April 2025
Intermediate to advanced
374 pages
11h 18m
Spanish
Content preview from Patrones de diseño de ingeniería de datos
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Capítulo 10. Patrones de diseño de la observabilidad de los datos
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Los patrones de diseño de calidad de datos del capítulo anterior son cruciales para garantizar la relevancia de tus conjuntos de datos. Sin embargo, como se centran principalmente en los propios datos, confiar sólo en las soluciones de calidad de datos no será suficiente para que tengas un control integral de tu pila de ingeniería de datos.
Veamos un ejemplo para entenderlo mejor. El patrón Auditoría-Escritura-Auditoría-Publicación (AWAP) es un gran mecanismo de protección contra el procesamiento de datos de mala calidad. Por desgracia, aunque tu trabajo AWAP detecte perfectamente todos los problemas, puedes tener problemas. Un ejemplo de esto ocurre cuando tu trabajo AWAP no se ejecuta debido a una interrupción del flujo ascendente y no eres consciente de ello.
Sin embargo, hay buenas noticias: los patrones de diseño de observabilidad de datos de este capítulo llenan las lagunas dejadas por sus homólogos de calidad de datos, añadiendo al sistema capacidades de monitoreo y alerta. Para abordar estos problemas adicionales, las soluciones de los patrones de observabilidad se basan en dos pilares: la detección y el seguimiento.
Los patrones de diseño de detección detectan cualquier problema relacionado con los datos o el tiempo. Serían grandes candidatos para manejar el problema de interrupción del flujo ...
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