Webinar

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Removing the Data Obstacles in Data Science

Stop fighting your data and start using it. Watch Posit and Databricks discuss best practices for overcoming data governance hurdles and streamlining access to company assets.
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Many companies today have assembled teams of data scientists to identify trends, predict outcomes, and make recommendations. While these organizations have invested in specialized development tools for data science, they’ve not invested in data development tools.

Finding and accessing a company’s data assets is complex and time-consuming. Data scientists must often rely on meetings, conversations, and manual coding/configurations to find and access the necessary data. This, along with the complexities of data governance, dramatically impacts the data scientist’s ability to deliver.

Tools that can navigate data governance complexity and allow data scientists to streamline their data access work can help. Join TDWI Research Fellow Evan Levy, along with experts from Posit and Databricks, as they discuss tools, approaches, and best practices to work through and remove data scientists’ data governance and data management obstacles.

Topics include:

  • The current state of data science
  • Data obstacles in data science, including data access
  • Streamlining data governance complexity for data scientists
  • How Databricks and Posit can help overcome challenges

Speakers

James Blair Headshot

James Blair

Sr. Product Manager, Posit
James Blair is a Senior Product Manager at Posit, where he focuses on helping Posit commercial products seamlessly integrate into cloud platforms and environments. He has a background in statistics and data science and finds any excuse he can to write R code and ride his bike, although usually not at the same time.

Zac Davis

Solutions Architect at Databricks
Zac Davis is a Senior Solutions Architect at Databricks, based in Sydney, Australia, where he helps customers design and implement data and AI solutions. Formerly a Data Scientist, Zac contributes to several R packages, including sparklyr and brickster.