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Building Real-Time Analytics Systems - From Events to Insights with Apache Kafka and Apache Pinot: Mark Needham, Dunith... Building Real-Time Analytics Systems - From Events to Insights with Apache Kafka and Apache Pinot
Mark Needham, Dunith Dhanushka
R1,299 R1,140 Discovery Miles 11 400 Save R159 (12%) Ships in 12 - 19 working days

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. In the first part of this book, authors Mark Needham and Dunith Dhanushka from StarTree provide an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The 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. With this book, 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 static data using Kafka Streams Write real-time queries against event data stored in Apache Pinot Build a real-time dashboard, fraud detection pipeline, order tracking app, and anomaly detection system Learn how organizations like Uber, Stripe, and Just Eat use real-time analytics

Graph Algorithms - Practical Examples in Apache Spark and Neo4j (Paperback): Amy Hodler, Mark Needham Graph Algorithms - Practical Examples in Apache Spark and Neo4j (Paperback)
Amy Hodler, Mark Needham
R1,647 R1,352 Discovery Miles 13 520 Save R295 (18%) Ships in 12 - 19 working days

Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns-from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today's data Understand how popular graph algorithms work and how they're applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark

Robert Cray - Definitive Collection CD (2007) (CD): Robert Cray Robert Cray - Definitive Collection CD (2007) (CD)
Robert Cray; Contributions by Don Smith, John Hampton, Mark Needham, Niko Bolas, …
R243 Discovery Miles 2 430 Out of stock
Don Felder - ROAD TO FOREVER(Bonus Tracks) CD (2014) (CD): Don Felder Don Felder - ROAD TO FOREVER(Bonus Tracks) CD (2014) (CD)
Don Felder; Contributions by Mikal Blue, Ed Cherney, Will Briere, Mark Needham, …
R414 Discovery Miles 4 140 Out of stock
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