February 15, 2019 | Written by: Jesper Gardtman
Categorized: Analytics | Webinar
Share this post:
Increased productivity is key for everyone working within the field of Data Science
Machine Learning is or will be critical to the success of your business, regardless of industry. However, Gartner predicts that 60% of big data projects will fail to go beyond piloting and experimentation and will be abandoned.
Moreover, the average Data Science team has very few models in production:
- 80% of their time is spent wrangling and cleansing data
- Getting access to data is a challenge and data quality, governance and security are pressing issues
- Hiring and retaining talent is difficult
In the webinar, we will cover:
- Through demos how you as Data Scientists, Data Engineers and Data Stewards can collaborate, leveraging popular open source tools like RStudio or notebooks written in python, R or Scala together with efficient collection, masking, cataloging and integration of structured and unstructured data
- Customer examples of how teams build, deploy, monitor and enhance machine learning models and how different personas collaborate on building and deploying a use case
February 21st, 2019, at 14:00 CET
To register and watch, click here!
Please note that the webinar is valuable for a wide range of roles across industries, including: Head of Data Science, Head of Business Intelligence, Head of Analytics, CTO, Data Scientist and Data Engineer
If you have any questions regarding the webinar, please do not hesitate to contact me at firstname.lastname@example.org