Shakuntala Gupta Edward – författare

The "one-size-fits-all" thinking regarding traditional RDBMSs has been challenged in the last few years by the emergence of diversified NoSQL databases. More than 120 NoSQL databases are now available in the market, and the market leader by far is MongoDB. With so many companies opting for MongoDB as their NoSQL database of choice, there''s a need for a practical how-to combined with expert advice for getting the most out of the software.

Beginning with a short introduction to the basics of NoSQL databases, MongoDB experts Navin Sabharwal and Shankatala Gupta Edward introduce readers to MongoDB – the leading document based NoSQL database, acquainting them step by step with all aspects of MongoDB. They cover the data model, underlying architecture, how to code using Mongo Shell, and administration of the MongoDB platform, among other topics. The book also provides clear guidelines and practical examples for architecting and developing applications using the MongoDB platform and deploying them. Database developers, architects, and database administrators will find useful information covering all aspects of the MongoDB platform and how to put it to use practically.

Practical Guide to MongoDB provides readers with:

A solid understanding of NoSQL databasesAn understanding of how to get started with MongoDBMethodical coverage of the architecture, development, and administration of MongoDBA plethora of "How to’s" enabling you to use the technology most efficiently to solve the problems you face

Practical MongoDB is for those just starting to learning to work with NoSQL databases in general and MongoDB in particular. Skills in these areas are in demand, making this book essential reading for those who want to work more productively or break into big data work. It will prove equally useful for entrepreneurs and others who like to work with new technologies.

The "one-size-fits-all" thinking regarding traditional RDBMSs has been challenged in the last few years by the emergence of diversified NoSQL databases. More than 120 NoSQL databases are now available in the market, and the market leader by far is MongoDB. With so many companies opting for MongoDB as their NoSQL database of choice, there's a need for a practical how-to combined with expert advice for getting the most out of the software. Beginning with a short introduction to the basics of NoSQL databases, MongoDB experts Navin Sabharwal and Shankatala Gupta Edward introduce readers to MongoDB – the leading document based NoSQL database, acquainting them step by step with all aspects of MongoDB. They cover the data model, underlying architecture, how to code using Mongo Shell, and administration of the MongoDB platform, among other topics. The book also provides clear guidelines and practical examples for architecting and developing applications using the MongoDB platform and deploying them. Database developers, architects, and database administrators will find useful information covering all aspects of the MongoDB platform and how to put it to use practically.Practical Guide to MongoDB provides readers with:A solid understanding of NoSQL databasesAn understanding of how to get started with MongoDBMethodical coverage of the architecture, development, and administration of MongoDBA plethora of "How to’s" enabling you to use the technology most efficiently to solve the problems you facePractical MongoDB is for those just starting to learning to work with NoSQL databases in general and MongoDB in particular. Skills in these areas are in demand, making this book essential reading for those who want to work more productively or break into big data work. It will prove equally useful for entrepreneurs and others who like to work with new technologies.

Discover the methodologies and best practices for getting started with Google Cloud Platform relational services – CloudSQL and CloudSpanner.The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud.  You'll then take an in-depth hands on journey into Google CloudSQL and CloudSpanner, including choosing the right platform for your application needs, planning, provisioning, designing and developing your application. Sample applications are given that use Python to connect to CloudSQL and CloudSpanner, along with helpful features provided by the engines. You''ll also implement practical best practices in the last chapter. Hands On Google Cloud SQL and Cloud Spanner is a great starting point to apply GCP data offerings in your technology stack and the code used allows you to try out the examples and extend them in interestingways.What You'll LearnGet started with Big Data technologies on the Google Cloud Platform Review CloudSQL and Cloud Spanner  from basics to administrationApply best practices and use Google’s CloudSQL and CloudSpanner offeringWork with code in Python notebooks and scriptsWho This Book Is ForApplication architects, database architects, software developers, data engineers, cloud architects.

Discover the methodologies and best practices for getting started with Google Cloud Platform relational services – CloudSQL and CloudSpanner.The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud.  You''ll then take an in-depth hands on journey into Google CloudSQL and CloudSpanner, including choosing the right platform for your application needs, planning, provisioning, designing and developing your application. Sample applications are given that use Python to connect to CloudSQL and CloudSpanner, along with helpful features provided by the engines. You''''ll also implement practical best practices in the last chapter. Hands On Google Cloud SQL and Cloud Spanner is a great starting point to apply GCP data offerings in your technology stack and the code used allows you to try out the examples and extend them in interestingways.What You''ll LearnGet started with Big Data technologies on the Google Cloud Platform Review CloudSQL and Cloud Spanner  from basics to administrationApply best practices and use Google’s CloudSQL and CloudSpanner offeringWork with code in Python notebooks and scriptsWho This Book Is ForApplication architects, database architects, software developers, data engineers, cloud architects.

Generative AI and Agentic AI together are revolutionizing the technology landscape, with profound and far-reaching impacts across industries. Organizations are increasingly adopting these technologies to drive innovation, enhance unstructured content management, and improve problem-solving capabilities. With Agentic AI, enterprises are moving towards the development of intelligent systems that can plan, reason, and act with autonomy. While early proof-of-concepts (POCs) demonstrated the potential of these technologies, the current shift is toward responsible and scalable production implementations that leverage both generative and agentic capabilities.This book begins by guiding you through the technological evolution of AI, from early machine learning to today’s large language models (LLMs) and agentic systems. It then explores a wide range of use cases across industries, highlighting how LLMs can support decision-making, and how Agentic AI enables dynamic, collaborative systems that act with autonomy and intent. This is followed by Design Patterns across the lifecycle of AI solution development, deployment and monitoring. Readers will then gain insights into the methodologies for developing and deploying Generative and Agentic AI solutions at an enterprise level. A featured implementation demonstrates how Agentic AI can be effectively put into action.The book also introduces essential concepts such as MLOps, LLMOps, and Responsible AI principles which are critical for transitioning the AI solutions from experimentation to production. These principles ensure that AI deployments are scalable, secure, ethical and compliant. The book concludes with key takeaways and best practices for developing, evaluating, deploying and scaling AI applications responsibly and effectively within enterprise settings.You Will:Understand key design patterns to develop, deploy and monitor a Generative AI solution effectively.Learn how to develop and implement a production-ready Agentic AI use case.Discover best practices for building scalable, secure, and enterprise-grade AI solutions.Understand how to assess and mitigate risks using Responsible AI principles and LLMOps best practices.This book is for : Enterprise Software Engineers and Architects