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How Google Cloud's AlloyDB Empowers Bayer Crop Science to Overcome Data Challenges | Cloud Wars Live

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Contenido proporcionado por Bob Evans. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Bob Evans o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Bayer’s Data Evolution with AlloyDB

The Big Themes:

  • Data complexity and intelligent agriculture: Bayer Crop Science is addressing agriculture's complex data challenges. The company integrates data such as satellite imagery, weather conditions, soil data, and IoT device inputs, to drive innovation in seed development and farming practices. By leveraging cloud technologies like AlloyDB, Bayer's teams can support the future of farming, despite challenges posed by climate change and rising global food demand.
  • Integrating BigQuery for comprehensive analytics: To further enhance its data-driven insights, Bayer integrates Google BigQuery alongside AlloyDB for extensive data analysis. BigQuery serves as the central analytics warehouse, receiving billions of phenotypic data points for in-depth modeling and decision-making. During harvest season, Bayer can quickly access and analyze comprehensive datasets, enabling better decisions across production and supply chains.
  • Harvest season demands and system resilience: During harvest season, Bayer Crop Science faces intense pressure as high volumes of data flow in, requiring real-time analysis and decision-making. The peak demand period sees a sharp increase in read and write operations, making it essential for Bayer's data system to function seamlessly. AlloyDB played a crucial role in handling these spikes by providing low-latency data processing and high availability.

The Big Quote: “Climate change is a new challenge. You see some of these forecasts coming out of academia that yields will go down by 30% — that will arrest this great trend that we've seen continually increasing over the last 100 years. We need to solve for that, and that's going to take new types of data and new approaches and these types of things."

  continue reading

469 episodios

Artwork
iconCompartir
 
Manage episode 450967817 series 2536260
Contenido proporcionado por Bob Evans. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Bob Evans o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Bayer’s Data Evolution with AlloyDB

The Big Themes:

  • Data complexity and intelligent agriculture: Bayer Crop Science is addressing agriculture's complex data challenges. The company integrates data such as satellite imagery, weather conditions, soil data, and IoT device inputs, to drive innovation in seed development and farming practices. By leveraging cloud technologies like AlloyDB, Bayer's teams can support the future of farming, despite challenges posed by climate change and rising global food demand.
  • Integrating BigQuery for comprehensive analytics: To further enhance its data-driven insights, Bayer integrates Google BigQuery alongside AlloyDB for extensive data analysis. BigQuery serves as the central analytics warehouse, receiving billions of phenotypic data points for in-depth modeling and decision-making. During harvest season, Bayer can quickly access and analyze comprehensive datasets, enabling better decisions across production and supply chains.
  • Harvest season demands and system resilience: During harvest season, Bayer Crop Science faces intense pressure as high volumes of data flow in, requiring real-time analysis and decision-making. The peak demand period sees a sharp increase in read and write operations, making it essential for Bayer's data system to function seamlessly. AlloyDB played a crucial role in handling these spikes by providing low-latency data processing and high availability.

The Big Quote: “Climate change is a new challenge. You see some of these forecasts coming out of academia that yields will go down by 30% — that will arrest this great trend that we've seen continually increasing over the last 100 years. We need to solve for that, and that's going to take new types of data and new approaches and these types of things."

  continue reading

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