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Cloud Analytics With Google Cloud Platform

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Cloud Analytics With Google Cloud Platform

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Author : Sanket Thodge
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-04-10

Cloud Analytics With Google Cloud Platform written by Sanket Thodge 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 2018-04-10 with Computers categories.

Combine the power of analytics and cloud computing for faster and efficient insights Key Features Master the concept of analytics on the cloud: and how organizations are using it Learn the design considerations and while applying a cloud analytics solution Design an end-to-end analytics pipeline on the cloud Book Description With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation What you will learn Explore the basics of cloud analytics and the major cloud solutions Learn how organizations are using cloud analytics to improve the ROI Explore the design considerations while adopting cloud services Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub Process your data with tools such as Cloud Dataproc, BigQuery, etc Over 70 GCP tools to build an analytics engine for cloud analytics Implement machine learning and other AI techniques on GCP Who this book is for This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory.

Data Analytics With Google Cloud Platform

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Author : Murari Ramuka
language : en
Publisher: BPB Publications
Release Date : 2019-12-16

Data Analytics With Google Cloud Platform written by Murari Ramuka and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Computers categories.

Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services Key Featuresa- Learn the basic concept of Cloud Computing along with different Cloud service provides with their supported Models (IaaS/PaaS/SaaS)a- Learn the basics of Compute Engine, App Engine, Container Engine, Project and Billing setup in the Google Cloud Platforma- Learn how and when to use Cloud DataFlow, Cloud DataProc and Cloud DataPrep a- Build real-time data pipeline to support real-time analytics using Pub/Sub messaging servicea- Setting up a fully managed GCP Big Data Cluster using Cloud DataProc for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient mannera- Learn how to use Cloud Data Studio for visualizing the data on top of Big Querya- Implement and understand real-world business scenarios for Machine Learning, Data Pipeline EngineeringDescriptionModern businesses are awash with data, making data driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with enough knowledge of Cloud Computing in conjunction with Google Cloud Data platform to succeed in the role of a Cloud data expert.Current market is trending towards the latest cloud technologies, which is the need of the hour. Google being the pioneer, is dominating this space with the right set of cloud services being offered as part of GCP (Google Cloud Platform). At this juncture, this book will be very vital and will be cover all the services that are being offered by GCP, putting emphasis on Data services.What will you learnBy the end of the book, you will have come across different data services and platforms offered by Google Cloud, and how those services/features can be enabled to serve business needs. You will also see a few case studies to put your knowledge to practice and solve business problems such as building a real-time streaming pipeline engine, Scalable Datawarehouse on Cloud, fully managed Hadoop cluster on Cloud and enabling TensorFlow/Machine Learning API's to support real-life business problems. Remember to practice additional examples to master these techniques. Who this book is forThis book is for professionals as well as graduates who want to build a career in Google Cloud data analytics technologies. One stop shop for those who wish to get an initial to advance understanding of the GCP data platform. The target audience will be data engineers/professionals who are new, as well as those who are acquainted with the tools and techniques related to cloud and data space. a- Individuals who have basic data understanding (i.e. Data and cloud) and have done some work in the field of data analytics, can refer/use this book to master their knowledge/understanding.a- The highlight of this book is that it will start with the basic cloud computing fundamentals and will move on to cover the advance concepts on GCP cloud data analytics and hence can be referred across multiple different levels of audiences. Table of Contents1. GCP Overview and Architecture2. Data Storage in GCP 3. Data Processing in GCP with Pub/Sub and Dataflow 4. Data Processing in GCP with DataPrep and Dataflow5. Big Query and Data Studio6. Machine Learning with GCP7. Sample Use cases and ExamplesAbout the Author Murari Ramuka is a seasoned Data Analytics professional with 12+ years of experience in enabling data analytics platforms using traditional DW/BI and Cloud Technologies (Azure, Google Cloud Platform) to uncover hidden insights and maximize revenue, profitability and ensure efficient operations management. He has worked with several multinational IT giants like Capgemini, Cognizant, Syntel and Icertis.His LinkedIn Profile: https://www.linkedin.com/in/murari-ramuka-98a440a/

Cloud Analytics With Google Cloud Platform

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Author : Sanket Thodge
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-04-10

Data Engineering With Google Cloud Platform

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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-31

Data Engineering With Google Cloud Platform written by Adi Wijaya 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 2022-03-31 with Computers categories.

Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.

Data Science On Google Cloud Platform Exploratory Data Analytics

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Author :
language : en
Publisher:
Release Date : 2018

Data Science On Google Cloud Platform Exploratory Data Analytics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

Learn how to conduct exploratory data analytics on Google Cloud Platform.

Big Data Analytics

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Author : Ümit Demirbaga
language : en
Publisher: Springer Nature
Release Date : 2024-05-07

Big Data Analytics written by Ümit Demirbaga and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-07 with Computers categories.

This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics working environments in the first two chapters. The third chapter provides comprehensive information on big data processing systems - from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of big data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of big data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending machine learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for big data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their big data analytics skills using various big data analytics frameworks. The book will be of interest to business executives and IT managers as well as university students and their course leaders, in fact all those who want to get involved in the big data world.

Google Bigquery Analytics

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Author : Jordan Tigani
language : en
Publisher: John Wiley & Sons
Release Date : 2014-05-21

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 2014-05-21 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

Big Data Analytics With Applications In Insider Threat Detection

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Author : Bhavani Thuraisingham
language : en
Publisher: CRC Press
Release Date : 2017-11-22

Big Data Analytics With Applications In Insider Threat Detection written by Bhavani Thuraisingham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Computers categories.

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Architecting Data And Machine Learning Platforms

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Author : Marco Tranquillin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-10-12

Architecting Data And Machine Learning Platforms written by Marco Tranquillin 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 2023-10-12 with Computers categories.

All cloud architects need to know how to build data platforms that enable businesses to make data-driven decisions and deliver enterprise-wide intelligence in a fast and efficient way. This handbook shows you how to design, build, and modernize cloud native data and machine learning platforms using AWS, Azure, Google Cloud, and multicloud tools like Snowflake and Databricks. Authors Marco Tranquillin, Valliappa Lakshmanan, and Firat Tekiner cover the entire data lifecycle from ingestion to activation in a cloud environment using real-world enterprise architectures. You'll learn how to transform, secure, and modernize familiar solutions like data warehouses and data lakes, and you'll be able to leverage recent AI/ML patterns to get accurate and quicker insights to drive competitive advantage. You'll learn how to: Design a modern and secure cloud native or hybrid data analytics and machine learning platform Accelerate data-led innovation by consolidating enterprise data in a governed, scalable, and resilient data platform Democratize access to enterprise data and govern how business teams extract insights and build AI/ML capabilities Enable your business to make decisions in real time using streaming pipelines Build an MLOps platform to move to a predictive and prescriptive analytics approach

Intelligent Analytics For Industry 4 0 Applications

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Author : Avinash Chandra Pandey
language : en
Publisher: CRC Press
Release Date : 2023-06-06

Intelligent Analytics For Industry 4 0 Applications written by Avinash Chandra Pandey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Business & Economics categories.

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

Cloud Analytics With Google Cloud Platform

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