All Videos Tagged Hortonworks (Data Science Central) - Data Science Central 2020-10-23T06:23:58Z https://www.datasciencecentral.com/video/video/listTagged?tag=Hortonworks&rss=yes&xn_auth=no Best Fit Engineering for SQL on Hadoop tag:www.datasciencecentral.com,2015-11-24:6448529:Video:354703 2015-11-24T23:56:17.392Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-best-fit-engineering-for-sql-on-hadoop"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781530047?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>In our latest DSC Webinar series as we discuss how enterprises have increasingly large volumes of structured and semi-structured data generated by all sorts of applications. Much of that data is increasingly finding its way into Hadoop clusters for analytics because of its versatility and the economical, linear scalability of both data storage… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-best-fit-engineering-for-sql-on-hadoop"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781530047?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />In our latest DSC Webinar series as we discuss how enterprises have increasingly large volumes of structured and semi-structured data generated by all sorts of applications. Much of that data is increasingly finding its way into Hadoop clusters for analytics because of its versatility and the economical, linear scalability of both data storage and compute. And SQL is still the best option for querying it:<br /> <br /> SQL is the universal connector to many BI tools and technologies<br /> Prevalent SQL skills overcome the Hadoop skills gap<br /> Hadooponomics enables more analytics on more data at a much lower cost<br /> Forrester recently concluded that organizations need to choose more than one SQL-on-Hadoop tool to satisfy all requirements. Hortonworks and Teradata agree in this “best fit engineering” approach designed to match the benefits of each tool set to map to actual workload requirements, while remaining true to 100% open source innovation.<br /> <br /> You will learn about SQL on Hadoop best practices, including:<br /> <br /> A brief history of SQL on Hadoop<br /> Architecture and use cases for Hive and Presto<br /> Technical deep dive and futures for Hive and Presto<br /> <br /> Speakers:<br /> <br /> Mark Shainman, Program Manager -- Teradata<br /> Mark Lochbihler, Director, Partner Engineering -- Hortonworks<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central Deriving Analytic Insights from Machine Data and IoT Sensors tag:www.datasciencecentral.com,2015-06-25:6448529:Video:293848 2015-06-25T18:31:18.713Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/deriving-analytic-insights-from-machine-data-and-iot-sensors"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781527456?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Hadoop and The Internet of Things has enabled data driven companies to leverage new data sources and apply new analytical techniques in creative ways that provide competitive advantage. Beyond clickstream data, companies are finding transformational insights stemming from machine data and telemetry that are radically improving operational… <a href="https://www.datasciencecentral.com/video/deriving-analytic-insights-from-machine-data-and-iot-sensors"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781527456?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Hadoop and The Internet of Things has enabled data driven companies to leverage new data sources and apply new analytical techniques in creative ways that provide competitive advantage. Beyond clickstream data, companies are finding transformational insights stemming from machine data and telemetry that are radically improving operational efficiencies and yielding new actionable customer insights.<br /> <br /> We will discuss real world case studies from the field that describe the strategies, architectures, and results from forward thinking Fortune 500 organizations across a variety of verticals, including insurance, healthcare, media &amp; entertainment, communications, and manufacturing.<br /> <br /> Panelist:<br /> Chad Meley, Vice President of Product &amp; Services, Teradata<br /> John Kreisa, Vice President of Marketing Strategy, Hortonworks<br /> <br /> Hosted by:Bill Vorhies, Senior Contributing Editor, Data Science Central &amp; Data Magnum DSC Webinar Series: Better Risk Management with Apache Hadoop and RedHat tag:www.datasciencecentral.com,2015-03-03:6448529:Video:254156 2015-03-03T23:49:40.795Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-better-risk-management-with-apache-hadoop-and-"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781528035?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>The risk management systems that each firm operates must respond not only to new reporting requirements but also handle ever-growing amounts of data to perform more comprehensive analysis. Most existing systems are not inherently designed to scale thus, many are inflexible and also expensive to operate.<br></br> <br></br> In today’s webinar… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-better-risk-management-with-apache-hadoop-and-"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781528035?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />The risk management systems that each firm operates must respond not only to new reporting requirements but also handle ever-growing amounts of data to perform more comprehensive analysis. Most existing systems are not inherently designed to scale thus, many are inflexible and also expensive to operate.<br /> <br /> In today’s webinar you’ll learn:<br /> -Details on a modern data architecture for financial services risk management.<br /> - Use cases and best practices of how other financial services are using this MDA for Risk Management.<br /> -Solutions that can help organizations scale-out, store real-time data with very low-latency, and efficiently process and store huge volumes of data that support advanced analytics capabilities. DSC Webinar Series: Data Transformation and Acquisition Techniques, to Handle Petabytes of Data tag:www.datasciencecentral.com,2014-11-11:6448529:Video:222794 2014-11-11T22:11:00.569Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-transformation-and-acquisition-techniques"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781527374?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Many organizations have become aware of the importance of big data technologies, such as Apache Hadoop but are struggling to determine the right architecture to integrate it with their existing analytics and data processing infrastructure. As companies are implementing Hadoop, they need to learn new skills and languages, which can impact… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-transformation-and-acquisition-techniques"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781527374?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Many organizations have become aware of the importance of big data technologies, such as Apache Hadoop but are struggling to determine the right architecture to integrate it with their existing analytics and data processing infrastructure. As companies are implementing Hadoop, they need to learn new skills and languages, which can impact developer productivity. Often times they resort to hand-coded solutions which can be brittle, impact the productivity of the developer and the efficiency of the Hadoop cluster.<br /> <br /> To truly tap into the business benefits of the big data solutions, it’s necessary to ensure that the business and IT have simple tools-based methods to get data in, change and transform it, and keep it continuously updated with their data warehouse.<br /> <br /> In this webinar you’ll learn how the Oracle and Hortonworks solution can:<br /> <br /> Accelerate developer productivity<br /> Optimize data transformation workloads for on Hadoop<br /> Lower cost of data storage and processing<br /> Minimize risks in deployment of big data projects<br /> Provide proven industrial scale tooling for data integration projects<br /> We will also discuss how technologies from both Oracle and Hortonworks can deploy the big data reservoir or data lake, an efficient cost-effective way to handle petabyte-scale data staging, transformations, and aged data requirements while reclaiming compute power and storage from your existing data warehouse.<br /> <br /> Speakers:<br /> Jeff Pollock, Vice President, Oracle<br /> Tim Hall, Vice President, Hortonworks<br /> <br /> Hosted by:<br /> Tim Matteson, Co-Founder, Data Science Central DSC Webinar Series: Hadoop 2.0: YARN to Further Optimize Data Processing tag:www.datasciencecentral.com,2014-09-16:6448529:Video:205640 2014-09-16T20:49:26.121Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/hadoop-2-0-yarn-to-further-optimize-data-processing"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781527185?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Data is exponentially increasing in both types and volumes, creating opportunities for businesses. To fully realize the potential of this new data, analysts recommend the shift from a single platform to a data ecosystem. Multiple systems are needed to exploit the variety and volume of data sources. A flexible data repository such as a data lake is… <a href="https://www.datasciencecentral.com/video/hadoop-2-0-yarn-to-further-optimize-data-processing"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781527185?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Data is exponentially increasing in both types and volumes, creating opportunities for businesses. To fully realize the potential of this new data, analysts recommend the shift from a single platform to a data ecosystem. Multiple systems are needed to exploit the variety and volume of data sources. A flexible data repository such as a data lake is needed to store the data. Technologically speaking Apache Hadoop 2 enables true data lake architectures. The introduction of YARN in particular added a pluggable framework that enabled new data access patterns in addition to MapReduce. An intelligent data management layer is needed to manage metadata and usage patterns as well as track consumption across these data platforms.<br /> <br /> Join us in this webinar as our panel of experts discusses how Hadoop can be used alongside the Enterprise Data Warehouse and with Data Integration tools to enable the optimization of data processing workloads for more efficient use of resources