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| 001 | 979-8-8688-0029-0 | ||
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| 005 | 20251030110900.0 | ||
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| 008 | 231227s2024 xxu| s |||| 0|eng d | ||
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_a10.1007/979-8-8688-0029-0 _2doi |
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_aCOM091000 _2bisacsh |
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| 100 | 1 |
_aKumar, Anjani. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _968582 |
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| 245 | 1 | 0 |
_aArchitecting a Modern Data Warehouse for Large Enterprises _h[electronic resource] : _bBuild Multi-cloud Modern Distributed Data Warehouses with Azure and AWS / _cby Anjani Kumar, Abhishek Mishra, Sanjeev Kumar. |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aBerkeley, CA : _bApress : _bImprint: Apress, _c2024. |
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| 300 |
_aXV, 368 p. 146 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _aChapter 1: Introduction -- Chapter 2: Modern Data Warehouses -- Chapter 3: Data Lake, Lake House, and Delta Lake -- Chapter 4: Data Mesh -- Chapter 5: Data Orchestration Techniques -- Chapter 6: Data Democratization, Governance, and Security -- Chapter 7: Business Intelligence. | |
| 520 | _aDesign and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution. The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines. You will: Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehouses Gain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model’s performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications. | ||
| 650 | 0 |
_aCloud Computing. _958386 |
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| 650 | 0 | _aMicrosoft software. | |
| 650 | 0 | _aMicrosoft .NET Framework. | |
| 650 | 0 |
_aComputer networks . _960157 |
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| 650 | 1 | 4 |
_aCloud Computing. _958386 |
| 650 | 2 | 4 | _aMicrosoft. |
| 650 | 2 | 4 |
_aComputer Communication Networks. _965689 |
| 700 | 1 |
_aMishra, Abhishek. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _968583 |
|
| 700 | 1 |
_aKumar, Sanjeev. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _968584 |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9798868800283 |
| 776 | 0 | 8 |
_iPrinted edition: _z9798868800306 |
| 776 | 0 | 8 |
_iPrinted edition: _z9798868805929 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/979-8-8688-0029-0 |
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| 912 | _aZDB-2-SXPC | ||
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