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Accelerating Energy Trading Analytics with Dash Enterprise
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[{"primary_field_html_id":"719653_161596pi_719653_161596","secondary_field_html_id":"Companypi_Company","primary_field_value":"Professional"},{"primary_field_html_id":"719653_161596pi_719653_161596","secondary_field_html_id":"719653_161605pi_719653_161605","primary_field_value":"Professional"}]; $('.form-field-primary input, .form-field-primary select').each(function(index, input) { $(input).on('change', window.piAjax.checkForDependentField); window.piAjax.checkForDependentField.call(input); }); })(); });})();</script> </div> </div> </div> <div id="paragraph" pardot-region="paragraph-1" pardot-repeatable pardot-region-type="pardot"> <p> As one of Europe’s leading gas companies and one of the world’s largest electricity producers, Uniper generates power in over 40 countries and manages a global energy trading portfolio. To adapt to radical market changes and competitor behavior, Uniper prioritizes digitalization, particularly in advanced analytics, automation, and algorithmic tools. </p> <p> Uniper turned to Dash Enterprise to access a centralized app management platform that accommodates various Python workflows, seeing decreased deployment time from four weeks to nine minutes while maintaining security compliance. </p> <p> Watch the recorded webinar to learn how Dash Enterprise enables the following: </p> <ul> <li>App deployment without lengthy IT lead times associated with infrastructure provisioning and configuration </li> <li>Integration with an existing automated CI/CD pipelines and single sign-on for user authentication, without manual operations </li> <li>Collaboration within the Databricks Python notebook environment, resulting in a growing user base and an increasing number of data apps </li> <li>Platform observability into the cloud-native Kubernetes architecture, granting greater power for administrators to track and control resource usage </li> </ul> </div> </div> </div> </div> <div class="section-speaker"> <div class="container"> <h2 class="speaker-title" pardot-region="speaker-section-title" pardot-repeatable> Meet the Speakers </h2> <div class="speakers" pardot-region="speakers" pardot-repeatable> <div class="speaker-item"> <div class="speaker-img"> <img src="https://images.prismic.io/plotly-marketing-website-2/68222ad4-08e4-4a52-83b0-633d970564f3_Volodymyr+Sorokoumov_Uniper+Webinar+Speaker.jpeg?auto=compress,format" /> </div> <div class="speaker-info"> <h3>Volodymyr Sorokoumov</h3> <p class="speaker-paragraph"> Volodymyr leads Platform Design and Operations team of Digital Trading at Uniper. During his tenure at the company, he has designed the company’s award-winning Azure data lake platform, implemented advanced analytics use cases like real-time analytics, and built numerous cloud-native applications focusing on hyperscaling, resilience, and high availability. Volodymyr also specializes in commodity and energy trading and is a Certified Business Analysis Professional (CBAP) and Energy Risk Professional (ERP). </p> </div> </div> <div class="speaker-item"> <div class="speaker-img"> <img src="https://images.prismic.io/plotly-marketing-website-2/b4c59352-4c59-4e44-adcf-a09ef04fe427_Tunay+Okumus_Uniper+Webinar+Speaker.jpeg?auto=compress,format" /> </div> <div class="speaker-info"> <h3>Tunay Okumus</h3> <p class="speaker-paragraph"> Tunay is an MLOps Engineer for Algo-Trading at Uniper. He designs and implements cloud-based machine learning solutions and data platforms for the company’s digital trading division. Previously, he developed computational models and simulation software in renewables energy topics (e.g. photovoltaics and lithium-ion batteries) via artificial neural networks and kinetic Monte Carlo method. Tunay holds a Master’s Degree in mechanical engineering from the Technical University of Braunschweig. 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