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The Google Cloud Data Stack


The Google Cloud Data Stack
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The Google Cloud Data Stack


The Google Cloud Data Stack
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Author : Dwayne Daniel
language : en
Publisher: Independently Published
Release Date : 2025-09-30

The Google Cloud Data Stack written by Dwayne Daniel and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.


The data challenges of today demand more than traditional databases and ETL scripts. Businesses need platforms that can scale effortlessly, handle both real-time and historical data, and reduce the complexity of managing infrastructure. Google Cloud offers this through its serverless data stack, and this book shows you exactly how to use it. The Google Cloud Data Stack: A Project-Based Guide to Dataflow and BigQuery, Architecting Scalable and Serverless Data Solutions is a hands-on guide for engineers, architects, and analysts who want to master Google Cloud's modern data ecosystem. With a practical, project-based approach, it walks you through building robust data pipelines, architecting data lakehouse solutions, and running advanced analytics with confidence. Whether your focus is on streaming IoT events, large-scale batch processing, or predictive analytics, you'll learn how to design solutions that scale without the operational burden of traditional systems. What sets this book apart is its structured, progressive coverage of the Google Cloud data stack. You'll begin with the foundations, learning how to set up projects, configure IAM, and navigate the Cloud Console and Cloud Shell. From there, you'll move into building pipelines with Dataflow-covering the Apache Beam programming model, batch and streaming use cases, and ETL orchestration with templates. BigQuery is explored in depth, with chapters dedicated to architecture, data loading, querying at scale, and advanced features such as BigQuery ML for machine learning and BigQuery GIS for geospatial analytics. The book also dives into integrating Dataflow and BigQuery, applying best practices for schema evolution, and designing hybrid workflows that combine batch and streaming. Later chapters guide you through optimization strategies for cost and performance, real-time analytics with Pub/Sub, and security and governance essentials. Finally, a full case study brings everything together with an end-to-end solution, supported by extended code snippets and deployment templates in the appendix. If you've been asking yourself how to build data platforms that grow with your business, how to make streaming and batch pipelines work together, or how to use BigQuery beyond basic SQL for predictive and geospatial analytics, this book provides the answers. Take the next step toward mastering serverless data engineering. Equip yourself with the knowledge, examples, and patterns you need to architect data solutions on Google Cloud that are not only powerful but sustainable. Purchase your copy today and start building systems designed for scale, performance, and the future of data.



Data Science On The Google Cloud Platform


Data Science On The Google Cloud Platform
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Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-12-12

Data Science On The Google Cloud Platform written by Valliappa Lakshmanan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-12 with Computers categories.


Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines



Ai Based Data Analytics


Ai Based Data Analytics
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Author : Kiran Chaudhary
language : en
Publisher: CRC Press
Release Date : 2023-12-29

Ai Based Data Analytics written by Kiran Chaudhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.


This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviour AI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.



Fundamentals Of Data Engineering


Fundamentals Of Data Engineering
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Author : Joe Reis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-22

Fundamentals Of Data Engineering written by Joe Reis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Computers categories.


"Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle." - from Publisher.



The Datapreneurs


The Datapreneurs
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Author : Bob Muglia
language : en
Publisher: Simon and Schuster
Release Date : 2023-06-13

The Datapreneurs written by Bob Muglia and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-13 with Computers categories.


A leader in the data economy explains how we arrived at AI—and how we can navigate its future In The Datapreneurs, Bob Muglia helps us understand how innovation in data and information technology have led us to AI—and how this technology must shape our future. The long-time Microsoft executive, former CEO of Snowflake, and current tech investor maps the evolution of the modern data stack and how it has helped build today’s economy and society. And he explains how humanity must create a new social contract for the artificial general intelligence (AGI)—autonomous machines intelligent as people—that he expects to arrive in less than a decade. Muglia details his personal experience in the foundational years of computing and data analytics, including with Bill Gates and Sam Altman, the CEO of OpenAI, the creator of ChatGPT, and others that are not household names—yet. He builds upon Isaac Asimov’s Laws of Robotics to explore the moral, ethical, and legal implications of today’s smart machines, and how a combination of human and machine intelligence could create an era of progress and prosperity where all the people on Earth can have what they need and want without destroying our natural environment. The Datapreneurs is a call to action. AGI is surely coming. Muglia believes that tech business leaders, ethicists, policy leaders, and even the general public must collaborate answer the short- and long-term questions raised by its emergence. And he argues that we had better get going, because advances are coming so fast that society risks getting caught flatfooted—with potentially disastrous consequences.



Unlocking Retail Success Leveraging Analytics Stack Solutions For Data Driven Decision Making And Competitive Edge


Unlocking Retail Success Leveraging Analytics Stack Solutions For Data Driven Decision Making And Competitive Edge
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Author : Olalekan Olaniru
language : en
Publisher: GRIN Verlag
Release Date : 2024-01-15

Unlocking Retail Success Leveraging Analytics Stack Solutions For Data Driven Decision Making And Competitive Edge written by Olalekan Olaniru and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-15 with Computers categories.


Seminar paper from the year 2023 in the subject Computer Science - Commercial Information Technology, grade: 2,0, (International University of Applied Sciences), course: Analytical Software & Framework, language: English, abstract: This study focused on how an analytics stack solution can help a traditional retail company leverage the massive amount of data generated by various sales channels to improve its decision-making, productivity, and competitiveness. The analytics stack solution enables real-time tracking and analysis of customer behavior, sales performance, and market trends across physical stores, e-commerce, wholesale, and other channels. The study also examines the best deployment option (on-premise or cloud) for the analytics stack solution, considering the data type, volume, security, privacy, flexibility, and scaling factors. Furthermore, the study discusses the change management issues, essential components of a retail analytics stack and recommendations for adoption.



Google Cloud Certified Professional Cloud Architect All In One Exam Guide


Google Cloud Certified Professional Cloud Architect All In One Exam Guide
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Author : Iman Ghanizada
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-02-19

Google Cloud Certified Professional Cloud Architect All In One Exam Guide written by Iman Ghanizada and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-19 with Computers categories.


Everything you need to succeed on the Google Cloud Certified Professional Cloud Architect exam in one accessible study guide Take the challenging Google Cloud Certified Professional Cloud Architect exam with confidence using the comprehensive information contained in this invaluable self-study guide. The book provides a thorough overview of cloud architecture and Google Cloud Platform (GCP) and shows you how to pass the test. Beyond exam preparation, the guide also serves as a valuable on-the-job reference. Written by a recognized expert in the field, Google Cloud Certified Professional Cloud Architect All-In-One Exam Guide is based on proven pedagogy and features special elements that teach and reinforce practical skills. The book contains accurate practice questions and in-depth explanations. You will discover how to design, develop, and manage robust, secure, scalable, and highly available solutions to drive business objectives. Offers 100% coverage of every objective for the Google Cloud Certified Professional Cloud Architect exam Online content includes 100 additional practice questions in the TotalTester customizable exam engine Written by a Google Cloud Certified Professional Cloud Architect



Google Bigquery Analytics


Google Bigquery Analytics
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Author : Jordan Tigani
language : en
Publisher: John Wiley & Sons
Release Date : 2014-06-09

Google Bigquery Analytics written by Jordan Tigani and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-09 with Computers categories.


How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addition to the mechanics of BigQuery, the book also covers the architecture of the underlying Dremel query engine, providing a thorough understanding that leads to better query results. Features a companion website that includes all code and data sets from the book Uses real-world examples to explain everything analysts need to know to effectively use BigQuery Includes web application examples coded in Python



Fundamentals Of Analytics Engineering


Fundamentals Of Analytics Engineering
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Author : Dumky De Wilde
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29

Fundamentals Of Analytics Engineering written by Dumky De Wilde and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.


Gain a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering Key Features Discover how analytics engineering aligns with your organization's data strategy Access insights shared by a team of seven industry experts Tackle common analytics engineering problems faced by modern businesses Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer. After conquering data ingestion and techniques for data quality and scalability, you’ll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You’ll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You’ll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance. By the end of this book, you’ll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.What you will learn Design and implement data pipelines from ingestion to serving data Explore best practices for data modeling and schema design Scale data processing with cloud based analytics platforms and tools Understand the principles of data quality management and data governance Streamline code base with best practices like collaborative coding, version control, reviews and standards Automate and orchestrate data pipelines Drive business adoption with effective scoping and prioritization of analytics use cases Who this book is for This book is for data engineers and data analysts considering pivoting their careers into analytics engineering. Analytics engineers who want to upskill and search for gaps in their knowledge will also find this book helpful, as will other data professionals who want to understand the value of analytics engineering in their organization's journey toward data maturity. To get the most out of this book, you should have a basic understanding of data analysis and engineering concepts such as data cleaning, visualization, ETL and data warehousing.



Building Machine Learning And Deep Learning Models On Google Cloud Platform


Building Machine Learning And Deep Learning Models On Google Cloud Platform
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Author : Ekaba Bisong
language : en
Publisher: Apress
Release Date : 2019-09-27

Building Machine Learning And Deep Learning Models On Google Cloud Platform written by Ekaba Bisong and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.


Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is dividedinto eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your results Know the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers