Abstract: 

When it comes to data science in the enterprise, organizations often face a culture of selfinterest that leads to unnecessary friction, infighting and inefficiencies, and ultimately a failure to realize the full potential of data science. It's a plot we're all familiar with from Game of Thrones, which is fine for a TV show, but not when you're trying to solve critical business problems. When synchronization is lacking across a data team - the LOB user demanding business answers, the data scientist under pressure to perform analysis, the compliance team governing data access - the swords and factions can come out, and no productive progress will be made.

In this keynote, David Taieb will examine the expectations and challenges around data science - including the shortage of technical expertise, overly complex and inaccessible analytics tools, and insufficient attention paid to data governance and cataloging - with a focus on how to reduce the costs and time-to-market associated with deploying analytics to end users, and ultimately operationalizing data science so it becomes a central business function. David will reveal some of the tools that data team members can use to better collaborate with one another to solve key business problems, including Jupyter Notebooks and PixieDust, an open source helper library that helps data scientists and developers more easily visualize data and build dashboards, making data more shareable and consumable across the business.

Bio: 

David Taieb is a Distinguished Engineer for the Watson Data Platform Developer Advocacy team at IBM, leading a team of avid technologists with the mission of educating developers on the art of possible with cloud technologies. He’s passionate about innovation and building Open Source tools like the PixieDust Python Library for Jupyter Notebooks and Apache Spark, that help improve developer productivity and overall experience. David enjoys sharing his experience by speaking at conferences and meeting as many people as possible.