All Videos Tagged Management” (Data Science Central) - Data Science Central 2021-02-27T22:11:59Z https://www.datasciencecentral.com/video/video/listTagged?tag=Management%E2%80%9D&rss=yes&xn_auth=no DSC Webinar Series: Data Science Leadership Exchange: Best Practices for Driving Outcomes tag:www.datasciencecentral.com,2020-08-25:6448529:Video:978394 2020-08-25T22:43:07.968Z Sean Welch https://www.datasciencecentral.com/profile/SeanWelch <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-leadership-exchange-best"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/7614174854?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Despite an increasing awareness of the role data science plays in successful business outcomes, data science leaders still struggle to organize, implement and communicate effective data science initiatives. <br></br> <br></br> Join “Data Science Leadership Exchange: Best Practices for Driving Outcomes,” and gain advice on optimizing your data management… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-leadership-exchange-best"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/7614174854?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Despite an increasing awareness of the role data science plays in successful business outcomes, data science leaders still struggle to organize, implement and communicate effective data science initiatives. <br /> <br /> Join “Data Science Leadership Exchange: Best Practices for Driving Outcomes,” and gain advice on optimizing your data management strategies. In this latest Data Science Central webinar, some of the industry’s best and brightest from Bayer, S&amp;P Global and Transamerica will be presenting their insights and experiences. <br /> <br /> Sponsored by Domino Data Lab, our distinguished group of panelists will discuss:<br /> <br /> The pros and cons of different data science organizational structures<br /> Best practices across each phase of the data science lifecycle, from model ideation through production models ops and ongoing model management<br /> Firsthand success stories — and answers to your questions<br /> <br /> Speakers: <br /> Brian Loyal, Cloud Analytics Lead - Bayer Crop Science<br /> Patrick Harrison, Director of AI Engineering - S&amp;P Global<br /> Matt Cornett, Director of Data Science - Transamerica<br /> <br /> Hosted by: <br /> Bill Vorhies, Editorial Contributor - Data Science Central DSC Webinar Series: DataOps: How Bell Canada Powers their Business with Data tag:www.datasciencecentral.com,2020-07-15:6448529:Video:962289 2020-07-15T22:44:32.762Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-dataops-how-bell-canada-powers-their-business"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/6911730865?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Agile data management has become a necessity for organizations that need to maximize the value of their data. The business is focused on outcomes but the bulk of the effort is built around data processing and delivery.  Demand for data outstrips the capacity of IT organizations and data engineering teams to deliver. New data management… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-dataops-how-bell-canada-powers-their-business"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/6911730865?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Agile data management has become a necessity for organizations that need to maximize the value of their data. The business is focused on outcomes but the bulk of the effort is built around data processing and delivery.  Demand for data outstrips the capacity of IT organizations and data engineering teams to deliver. New data management practices that adapt the practices DevOps to support data operations (DataOps) are the key to agility in data management. The enabling technologies exist today and data management practices are moving quickly toward a future of DataOps. DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics.<br /> <br /> In this latest Data Science Central webinar, you will learn:<br /> <br /> How to identify the most impactful bottlenecks sitting in the way of streamlined data processing<br /> How to evaluate multiple strategies for improving data processing outcomes and their relative impact<br /> Where to prioritize people, process, and technology changes to maximize impact<br /> How Bell revolutionized their data delivery framework by incorporating DataOps principles and technology<br /> <br /> Speakers: <br /> Johnathan Bald, Sr. Director of Sales - Hitachi Vantara<br /> Jude Vanniasinghe, Sr. Manager of Business Intelligence - Bell<br /> <br /> Presentation Moderator: <br /> Mike Williams, Global Solution Lead, Analytics and IoT - Hitachi Vantara<br /> <br /> Hosted by: <br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: Accelerating AI Adoption with Machine Learning Operations (MLOps) tag:www.datasciencecentral.com,2020-03-31:6448529:Video:941928 2020-03-31T23:12:14.852Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerating-ai-adoption-with-machine-learning"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/4287841545?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.<br></br> <br></br> In this… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerating-ai-adoption-with-machine-learning"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/4287841545?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Massive investments in data science teams and machine learning platforms have yet to yield results for most companies. The last mile for AI project success is the deployment and management of models in production requiring new technology and practices. This new area is called Machine Learning Operations or MLOps.<br /> <br /> In this latest Data Science Central webinar, you will get an overview of MLOps and discover the issues, capabilities, and best practices required for successful and sustained deployment of machine learning in production, including:<br /> <br /> ●    The challenges of production model deployment - and how to overcome them<br /> ●    Best practices to avoid production model monitoring pitfalls<br /> ●    How to maintain high-performing models using production lifecycle management<br /> ●    Mastering production model governance to minimize risk and ensure regulatory compliance<br /> <br /> Speaker: <br /> Sivan Metzger, Managing Director, MLOps &amp; Governance - DataRobot<br /> <br /> Hosted by:<br /> Sean Welch, Host and Producer - Data Science Central DSC Webinar Series: Accelerate Analytics Projects with Data Prep on AWS tag:www.datasciencecentral.com,2019-08-15:6448529:Video:869444 2019-08-15T21:54:59.827Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerate-analytics-projects-with-data-prep"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3428295029?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Leveraging the benefits of effective data preparation to help build a modern ERP system is a vital component in innovating an organization's data workflow systems. Complex pattern matching and parsing of unstructured data requires a great deal of time and effort often utilizing labor-intensive hand coding.<br></br> <br></br> Join us for this… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-accelerate-analytics-projects-with-data-prep"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3428295029?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Leveraging the benefits of effective data preparation to help build a modern ERP system is a vital component in innovating an organization's data workflow systems. Complex pattern matching and parsing of unstructured data requires a great deal of time and effort often utilizing labor-intensive hand coding.<br /> <br /> Join us for this latest Data Science Central webinar to learn how B/A Products Company has managed to cut 6-12 months process time of reformatting, restructuring and preparing data down to only 2 months through automation and simplification.<br /> <br /> In this webinar you will:<br /> <br /> • Understand technology trends that simplify your analytics modernization journey<br /> • Learn about the challenges and solutions that B/A Products Company used to solve their issues with legacy ERP systems<br /> • Learn how to accelerate time-to-value for analytics projects with data preparation on AWS<br /> • See in action the before / after with the solution live demo<br /> <br /> Speakers:<br /> Jacob S J Joseph, Information Systems Manager - B/A Products Co.<br /> Samantha Winters, Director of Marketing and Business Analytics - B/A Products Co.<br /> Matt Derda, Customer Marketing Manager - Trifacta<br /> <br /> Hosted by:<br /> Stephanie Glen, Editorial Director - Data Science Central DSC Webinar Series: The State of Data Preparation in 2019 tag:www.datasciencecentral.com,2019-06-25:6448529:Video:846235 2019-06-25T21:30:56.229Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-the-state-of-data-preparation-in-2019-1"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/3109900816?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Over the past few years, data preparation has emerged as a stand-alone category within data management and analytics. A technology category that originated out of joint research across UC Berkeley and Stanford, it is now recognized as a critical technology by end users, organizations and industry analysts alike. Data preparation has evolved… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-the-state-of-data-preparation-in-2019-1"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/3109900816?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Over the past few years, data preparation has emerged as a stand-alone category within data management and analytics. A technology category that originated out of joint research across UC Berkeley and Stanford, it is now recognized as a critical technology by end users, organizations and industry analysts alike. Data preparation has evolved tremendously since the category first emerged in 2015. So what’s new? How far have we come? Where are we headed in the future?<br /> <br /> Join this latest Data Science Central webinar with Dresner Advisory Service’s Chief Research Officer, Howard Dresner, for an overview of the data preparation market. In the session, Howard reviews findings from his 2019 “Wisdom of the Crowds Market Study” on data preparation, compiled from end user responses.<br /> <br /> This webinar will cover the following topics:<br /> <br /> How data preparation is being utilized within organizations – what users &amp; departments utilize data prep?<br /> What are the most critical features of data preparation technologies?<br /> Differences between traditional ETL technologies and this new generation of data preparation tools.<br /> <br /> Speakers:<br /> Howard Dresner, Chief Research Officer Analyst - Dresner Advisory Services<br /> Will Davis, Senior Director of Product Marketing - Trifacta<br /> <br /> Hosted by:<br /> Rafael Knuth, Contributing Editor - Data Science Central