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Auteur Sagar LAD |
Documents disponibles écrits par cet auteur (2)
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Hands-On Azure Data Platform : Building Scalable Enterprise-Grade Relational and Non-Relational database Systems with Azure Data Services / Sagar LAD / BPB Publications (2022)
Titre : Hands-On Azure Data Platform : Building Scalable Enterprise-Grade Relational and Non-Relational database Systems with Azure Data Services Type de document : e-book Auteurs : Sagar LAD Editeur : BPB Publications Année de publication : 2022 ISBN/ISSN/EAN : 9789355510303 Note générale : copyrighted Langues : Anglais (eng) Résumé : Plan, build, deploy, and monitor data solutions on Azure Key Features Work with PostgreSQL, MySQL, and CosmosDB databases on Microsoft Azure. Work with whole data architecture, leverage Azure Storage, Azure Synapse, and Azure Data Lake. Data integration strategies with Azure Data Factory and Data Bricks. Description 'Hands-On Azure Data Platform' helps readers get a fundamental understanding of the Database, Data Warehouse, and Data Lake and their management on the Azure Data Platform. The book describes how to work efficiently with Relational and Non-Relational Databases, Azure Synapse Analytics, and Azure Data Lake. The readers will use Azure Databricks and Azure Data Factory to experience data processing and transformation. The book delves deeply into topics like continuous integration, continuous delivery, and the use of Azure DevOps. The book focuses on the integration of Azure DevOps with CI/CD pipelines for data ops solutions. The book teaches readers how to migrate data from an on-premises system or another cloud service provider to Azure. After reading the book, readers will develop end-to-end data solutions using the Azure data platform. Additionally, data engineers and ETL developers can streamline their ETL operations using various efficient Azure services. What you will learn In-depth knowledge of the principles of the data warehouse and the data lake. Acquaint yourself with Azure Storage Files, Blobs, and Queues. Create relational databases on the Azure platform using SQL, PostgreSQL, and MySQL. With Cosmos DB, you can create extremely scalable databases and data warehouses. Utilize Azure Databricks and Data Factory to develop data integration solutions. Who this book is for This book is designed for big data engineers, data architects, and cloud engineers who want to understand how to use the Azure Data Platform to build enterprise-grade solutions. Learning about databases and the Azure Data Platform would be helpful but not necessary. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88937932 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=572784 Mastering Databricks Lakehouse Platform : Perform Data Warehousing, Data Engineering, Machine Learning, DevOps, and BI into a Single Platform (English Edition) / Sagar LAD / BPB Publications (2022)
Titre : Mastering Databricks Lakehouse Platform : Perform Data Warehousing, Data Engineering, Machine Learning, DevOps, and BI into a Single Platform (English Edition) Type de document : e-book Auteurs : Sagar LAD Editeur : BPB Publications Année de publication : 2022 ISBN/ISSN/EAN : 9789355511393 Note générale : copyrighted Langues : Anglais (eng) Résumé : Enable data and AI workloads with absolute security and scalabilityKey Features? Detailed, step-by-step instructions for every data professional starting a career with data engineering.? Access to DevOps, Machine Learning, and Analytics wirthin a single unified platform.? Includes design considerations and security best practices for efficient utilization of Databricks platform.DescriptionStarting with the fundamentals of the databricks lakehouse platform, the book teaches readers on administering various data operations, including Machine Learning, DevOps, Data Warehousing, and BI on the single platform.The subsequent chapters discuss working around data pipelines utilizing the databricks lakehouse platform with data processing and audit quality framework. The book teaches to leverage the Databricks Lakehouse platform to develop delta live tables, streamline ETL/ELT operations, and administer data sharing and orchestration. The book explores how to schedule and manage jobs through the Databricks notebook UI and the Jobs API. The book discusses how to implement DevOps methods on the Databricks Lakehouse platform for data and AI workloads. The book helps readers prepare and process data and standardizes the entire ML lifecycle, right from experimentation to production.The book doesn't just stop here; instead, it teaches how to directly query data lake with your favourite BI tools like Power BI, Tableau, or Qlik. Some of the best industry practices on building data engineering solutions are also demonstrated towards the end of the book.What you will learn? Acquire capabilities to administer end-to-end Databricks Lakehouse Platform.? Utilize Flow to deploy and monitor machine learning solutions.? Gain practical experience with SQL Analytics and connect Tableau, Power BI, and Qlik.? Configure clusters and automate CI/CD deployment.? Learn how to use Airflow, Data Factory, Delta Live Tables, Databricks notebook UI, and the Jobs API.Who this book is forThis book is for every data professional, including data engineers, ETL developers, DB administrators, Data Scientists, SQL Developers, and BI specialists. You don't need any prior expertise with this platform because the book covers all the basics.Table of Contents1. Getting started with Databricks Platform2. Management of Databricks Platform3. Spark, Databricks, and Building a Data Quality Framework4. Data Sharing and Orchestration with Databricks5. Simplified ETL with Delta Live Tables6. SCD Type 2 Implementation with Delta Lake7. Machine Learning Model Management with Databricks8. Continuous Integration and Delivery with Databricks9. Visualization with Databricks10. Best Security and Compliance Practices of Databricks Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88937983 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=572869
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