All Videos Tagged Data Blending (Data Science Central) - Data Science Central 2019-11-22T20:43:04Z https://www.datasciencecentral.com/video/video/listTagged?tag=Data+Blending&rss=yes&xn_auth=no Practical Application of Data in Politics tag:www.datasciencecentral.com,2016-08-16:6448529:Video:459502 2016-08-16T20:24:27.716Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/practical-application-of-data-in-politics"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781532806?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>It goes without saying, we live in a very data-rich age. In the political arena, sophisticated analytic firms like Deep Root manage and analyze an ever-growing list of data sources to project voter turnout and predict vote choice. To do this, they must first access and acquire the data, and then build complex data blending and analysis workflows to turn a… <a href="https://www.datasciencecentral.com/video/practical-application-of-data-in-politics"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781532806?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />It goes without saying, we live in a very data-rich age. In the political arena, sophisticated analytic firms like Deep Root manage and analyze an ever-growing list of data sources to project voter turnout and predict vote choice. To do this, they must first access and acquire the data, and then build complex data blending and analysis workflows to turn a variety of unlinked data sources into a single, actionable database of information. Only then can they decide which voters to speak with, with what message and through which media.<br /> <br /> Join us for our latest Data Science Central Webinar and learn how Alteryx, Amazon Web Services, and Deep Root Analytics work together to leverage numerous data sources to quickly deliver critical insights.<br /> <br /> You will learn how to:<br /> <br /> Quickly blend and analyze data from all sources - cloud and local<br /> Apply predictive and geo-spatial analytics to big data<br /> Enable data analysts with the cloud computing power of Amazon Web Services<br /> Empower the organization at large with analytic visualizations from Tableau<br /> Speakers:<br /> Raman Kaler, Alliance Manager -- Alteryx<br /> Nick Tussing, Solutions Engineer -- Alteryx<br /> Danielle Mendheim, Database Analyst -- Deep Root Analytics<br /> Mandus Momberg, Solutions Architect -- Amazon Web Services<br /> <br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central Faster Self-Service Analytics with Salesforce Data & Visualizations tag:www.datasciencecentral.com,2016-07-28:6448529:Video:452753 2016-07-28T23:11:20.229Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/faster-self-service-analytics-with-salesforce-data-visualizations"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781530842?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>The de facto CRM for most organizations today is Salesforce. The sales, marketing, and service data found in Salesforce often needs to be combined with other data sources for impactful business insights. Blending, enriching, and analyzing Salesforce data with other sources takes time and slows time to critical insights. Ryder Systems - a… <a href="https://www.datasciencecentral.com/video/faster-self-service-analytics-with-salesforce-data-visualizations"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781530842?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />The de facto CRM for most organizations today is Salesforce. The sales, marketing, and service data found in Salesforce often needs to be combined with other data sources for impactful business insights. Blending, enriching, and analyzing Salesforce data with other sources takes time and slows time to critical insights. Ryder Systems - a leading provider of global commercial transportation, logistics, and supply chain management solutions – has overcome such analytic obstacles firsthand.<br /> <br /> In this latest Data Science Central webinar, you will learn how organizations like Ryder can easily harness the power of Salesforce by using self-service analytics to:<br /> <br /> Blend your Salesforce data with other data sources, including databases, applications and spreadsheets – in hours, not weeks<br /> Apply advanced analytics to your CRM data for richer insights<br /> Produce dashboards and visualizations for analysis<br /> Join us for this live webinar to learn how leading organizations are accelerating their analytics and visualizations for deeper insights through self-service analytics.<br /> <br /> Speakers:<br /> Raman Kaler, Alliance Manager -- Alteryx<br /> Thuy Ngyuen, Solutions Engineer -- Alteryx<br /> Benjamin Pruden, Director of Product Marketing -- Salesforce Wave Analytics Cloud<br /> Kaitlyn Joffe, Customer Intelligence &amp; Insights Analyst -- Ryder System, Inc<br /> Sumit Tuteja, Sr. Marketing Analyst -- Ryder System, Inc.<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central 4 Steps to improve your Search Technology and Boost Sales, BI and User Experience tag:www.datasciencecentral.com,2016-07-21:6448529:Video:450384 2016-07-21T12:01:47.711Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/4-steps-to-improve-your-search-technology-and-boost-sales-bi-and-"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781530938?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Visitors who search within e-commerce sites are two to three times more likely to convert compared to those who don't. Improving search relevancy and user experience can significantly boost your bottom line. Frequently, users will search for a product, don’t find it, and leave because of poor search technology/algorithms. This webinar… <a href="https://www.datasciencecentral.com/video/4-steps-to-improve-your-search-technology-and-boost-sales-bi-and-"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781530938?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Visitors who search within e-commerce sites are two to three times more likely to convert compared to those who don't. Improving search relevancy and user experience can significantly boost your bottom line. Frequently, users will search for a product, don’t find it, and leave because of poor search technology/algorithms. This webinar addresses these issues.<br /> <br /> In this latest Data Science Central Webinar event, you will learn from CrowdFlower and its customers --Adobe and Etsy-- four techniques to improve your search relevance practices, business outcomes and user experience.<br /> <br /> Measurement: To update your site’s internal search functionality, it’s vital that you know exactly what metrics your company should optimize. Learn how you should sample queries for measurement.<br /> Incorporating Human-Labeled Data: Labeled Data-Metrics such as click data are valuable, but on their own they don't tell the complete story. Human-curated training data can contribute valuable additional information. CrowdFlower, Adobe and Etsy will share how they use a human-in-the-loop approach to grade results, whether it involves images, descriptions, or an entire page of results.<br /> Improve your search filtering UI: CrowdFlower, Adobe and Etsy will share how they examined their individual result pages to help build out additional categories and tags to improve customer search experiences.<br /> Ranking features: A key use of human-curated training data is ranking features. Adobe will discuss how they use a human-in-the-loop approach to verify their deep learning image tagger based upon contributor photographers.<br /> Learn how these leading companies design their site search interfaces, surface their results, and constantly refine them to enhance your own site’s search relevance to improve customer experience.<br /> <br /> Speakers:<br /> Lukas Biewald, CEO and Co-Founder -- CrowdFlower<br /> Jaime DeLanghe, Product Manager -- Etsy<br /> Andy Edmonds, Search Science Architect -- Adobe<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central New Methods for Data Preparation, Advanced Analytics, and Visual Analytics tag:www.datasciencecentral.com,2016-07-19:6448529:Video:449904 2016-07-19T05:17:51.713Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/new-methods-for-data-preparation-advanced-analytics-and-visual-an"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781530901?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>To gain a competitive advantage, businesses need to be able to access, blend, and perform advanced analytics on all their data. Traditionally the analytic process would involve multiple groups, the slow building of data marts and intensive coding. However new tools allow businesses to create a culture of self-service analytics, by… <a href="https://www.datasciencecentral.com/video/new-methods-for-data-preparation-advanced-analytics-and-visual-an"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781530901?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />To gain a competitive advantage, businesses need to be able to access, blend, and perform advanced analytics on all their data. Traditionally the analytic process would involve multiple groups, the slow building of data marts and intensive coding. However new tools allow businesses to create a culture of self-service analytics, by enabling all these steps within an easy to use repeatable workflow and ad hoc data discovery through visual analytics. In this webinar you’ll learn by example as we walk through how to:<br /> <br /> Perform basic data blending tasks such as parsing XML data<br /> Utilise predictive analytics to analyze part failure trends<br /> Apply spatial analytics to find and analyse customer behavior by store<br /> Output all underlying analytic work to visual format<br /> Register for this latest Data Science Central webinar and see how you can establish an easy method for data blending, advanced analytics, and visual data discovery.<br /> <br /> Speakers:<br /> Shaan Mistry, Solutions Engineer -- Alteryx<br /> Thomas Christian, Senior Product Consultant -- Tableau<br /> <br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central Enhance Predictive Modeling with Better Data Preparation tag:www.datasciencecentral.com,2016-06-22:6448529:Video:438922 2016-06-22T16:53:48.583Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/enhance-predictive-modeling-with-better-data-preparation"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781530779?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Predictive modeling can be tough to implement in itself. Additionally, increasing data types and sources are making the data preparation process more complex too. Experts know that while predictive modeling can deliver substantial business gains, it can also wreak havoc if the data used for analysis is not accurate or complete.<br></br> <br></br> In… <a href="https://www.datasciencecentral.com/video/enhance-predictive-modeling-with-better-data-preparation"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781530779?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Predictive modeling can be tough to implement in itself. Additionally, increasing data types and sources are making the data preparation process more complex too. Experts know that while predictive modeling can deliver substantial business gains, it can also wreak havoc if the data used for analysis is not accurate or complete.<br /> <br /> In this live webinar, we will walk you through the steps to build the right dataset for more accurate predictive modeling. You’ll learn how to:<br /> <br /> Access the quality of your data<br /> Cleanse and prepare data for analysis<br /> Decide what predictive modeling techniques to use<br /> Join the webinar to get practical advice on making data preparation and predictive analytics more accessible throughout your organization.<br /> <br /> Speakers:<br /> <br /> Dr. Dan Putler, Chief Scientist -- Alteryx<br /> Matt Madden, Product Director -- Alteryx<br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central