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Innhold levert av Bob Evans. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Bob Evans eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
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Google Cloud's Gerrit Kazmaier & Rayn Veerubhotla On Unlocking the Future with AI and Multimodal Systems| Cloud Wars Live

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Manage episode 439130292 series 2536260
Innhold levert av Bob Evans. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Bob Evans eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Google Cloud Data Innovations

The Big Themes:

  • Integration of unstructured data with AI: Google Cloud is shifting how enterprises leverage their data by integrating unstructured data (which makes up 85-90% of all data) with structured data through its BigQuery multimodal data foundation. This integration allows for a more comprehensive data landscape where AI models can seamlessly access and analyze both types of data. This approach addresses the limitations of traditional data systems and unlocks new potential for AI-driven analytics.
  • The role of partners in maximizing AI and data value: Google Cloud’s service partners implement solutions and bring industry best practices to customer environments, while independent software vendors (ISVs) build applications that leverage Google Cloud’s data and AI tools. Programs like the Google Cloud Ready (GCR) initiative streamline integrations.
  • Integration challenge: The challenge for organizations lies in connecting disparate data sources, such as operational data from systems like SAP and CRM data from Salesforce, with analytics tools to enable real-time decision-making. Google Cloud addresses this by developing connectors, such as Cortex.

The Big Quote: “We are coming to the Third Age in data, which is going to divide data systems. It’s not just about having lots of one data type… it’s having the broadest possible set of data signals you can bring together. That idea of wide data systems means combining all of your data signals, structured and unstructured, into one unified system."

  continue reading

455 episoder

Artwork
iconDel
 
Manage episode 439130292 series 2536260
Innhold levert av Bob Evans. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Bob Evans eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Google Cloud Data Innovations

The Big Themes:

  • Integration of unstructured data with AI: Google Cloud is shifting how enterprises leverage their data by integrating unstructured data (which makes up 85-90% of all data) with structured data through its BigQuery multimodal data foundation. This integration allows for a more comprehensive data landscape where AI models can seamlessly access and analyze both types of data. This approach addresses the limitations of traditional data systems and unlocks new potential for AI-driven analytics.
  • The role of partners in maximizing AI and data value: Google Cloud’s service partners implement solutions and bring industry best practices to customer environments, while independent software vendors (ISVs) build applications that leverage Google Cloud’s data and AI tools. Programs like the Google Cloud Ready (GCR) initiative streamline integrations.
  • Integration challenge: The challenge for organizations lies in connecting disparate data sources, such as operational data from systems like SAP and CRM data from Salesforce, with analytics tools to enable real-time decision-making. Google Cloud addresses this by developing connectors, such as Cortex.

The Big Quote: “We are coming to the Third Age in data, which is going to divide data systems. It’s not just about having lots of one data type… it’s having the broadest possible set of data signals you can bring together. That idea of wide data systems means combining all of your data signals, structured and unstructured, into one unified system."

  continue reading

455 episoder

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