Overcoming the challenges of data science deployment
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Overcoming the challenges of data science deployment
In this webinar, Bellrock Technology Product Manager, Dr. David Bell, discusses how to overcome the challenges of data science deployment.
With 4 out 5 data science projects failing to make it into production, deployment is a key issue for the industry and will be a key area to generate ROI and unlock future investments across pretty much every market sector.
Spoiler alert! Deploying data science is hard.
Organisations have data siloed across a wide range of sources with a varied range of quality and accessibility. The models created are increasingly complex and written in languages that are unknown to many IT professionals (who have their day to day challenges). Then, to compound the pain, business users have exceptionally high levels of expectations for strong visualisations and real time insights delivered to their platforms of choice.
It is little wonder that Data Scientists end up spending most of their time piecing all of this together rather than doing what they are good at, building models for your organisation.
During this session David will discuss:
• Why is Data Science deployment so hard
• Expectations vs reality
• Overcoming the 5 main challenges
• What could a solution look like
Dr. David Bell, Product Manager, Bellrock Technology
David Bell has a PhD in Artificial Intelligence and is the Product Manager with Bellrock Technology. Having spent years developing and delivering data driven solutions in both academic and industrial contexts, he is now leveraging that experience to drive forward the product vision for Lumen, Bellrock Technology's intelligent deployment platform.
Bellrock Technology
Bellrock Technology is a software company based in Glasgow. The company was founded to help large organisations become data-driven. Our customers deploy their models utilising their live and static data to deliver maximum business value to their companies.
Bellrock Technology developed Lumen®, the world’s most advanced analytics deployment platform, in order to instantly turn trained data science models into live, useful data analytics. Its patented technology removes traditional integration and deployment challenges, automatically creating complex data-pipelines and making results immediately available to end users.
