| Titre : |
Database design and modeling with google cloud : learn database design and development to take your data to applications, analytics, and AI |
| Type de document : |
document électronique |
| Editeur : |
Birmingham : Packt Publishing |
| Année de publication : |
2023 |
| Importance : |
1 fichier PDF |
| Présentation : |
ill. |
| ISBN/ISSN/EAN : |
978-1-80461-786-1 |
| Note générale : |
Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Index |
| Mots-clés : |
Databases
Databese design
Cloud computing
Artificial intelligence |
| Index. décimale : |
004.65 Bases de données et leurs structures |
| Résumé : |
Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needsKey FeaturesFamiliarize yourself with business and technical considerations involved in modeling the right databaseTake your data to applications, analytics, and AI with real-world examplesLearn how to code, build, and deploy end-to-end solutions with expert advicePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you'll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You'll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learnUnderstand different use cases and real-world applications of data in the cloudWork with document and indexed NoSQL databasesGet to grips with modeling considerations for analytics, AI, and MLUse real-world examples to learn about ETL servicesDesign structured, semi-structured, and unstructured data for your applications and analyticsImprove observability, performance, security, scalability, latency SLAs, SLIs, and SLOsWho this book is forThis book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data. |
| Note de contenu : |
Summary :
I. Database model: business and technical design considerations.
1. Data, databases, and design.
2. Handling data on the cloud.
II. Structured data.
3. Database modeling for structured data.
4. Setting up a fully managed RDBMS.
5. Designing an analytical data warehouse.
III. Semi-structured, unstructured data, and NoSQL design.
6. Designing for semi-structured data.
7. Unstructured data management.
IV. Devops and databases.
8. Devops and databases.
V. Data to AI.
9. Data to AI – modeling your databases for analytics and ML.
10. Looking ahead – designing for LLM applications. |
Database design and modeling with google cloud : learn database design and development to take your data to applications, analytics, and AI [document électronique] . - Birmingham : Packt Publishing, 2023 . - 1 fichier PDF : ill. ISBN : 978-1-80461-786-1 Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Index
| Mots-clés : |
Databases
Databese design
Cloud computing
Artificial intelligence |
| Index. décimale : |
004.65 Bases de données et leurs structures |
| Résumé : |
Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needsKey FeaturesFamiliarize yourself with business and technical considerations involved in modeling the right databaseTake your data to applications, analytics, and AI with real-world examplesLearn how to code, build, and deploy end-to-end solutions with expert advicePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you'll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You'll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learnUnderstand different use cases and real-world applications of data in the cloudWork with document and indexed NoSQL databasesGet to grips with modeling considerations for analytics, AI, and MLUse real-world examples to learn about ETL servicesDesign structured, semi-structured, and unstructured data for your applications and analyticsImprove observability, performance, security, scalability, latency SLAs, SLIs, and SLOsWho this book is forThis book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data. |
| Note de contenu : |
Summary :
I. Database model: business and technical design considerations.
1. Data, databases, and design.
2. Handling data on the cloud.
II. Structured data.
3. Database modeling for structured data.
4. Setting up a fully managed RDBMS.
5. Designing an analytical data warehouse.
III. Semi-structured, unstructured data, and NoSQL design.
6. Designing for semi-structured data.
7. Unstructured data management.
IV. Devops and databases.
8. Devops and databases.
V. Data to AI.
9. Data to AI – modeling your databases for analytics and ML.
10. Looking ahead – designing for LLM applications. |
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004 Informatique. Science et technologie de l'informatique
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Database design and modeling with google cloud (2023)
