup france #12Tanguy MOAL
Presentation detailing how Elasticsearch is involved in Oncrawl, a SaaS solution for easy SEO monitoring.
The presentation explains how the application is built, and how it integrates Elasticsearch, a powerful general purpose search engine.
Oncrawl is data centric and elasticsearch is used as an analytics engine rather than a full text search engine.
The application uses Apache Hadoop and Apache Nutch for the crawl pipeline and data analysis.
Oncrawl is a Cogniteev solution.
Neustar is a fast growing provider of enterprise services in telecommunications, online advertising, Internet infrastructure, and advanced technology. Neustar has engaged Think Big Analytics to leverage Hadoop to expand their data analysis capacity. This session describes how Hadoop has expanded their data warehouse capacity, agility for data analysis, reduced costs, and enabled new data products. We look at the challenges and opportunities in capturing 100′s of TB’s of compact binary network data, ad hoc analysis, integration with a scale out relational database, more agile data development, and building new products integrating multiple big data sets.
Transform Your Business with Big Data and Hortonworks Pactera_US
Customer insight and marketplace predictions are a few of the profitable benefits found in big data technology. Leading companies are using the advanced analytics solution to find new revenue streams, increase customer satisfaction and optimize the supply chain.
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
Realizing the Promise of Big Data with Hadoop - Cloudera Summer Webinar Serie...Cloudera, Inc.
Apache Hadoop, an open-source platform, is increasingly gaining adoption within organizations trying to draw insight from all the big data being generated. Hadoop, and a handful of open-source tools that complement it, are promising to make gigantic and diverse datasets easily and economically available for quick analysis. A burgeoning partner ecosystem is also essential to helping organizations turn big data into business value.
Hadoop 2.0: YARN to Further Optimize Data ProcessingHortonworks
Data is exponentially increasing in both types and volumes, creating opportunities for businesses. Watch this video and learn from three Big Data experts: John Kreisa, VP Strategic Marketing at Hortonworks, Imad Birouty, Director of Technical Product Marketing at Teradata and John Haddad, Senior Director of Product Marketing at Informatica.
Multiple systems are needed to exploit the variety and volume of data sources, including a flexible data repository. Learn more about:
- Apache Hadoop 2 and YARN
- Data Lakes
- Intelligent data management layers needed to manage metadata and usage patterns as well as track consumption across these data platforms.
IT @ Intel: Preparing the Future Enterprise with the Internet of ThingsIntel IT Center
The Internet of Things (IoT) is the concept of diverse machines, devices, and technologies connecting, interacting, and negotiating with each other to help improve and enrich our lives. No longer is this limited to just computer or smart phone technology. Everyday items such as household appliance, cars and even toys can connect to the internet to integrate with other computing things, processes and services. This new paradigm is changing how data is used and collected, and introducing new challenges for enterprises.
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...NoSQLmatters
Come to this deep dive on how Pivotal's Data Lake Vision is evolving by embracing next generation in-memory data exchange and compute technologies around Spark and Tachyon. Did we say Hadoop, SQL, and what's the shortest path to get from past to future state? The next generation of data lake technology will leverage the availability of in-memory processing, with an architecture that supports multiple data analytics workloads within a single environment: SQL, R, Spark, batch and transactional.
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.
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
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.
Big Data, Hadoop, Hortonworks and Microsoft HDInsightHortonworks
Big Data is everywhere. And at the center of the big data discussion is Apache Hadoop, a next-generation enterprise data platform that allows you to capture, process and share the enormous amounts of new, multi-structured data that doesn’t fit into transitional systems.
With Microsoft HDInsight, powered by Hortonworks Data Platform, you can bridge this new world of unstructured content with the structured data we manage today. Together, we bring Hadoop to the masses as an addition to your current enterprise data architectures so that you can amass net new insight without net new headache.
BlueData Hunk Integration: Splunk Analytics for HadoopBlueData, Inc.
BlueData is working in partnership with Splunk to streamline and accelerate the deployment and adoption of Hunk: Splunk Analytics for Hadoop. The BlueData EPIC software platform now integrates Hunk with Hadoop clusters running on virtualized on-premises infrastructure.
Using Hunk with the BlueData EPIC platform, our joint customers can quickly provision virtual Hadoop clusters together with Hunk in a matter of minutes – providing their data scientists and analysts with the ability to rapidly detect patterns and find anomalies across petabytes of raw data in Hadoop.
Learn more at http://www.bluedata.com
Join Cloudian, Hortonworks and 451 Research for a panel-style Q&A discussion about the latest trends and technology innovations in Big Data and Analytics. Matt Aslett, Data Platforms and Analytics Research Director at 451 Research, John Kreisa, Vice President of Strategic Marketing at Hortonworks, and Paul Turner, Chief Marketing Officer at Cloudian, will answer your toughest questions about data storage, data analytics, log data, sensor data and the Internet of Things. Bring your questions or just come and listen!
Brian Brownlow is an experienced senior analyst programmer for Mayo Clinic. He is made a workshop presentation at the 2014 BDPA Technology Conference on the topic, 'Big Data Implementation - Mayo Clinic Case Study'. This presentation will show part of the Mayo Clinic story on the embarking of an exploration of the application of `Big Data' technologies. `Big Data' is seen as one set of tools that can be used to enhance medical research, medical education and practice management. Mayo Clinic is always searching for better, faster and cheaper ways to use its data to improve patient care and sustain financial outcomes in a challenging reimbursement environment. Our approach uses several components that are open source and combines them with data from various sources to provide information to decision makers in near real time. We have created a center of `Big Data' excellence using in-house staff and vendor engagements. `Big Data' is one element of our Enterprise Data Trust framework.
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
The Value of the Modern Data Architecture with Apache Hadoop and Teradata Hortonworks
This webinar discusses why Apache Hadoop most typically the technology underpinning "Big Data". How it fits in a modern data architecture and the current landscape of databases and data warehouses that are already in use.
10 Amazing Things To Do With a Hadoop-Based Data LakeVMware Tanzu
Greg Chase, Director, Product Marketing presents Big Data 10 A
mazing Things to do With A Hadoop-based Data Lake at the Strata Conference + Hadoop World 2014 in NYC.
Oncrawl elasticsearch meetup france #12Tanguy MOAL
Presentation detailing how Elasticsearch is involved in Oncrawl, a SaaS solution for easy SEO monitoring.
The presentation explains how the application is built, and how it integrates Elasticsearch, a powerful general purpose search engine.
Oncrawl is data centric and elasticsearch is used as an analytics engine rather than a full text search engine.
The application uses Apache Hadoop and Apache Nutch for the crawl pipeline and data analysis.
Oncrawl is a Cogniteev solution.
Neustar is a fast growing provider of enterprise services in telecommunications, online advertising, Internet infrastructure, and advanced technology. Neustar has engaged Think Big Analytics to leverage Hadoop to expand their data analysis capacity. This session describes how Hadoop has expanded their data warehouse capacity, agility for data analysis, reduced costs, and enabled new data products. We look at the challenges and opportunities in capturing 100′s of TB’s of compact binary network data, ad hoc analysis, integration with a scale out relational database, more agile data development, and building new products integrating multiple big data sets.
Transform Your Business with Big Data and Hortonworks Pactera_US
Customer insight and marketplace predictions are a few of the profitable benefits found in big data technology. Leading companies are using the advanced analytics solution to find new revenue streams, increase customer satisfaction and optimize the supply chain.
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
Realizing the Promise of Big Data with Hadoop - Cloudera Summer Webinar Serie...Cloudera, Inc.
Apache Hadoop, an open-source platform, is increasingly gaining adoption within organizations trying to draw insight from all the big data being generated. Hadoop, and a handful of open-source tools that complement it, are promising to make gigantic and diverse datasets easily and economically available for quick analysis. A burgeoning partner ecosystem is also essential to helping organizations turn big data into business value.
Hadoop 2.0: YARN to Further Optimize Data ProcessingHortonworks
Data is exponentially increasing in both types and volumes, creating opportunities for businesses. Watch this video and learn from three Big Data experts: John Kreisa, VP Strategic Marketing at Hortonworks, Imad Birouty, Director of Technical Product Marketing at Teradata and John Haddad, Senior Director of Product Marketing at Informatica.
Multiple systems are needed to exploit the variety and volume of data sources, including a flexible data repository. Learn more about:
- Apache Hadoop 2 and YARN
- Data Lakes
- Intelligent data management layers needed to manage metadata and usage patterns as well as track consumption across these data platforms.
IT @ Intel: Preparing the Future Enterprise with the Internet of ThingsIntel IT Center
The Internet of Things (IoT) is the concept of diverse machines, devices, and technologies connecting, interacting, and negotiating with each other to help improve and enrich our lives. No longer is this limited to just computer or smart phone technology. Everyday items such as household appliance, cars and even toys can connect to the internet to integrate with other computing things, processes and services. This new paradigm is changing how data is used and collected, and introducing new challenges for enterprises.
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...NoSQLmatters
Come to this deep dive on how Pivotal's Data Lake Vision is evolving by embracing next generation in-memory data exchange and compute technologies around Spark and Tachyon. Did we say Hadoop, SQL, and what's the shortest path to get from past to future state? The next generation of data lake technology will leverage the availability of in-memory processing, with an architecture that supports multiple data analytics workloads within a single environment: SQL, R, Spark, batch and transactional.
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.
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
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.
Big Data, Hadoop, Hortonworks and Microsoft HDInsightHortonworks
Big Data is everywhere. And at the center of the big data discussion is Apache Hadoop, a next-generation enterprise data platform that allows you to capture, process and share the enormous amounts of new, multi-structured data that doesn’t fit into transitional systems.
With Microsoft HDInsight, powered by Hortonworks Data Platform, you can bridge this new world of unstructured content with the structured data we manage today. Together, we bring Hadoop to the masses as an addition to your current enterprise data architectures so that you can amass net new insight without net new headache.
BlueData Hunk Integration: Splunk Analytics for HadoopBlueData, Inc.
BlueData is working in partnership with Splunk to streamline and accelerate the deployment and adoption of Hunk: Splunk Analytics for Hadoop. The BlueData EPIC software platform now integrates Hunk with Hadoop clusters running on virtualized on-premises infrastructure.
Using Hunk with the BlueData EPIC platform, our joint customers can quickly provision virtual Hadoop clusters together with Hunk in a matter of minutes – providing their data scientists and analysts with the ability to rapidly detect patterns and find anomalies across petabytes of raw data in Hadoop.
Learn more at http://www.bluedata.com
Explore, Analyze and Visualize Data in Hadoop and NoSQL. Make massive quantities of machine data accessible, usable and valuable for the people who need it, at the speed they need it. Use Hunk to turn underutilized data into valuable insights in minutes, not weeks or months.
Cloudera and Appfluent provide large enterprises with a proven solution that maximizes data savings and minimizes legacy data warehouse costs. Appfluent’s data usage analytics deliver in-depth visibility into data warehouse and business intelligence systems.
With this comprehensive information, organizations can create a plan for a successful move to Cloudera’s enterprise data hub, powered by Apache Hadoop.
Big Data, Big Thinking: Simplified Architecture Webinar Fact SheetSAP Technology
How can you handle the complexities of Big Data while simplifying your IT architecture? In this webinar, SAP’s Dr Mark von Kopp and Bernard Doering from Cloudera reveal why Big Data is about more than the “3 Vs” and how to create a unified data management framework that will actively streamline your IT landscape.
Take a look at this fact sheet to discover the future of Big Data now.
More information at http://www.sapbigdatabigthinking.com/
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big DataHortonworks
Hadoop is a great platform for storing and processing massive amounts of data. Elasticsearch is the ideal solution for Searching and Visualizing the same data. Join us to learn how you can leverage the full power of both platforms to maximize the value of your Big Data.
In this webinar we'll walk you through:
How Elasticsearch fits in the Modern Data Architecture.
A demo of Elasticsearch and Hortonworks Data Platform.
Best practices for combining Elasticsearch and Hortonworks Data Platform to extract maximum insights from your data.
This slide gives a simple and purposeful knowledge about popular Hadoop platforms.
From simple definition to importance of Hadoop in modern era the presentation also introduces Hadoop service providers along with its core components.
Do go through it once and comment below with your feedback. I am sure that this slide will help many in presenting basics of Hadoop for their projects or business purpose.
The crisp information has been generated after going through detailed information available on internet as well as research papers
Cisco Big Data Warehouse Expansion Featuring MapR DistributionAppfluent Technology
Learn more about the Cisco Big Data Warehouse Expansion Solution featuring MapR Distribution including Apache Hadoop.
The BDWE solution begins with the collection of data usage statistics by Appfluent. Then the BDWE solution optimizes Cisco UCS hardware for running the MapR Distribution including Hadoop, software for federating multiple data sources, and a comprehensive services methodology for assessing, migrating, virtualizing, and operating a logically expanded warehouse.
Enrich a 360-degree Customer View with Splunk and Apache HadoopHortonworks
What if your organization could obtain a 360 degree view of the customer across offline, online and social and mobile channels? Attend this webinar with Splunk and Hortonworks and see examples of how marketing, business and operations analysts can reach across disparate data sets in Hadoop to spot new opportunities for up-sell and cross-sell. We'll also cover examples of how to measure buyer sentiment and changes in buyer behavior. Along with best practices on how to use data in Hadoop with Splunk to assign customer influence scores that online, call-center, and retail branches can use to customize more compelling products and promotions.
Hitachi Data Systems Hadoop Solution. Customers are seeing exponential growth of unstructured data from their social media websites to operational sources. Their enterprise data warehouses are not designed to handle such high volumes and varieties of data. Hadoop, the latest software platform that scales to process massive volumes of unstructured and semi-structured data by distributing the workload through clusters of servers, is giving customers new option to tackle data growth and deploy big data analysis to help better understand their business. Hitachi Data Systems is launching its latest Hadoop reference architecture, which is pre-tested with Cloudera Hadoop distribution to provide a faster time to market for customers deploying Hadoop applications. HDS, Cloudera and Hitachi Consulting will present together and explain how to get you there. Attend this WebTech and learn how to: Solve big-data problems with Hadoop. Deploy Hadoop in your data warehouse environment to better manage your unstructured and structured data. Implement Hadoop using HDS Hadoop reference architecture. For more information on Hitachi Data Systems Hadoop Solution please read our blog: http://blogs.hds.com/hdsblog/2012/07/a-series-on-hadoop-architecture.html
The Briefing Room with William McKnight and Actian
Live Webcast on October 14, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=135528d85baa96a07850bd35961d459d
Integrating Hadoop with existing data sources, workflows and analytics can be a real challenge. While some components, like Hive and Spark, can give SQL access to Hadoop data, there isn’t much that enables Hadoop to be treated as a genuine BI and analytics platform, capable of running multiple jobs that serve multiple users and multiple applications. But what if you could turn Hadoop into a versatile, high performance development platform, forgoing all the pain of figuring out how and where to manage big data?
Register for this episode of The Briefing Room to hear veteran Analyst William McKnight as he discusses the fairly swift evolution of Hadoop’s capabilities. He’ll be briefed by Jim Hare of Actian, who will tout his company’s latest addition to its Analytic Platform: Hadoop SQL Edition. He will show how Actian has leveraged Hadoop and its scale out file system to create a fully functioning platform, providing everything from an analytic database to machine learning.
Visit InsideAnlaysis.com for more information.
Splunk Announces Beta Version of Hunk: Splunk Analytics for Hadoop
New Software Product to Explore, Analyze and Visualize Data in Hadoop
HADOOP SUMMIT NORTH AMERICA 2013, SAN JOSE – June 26, 2013 - Splunk Inc. (NASDAQ: SPLK), the leading software platform for real-time operational intelligence, today announced the beta version of Hunk: Splunk® Analytics for Hadoop. Hunk (beta) is a new software product from Splunk that integrates exploration, analysis and visualization of data in Hadoop. Building upon Splunk’s years of experience with big data analytics technology deployed at thousands of customers, Hunk drives dramatic improvements in the speed and simplicity of interacting with and analyzing data in Hadoop without programming, costly integrations or forced data migrations. Watch the Hunk video to learn more.
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
Big Data Made Easy: A Simple, Scalable Solution for Getting Started with HadoopPrecisely
With so many new, evolving frameworks, tools, and languages, a new big data project can lead to confusion and unwarranted risk.
Many organizations have found Data Warehouse Optimization with Hadoop to be a good starting point on their Big Data journey. Offloading ETL workloads from the enterprise data warehouse (EDW) into Hadoop is a well-defined use case that produces tangible results for driving more insights while lowering costs. You gain significant business agility, avoid costly EDW upgrades, and free up EDW capacity for faster queries. This quick win builds credibility and generates savings to reinvest in more Big Data projects.
A proven reference architecture that includes everything you need in a turnkey solution – the Hadoop distribution, data integration software, servers, networking and services – makes it even easier to get started.
Oracle Unified Information Architeture + Analytics by ExampleHarald Erb
Der Vortrag gibt zunächst einen Architektur-Überblick zu den UIA-Komponenten und deren Zusammenspiel. Anhand eines Use Cases wird vorgestellt, wie im "UIA Data Reservoir" einerseits kostengünstig aktuelle Daten "as is" in einem Hadoop File System (HDFS) und andererseits veredelte Daten in einem Oracle 12c Data Warehouse miteinander kombiniert oder auch per Direktzugriff in Oracle Business Intelligence ausgewertet bzw. mit Endeca Information Discovery auf neue Zusammenhänge untersucht werden.
Hadoop and Spark are big data frameworks used to extract useful span a variety of scenarios from ingestion, data prep, data management, processing, analyzing and visualizing data. Each step requires specialized toolsets to be productive. In this talk I will share solution examples in the Big Data ecosystem such as Cask, StreamSets, Datameer, AtScale, Dataiku on Microsoft’s Azure HDInsight that simplify your Big Data solutions. Azure HDInsight is a cloud Spark and Hadoop service for the enterprise and take advantage of all the benefits of HDInsight giving you the best of both worlds. Join this session for practical information that will enable faster time to insights for you and your business.
Sample portfolio of Brett Sheppard marketing in previous roles at Tableau, Splunk, DxContinuum / ServiceNow and Datadog including authored publications, narratives and product marketing, case studies, community and partner marketing, and analyst relations.
How Comcast Turns Big Data into Real Time Operational Insights: Winter Olympi...Brett Sheppard
2014 O'Reilly Strata conference presentation by Patrick Shumate and Brett Sheppard, about the Comcast technology stack delivering content from the 2014 Winter Olympics in Sochi. The session and slides are presented with approval from NBC and its parent company Comcast.
Checklist for early-stage startups to improve search engine optimization (SEO) for organic search, as part of a lead generation blog series by Brett Sheppard @zettaforce
The power to predict can give sales teams an “unfair advantage”. Predictive analytics can help your business-to-business (B2B) sales team leapfrog the competition and reduce the time from initial contact to sales closure. Tracking sales velocity is a good way to pinpoint where your sales and marketing execution fails to engage customers. Deals that drag on waste valuable sales resources and make it challenging for sales leadership to prepare accurate revenue forecasts. High-performing sales teams improve sales velocity and achieve competitive advantage using turn-key predictive analytics applications. Predictive models can be very powerful and profitable, even if they just give you a small edge in determining which option to choose or path to take. In this DxContinuum webinar with guest Forrester Research, learn best practices for how your organization can improve sales velocity with predictive analytics.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
National Security Agency - NSA mobile device best practices
Cloudera Hunk
1. SOLUTION BRIEF
Unlock the Business Value of Archived Data with
Cloudera and Hunk™
: Splunk Analytics for Hadoop
Unstructured data, much of it generated by machines or sensors, accounts for more than 90% of
data today. Organizations faced with the sheer complexity and scale of this data see the benefits
of Hadoop for economical long-term storage, but often struggle to manage that data in Hadoop.
Without a flexible, scalable, and secure data management solution, business analysts can miss
decision windows or make incomplete decisions based on limited or incomplete data—at great
cost to the organization.
Leveraging the Cloudera Enterprise Data Hub and Hunk™ for Hadoop
Archive Business Analytics
The growing volume and complexity of data highlights the fault lines in conventional approaches
to information management. Success in an ever-competitive data-driven market requires flexible,
massively scalable data management systems that grow with your business at a reasonable cost.
The enterprise data hub (EDH), delivered through Cloudera Enterprise, is a transformative active
archive solution helping enterprises gain more insight across all their data to make more informed
decisions. The Cloudera's enterprise data hub provides one place to economically store all historical
data, in any format, at any volume, for as long as needed without costly data movement, enabling
you to meet compliance management, security and governance requirements, while delivering data
on demand for reporting, exploration, and analysis.
The fully integrated EDH provided by Cloudera constitutes a highly scalable storage and multi-
workload processing platform, providing essential production capabilities such as security, resource
management, production workload visibility, multi-file format support, and cross-workload
optimizations that seamlessly integrate with specialized systems in your existing environment.
Integration of Cloudera EDH and Hunk™
Hunk is a full-featured platform for rapidly exploring, analyzing and visualizing data in Hadoop.
Based on years of experience building big data products deployed at thousands of Splunk customers,
Hunk automatically adds structure and identifies fields of interest at search time to deliver a faster,
more interactive experience from the data in your EDH. In Hunk, change perspectives on-the-fly,
preview results as MapReduce jobs are running, and govern access with role-based security. The
result is you no longer need a science project to get business value from your data in Hadoop.
Hunk natively integrates with the Cloudera
Distribution of Apache Hadoop (CDH) and the
Cloudera's enterprise data hub through the
Apache MapReduce framework. The combina-
tion of Hunk and Cloudera allows you to detect
patterns and find anomalies across terabytes
or petabytes of raw data in the EDH. Splunk’s
Search Processing Language (SPL™), Data
Model and Pivot enable rapid data exploration
without the need for specialized skills. With
Hunk and Cloudera, unlocking the business
value of data in Hadoop is faster and easier
than you thought possible.
SPLUNK
INDUSTRY
Machine-generated Big Data
WEBSITE
www.splunk.com
COMPANY OVERVIEW
Splunk Inc. (NASDAQ: SPLK) provides
the leading software platform for real-
time Operational Intelligence. Splunk®
software and cloud services enable or-
ganizations to search, monitor, analyze
and visualize machine-generated big
data coming from websites, applica-
tions, servers, networks, sensors and
mobile devices.
PRODUCT OVERVIEW
More than 7,000 enterprises, govern-
ment agencies, universities and service
providers in over 90 countries use
Splunk software to deepen business
and customer understanding, mitigate
cybersecurity risk, prevent fraud, im-
prove service performance and reduce
cost. Splunk products include Splunk®
Enterprise, Hunk™, Splunk Cloud™ and
premium Splunk Apps.
SOLUTION HIGHLIGHTS
>> Explore, analyze and visualize
raw unstructured data in Cloudera
Enterprise
>> Simply point Hunk at your Cloudera
cluster and start exploring data
immediately
>> Archive to Cloudera
I’m super excited about Hunk. Hunk is
solving one of the top issues that our
customers have—access to the skills
and know-how to leverage the data
inside of Hadoop. Splunk has a very
beautiful user interface that is very
easy to learn. So it bridges that gap
and makes it very easy to access the
data inside of Hadoop.
DR. AMR AWADALLAH
CTO, CLOUDERA
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