Data Analytics with Google Cloud Platform: Build Real Time Data Analytics on Google Cloud Platform by Murari Ramuka
BPB Publications | December 14, 2019 | English | ISBN: 9389423635 | True PDF | 267 pages | 14 MB
BPB Publications | December 14, 2019 | English | ISBN: 9389423635 | True PDF | 267 pages | 14 MB
Modern 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.
What will you learn
By 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 for
This 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.
● 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.
● 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.