Reduce Data Movement and Decrease Processing Times with a Machine Scale Feature Store(Molecula)

Building the Backend: Data Solutions that Power Leading Organizations

Travis Lawrence에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Travis Lawrence 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

4+ y ago 46:14

MP3•에피소드 홈

In this episode, we speak with H.O. Maycotte. H.O. is the CEO/founder of Molecula, an enterprise feature store that simplifies, accelerates, and controls big data access to power machine-scale analytics and AI. Molecula is powered by Pilosa, an open source project created by H.O. and team. Pilosa eliminates the need to copy data between systems in order to make it accessible for analytical and machine learning purposes at scale. Leading companies like Spotify, Hulu, Uber, Zillow, ESPN are all utilizing Pilosa.

Top 3 Value Bombs:

Large volume or complex workloads on a lake or DW can take hours to process, feature stores can reduce that to seconds in some scenarios.
On average, over 80% of an organization's data are copies of the original data. Reduce the movement and duplication of data across your organization.
Organizations do not have a data volume problem but rather data readiness problem. Enable the business with “real time” data.

43 에피소드

#Tech #Podcasting Education #Travis Lawrence