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Big Data Architect's Handbook: A guide to building proficiency in tools and systems used by leading big data experts, Paperback by Akhtar, Syed Muhammad Fahad (Used)

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$53.80

Paperback
Used: Like New
9781788835824
1788835824

Publication Date: 2018-06-21
Publisher: Packt Publishing
Paperback : 486 pages
Author: Akhtar, Syed Muhammad Fahad
ISBN-10: 1788835824
ISBN-13: 9781788835824

Product Description A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial Intelligence Key Features Learn to build and run a big data application with sample code Explore examples to implement activities that a big data architect performs Use Machine Learning and AI for structured and unstructured data Book Description The big data architects are the “masters” of data, and hold high value in today's market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect's Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action. What you will learn Learn Hadoop Ecosystem and Apache projects Understand, compare NoSQL database and essential software architecture Cloud infrastructure design considerations for big data Explore application scenario of big data tools for daily activities Learn to analyze and visualize results to uncover valuable insights Build and run a big data application with sample code from end to end Apply Machine Learning and AI to perform big data intelligence Practice the daily activities performed by big data architects Who This Book Is For Big Data Architect's Handbook is for you if you are an aspiring data professional, developer, or IT enthusiast who aims to be an all-round architect in big data. This book is your one-stop solution to enhance your knowledge and carry out easy to complex activities required to become a big data architect. Table of Contents Why Big Data Big Data Environment Setup Hadoop Ecosystem NoSQL Database Off-the-Shelf Tools Containerization Network Infrastructure Cloud Infrastructure Security & Monitoring Front End Architecture Back End Architecture Machine Learning Artificial Intelligence ElasticSearch Structured Data UnStructured Data Data Visualization Financial Trading system Retail Recommendation System About the Author Fahad Akhtar is having more than 10 years of industrial experience of analysis, designing, developing, integrating and managing large applications in different and diverse industries. He has vast exposure of working in UAE and Pakistan. He is currently working in Abu Dhabi Islamic Bank as Solution Architect. He received his MBA degree from Torrens University, Australia and Bachelor of Science in Computer Engineering from the National University of Computer and Emerging Sciences, Pakistan. He is having Professional Skills in IBM, Cloudera, Hortonworks Big data, Hadoop, Spark, Kafka, HBase, Hive, Sqoop, Flume and NoSQL. He successfully completed many projects. One of them is Archiving Emails with Predictions for 50+ Terabyte of emails. It makes them available for search and apply machine learning algorithms to collect many useful predictions and insight. He is currently working on Call Center Predict Customer Engagement. It uses the recorded audio files and speech to text algorithm to apply machine learning and predict customer engagements with the operator. He has cross-platform expertise and achieves recognition from IBM, Sun Microsystems and Microsoft. He received in 2017 -I


Books >> Subjects >> Computers & Technology >> Databases & Big Data >> Data Modeling & Design