All Videos Tagged Dirty Data”, (Data Science Central) - Data Science Central 2019-08-25T01:53:33Z https://www.datasciencecentral.com/video/video/listTagged?tag=Dirty+Data%E2%80%9D%2C&rss=yes&xn_auth=no DSC Webinar Series: 4 Ways to Tackle Common Data Prep Issues tag:www.datasciencecentral.com,2018-09-25:6448529:Video:763220 2018-09-25T21:15:12.271Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-4-ways-to-tackle-common-data-prep-issues"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781532499?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>Anyone who's ever analyzed data knows the pain of digging in only to find that it is poorly structured, full of inaccuracies, or just plain incomplete. But "dirty data" isn't just a pain point for analysts; it can have a major financial and cultural impact on an organization.<br></br> <br></br> In this latest Data Science Central webinar, you will… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-4-ways-to-tackle-common-data-prep-issues"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781532499?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />Anyone who's ever analyzed data knows the pain of digging in only to find that it is poorly structured, full of inaccuracies, or just plain incomplete. But "dirty data" isn't just a pain point for analysts; it can have a major financial and cultural impact on an organization.<br /> <br /> In this latest Data Science Central webinar, you will learn four actionable ways to overcome common data preparation issues, including how to establish a company standard for "clean data" and how to democratize data prep across your organization.<br /> <br /> Speakers:<br /> Louis Archer, London Manager -- Tableau<br /> Marina Lindl, Sales Consultant -- Tableau <br /> <br /> Hosted by:<br /> Bill Vorhies, Editorial Director -- Data Science Central