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Spotlight on Learning from Failure : Creating Better Data Pipelines with Natalino Busa /
When considering the complexities of implementing a next-generation data pipeline, the risk of over-promising and under-delivering is incredibly high due to the overwhelming expectations placed on predictive analytics today. It's critical to look at a number of factors-like your company's...
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| Formato: | Electrónico Video |
| Idioma: | Inglés |
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O'Reilly Media, Inc.,
2019.
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| Edición: | 1st edition. |
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| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | When considering the complexities of implementing a next-generation data pipeline, the risk of over-promising and under-delivering is incredibly high due to the overwhelming expectations placed on predictive analytics today. It's critical to look at a number of factors-like your company's culture and the historic promise gap between ETL (extract, transform, load) in the 1970s and AI (artificial intelligence) in the 2010s-to overcome the challenges and succeed. Natalino Busa discusses how to bust the myths, deconstruct the false assumptions, and avoid common pitfalls in order to build and deliver successful data pipelines that deliver real value to your organization. Recorded on February 26, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O'Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts' unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Learning from Failure, you'll discover the lessons learned from failures both large and small. You'll discover how successful companies have addressed setbacks, missteps, and challenges and how you can grow from their examples. |
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| Descripción Física: | 1 online resource (1 video file, approximately 59 min.) |