Orchestrate data architecting solutions using JAVA and related technologies to evaluate, recommend and present the most suitable solution to leadership and clients.
Key Features
- Learn how to adapt to the ever evolving data architecture technology landscape.
- Learn to select the most suitable option of technology, platform and architecture to realize effective business value.
- Learn to implement effective data security and governance principles.
Book Description
Java architectural patterns and tools help architects to build reliable, scalable and secure data engineering solutions that collect, manipulate, and publish data.
Developers working with JAVA and related technologies will be able to put their knowledge to work with this practical guide to Architecting Data Engineering solutions. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running in no time.
You will begin by with an overview of data architecture, exploring responsibilities of a Java data architect.
You'll learn about various data formats, data storage, databases and data application platforms and how to choose them. Then you'll learn how to architect a batch and real-time data processing pipeline. Later, you will understand the various JAVA Data Processing patterns. You will learn about Data security and governance. Next, you will learn how to publish Data as a Service and how you can architect it. Get to grips with how to evaluate and recommend an architecture by developing performance benchmarks, estimations and various decision metrics.
By the end of this book, you will be able to successfully orchestrate data architecture solutions using JAVA and related technologies, evaluate, and present the most suitable solution to your clients.
What you will learn
- Learn to analyze, classify and apply correct data architectural solution patterns to problem.
- Learn the Java related Data architecting tools, when and how to use them efficiently.
- Learn to build batch processing, real time processing and Data-as-a-Service proof of concepts using JAVA stack of technologies.
- Learn how to apply security and governance to a solution.
- Learn how to measure, evaluate, recommend and present the most suitable architectural solution.
- Learn core design patterns used in GraphQL and when they should be used in production.
Who This Book Is For
Data architects, aspiring data architects, java developers and anyone who wants to develop, optimize high performance and scalable data architecture solutions using JAVA will find this book useful. Basic understanding of data architecture and Java programming is required to get the best from this book.
Table of Contents
- Basics of Modern Data Architecture
- Data Storage and Databases
- Identifying the Right Data Platform
- ETL Data Load: A batchbased solution to Ingest Data in Data Warehouse
- Architecting a Batch Processing Pipeline
- Architecting a Real-time Processing Pipeline
- Core Architectural Design Patterns
- Enabling Data Security and Governance
- Exposing MongoDB Data as a Service
- Federated and Scalable DaaS with GraphQL
- Measuring Performance and Benchmarking your Applications
- Evaluate, Recommend, and Present Your Solutions
