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Streaming change data capture : a foundation for modern data architectures /
There are many benefits to becoming a data-driven organization, including the ability to accelerate and improve business decision accuracy through the real-time processing of transactions, social media streams, and IoT data. But those benefits require significant changes to your infrastructure. You...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media,
[2018]
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| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Petrie, Kevin, |e author. | |
| 245 | 1 | 0 | |a Streaming change data capture : |b a foundation for modern data architectures / |c Kevin Petrie, Dan Potter, and Itamar Ankorion. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, |c [2018] | |
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| 520 | |a There are many benefits to becoming a data-driven organization, including the ability to accelerate and improve business decision accuracy through the real-time processing of transactions, social media streams, and IoT data. But those benefits require significant changes to your infrastructure. You need flexible architectures that can copy data to analytics platforms at near-zero latency while maintaining 100% production uptime. Fortunately, a solution already exists. This ebook demonstrates how change data capture (CDC) can meet the scalability, efficiency, real-time, and zero-impact requirements of modern data architectures. Kevin Petrie, Itamar Ankorion, and Dan Potter--technology marketing leaders at Attunity--explain how CDC enables faster and more accurate decisions based on current data and reduces or eliminates full reloads that disrupt production and efficiency. The book examines: How CDC evolved from a niche feature of database replication software to a critical data architecture building block Architectures where data workflow and analysis take place, and their integration points with CDC How CDC identifies and captures source data updates to assist high-speed replication to one or more targets Case studies on cloud-based streaming and streaming to a data lake and related architectures Guiding principles for effectively implementing CDC in cloud, data lake, and streaming environments The Attunity Replicate platform for efficiently loading data across all major database, data warehouse, cloud, streaming, and Hadoop platforms. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Computer architecture. | |
| 650 | 0 | |a Software architecture. | |
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| 650 | 0 | |a Big data. | |
| 650 | 6 | |a Ordinateurs |x Architecture. | |
| 650 | 6 | |a Architecture logicielle. | |
| 650 | 6 | |a Génie logiciel. | |
| 650 | 6 | |a Données volumineuses. | |
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| 650 | 7 | |a Computer architecture. |2 fast |0 (OCoLC)fst00872026 | |
| 650 | 7 | |a Electronic data processing. |2 fast |0 (OCoLC)fst00906956 | |
| 650 | 7 | |a Software architecture. |2 fast |0 (OCoLC)fst01200416 | |
| 650 | 7 | |a Software engineering. |2 fast |0 (OCoLC)fst01124185 | |
| 700 | 1 | |a Potter, Dan, |e author. | |
| 700 | 1 | |a Ankorion, Itamar, |e author. | |
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