Building Real Time Analytics Systems
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Building Real-Time Analytics Systems
Author: Mark Needham
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-09-14
Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly. Author Mark Needham from StarTree provides an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The book's second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service. You will: Learn common architectures for real-time analytics Discover how event processing differs from real-time analytics Ingest event data from Apache Kafka into Apache Pinot Combine event streams with OLTP data using Debezium and Kafka Streams Write real-time queries against event data stored in Apache Pinot Build a real-time dashboard and order tracking app Learn how Uber, Stripe, and Just Eat use real-time analytics
Real-Time Analytics
Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.
Data Leadership in the Age of AI: Building Intelligent, Scalable Analytics Systems 2025
Author: Author : 1-Rajesh Sura, Author : 2-Dr. Sudhanshu Maurya
language: en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date:
PREFACE In an era where data is becoming the cornerstone of innovation and business growth, the ability to leverage this resource effectively has never been more crucial. As artificial intelligence (AI) continues to evolve and influence nearly every facet of business, organizations face the challenge of not only managing vast amounts of data but also transforming that data into actionable insights that drive decision-making and strategic direction. In this context, data leadership has emerged as a critical skill for businesses, government organizations, and technology leaders alike. The role of data leaders, those who are responsible for guiding organizations through data-driven transformations—has shifted from overseeing data collection and management to fostering a culture of intelligence, scalability, and innovation through advanced analytics. This book, Data Leadership in the Age of AI: Building Intelligent, Scalable Analytics Systems, aims to explore the evolving landscape of data leadership, offering insights into how organizations can build and scale intelligent analytics systems that leverage AI to drive efficiency, innovation, and competitive advantage. The integration of AI into data analytics systems is not just about enhancing existing processes but about fundamentally changing how organizations process, analyze, and derive value from data. With AI technologies like machine learning, natural language processing, and deep learning becoming more accessible and integrated into everyday operations, organizations must learn to navigate this new terrain with a strategic approach to data leadership. Data leadership is a multifaceted discipline that goes beyond simply managing data. It involves creating a vision for how data should be utilized to generate value, building scalable architectures that can support massive volumes of data, and developing the organizational culture necessary to foster collaboration, creativity, and innovation. As companies seek to implement AI-powered analytics systems, they must confront the complexities of data governance, data privacy, ethical concerns, and technological integration. A successful data leader is one who can effectively manage these complexities, ensuring that data systems are not only robust and scalable but also ethical, secure, and aligned with organizational goals. In this book, we will delve into the principles and strategies required to build intelligent, scalable analytics systems. We will explore key topics such as data architecture, data governance, and AI-driven insights, providing practical guidance for data leaders on how to design systems that can scale with the growing demands of today’s data-rich world. We will also examine how to foster a data-driven culture within organizations, ensuring that data and AI are at the heart of decision-making processes. Furthermore, this book will highlight case studies from leading organizations that have successfully integrated AI into their data analytics frameworks, showcasing the real-world applications and benefits of these systems. Through the insights and strategies presented in this book, readers will gain a deeper understanding of the intersection of data leadership and AI technologies, learning how to harness the power of AI to build intelligent systems that not only handle data on a scale but also extract meaningful, actionable insights in real time. Whether you are a data professional, a business leader, or someone looking to better understand the future of analytics in the AI-driven world, this book offers a comprehensive guide to navigating the evolving landscape of data leadership and AI-powered analytics. As we continue to move further into the age of AI, the role of data leadership will become even more critical to the success of organizations across industries. This book serves as a resource for those ready to take the helm in building intelligent, scalable analytics systems that will help drive their organizations forward into a new era of innovation and data-driven decision-making. Authors