Wydawca: Packt Publishing
Sinchan Banerjee
Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data.This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert.You’ll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you’ll understand how to architect a batch and real-time data processing pipeline. You’ll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you’ll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics.By the end of this book, you’ll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.
Tarik Makota, Brian Maguire, Danny Gagne, Rajeev...
Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale.Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you’ll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk.By the end of this AWS book, you’ll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).
Dean MacNeil, Aslam Cader
Jira Align is a platform purpose-built for enterprises to connect strategy with execution and drive transparency, consistency, and predictability at all levels of scale. The platform supports business value delivery in agile frameworks such as LeSS, DAD, and SAFe. It also caters to organizations that mix agile with waterfall to support scaled bimodal delivery.Starting with an introduction to the platform and its features, this book takes you through the foundational building blocks of Jira Align. You’ll learn how an organization can benefit from implementing Jira Align and understand how to connect dimensions such as people, work, time, and outcomes. The book takes you through the typical steps for implementing Jira Align for maximizing outcomes and helps you solve common team, program, and portfolio-level challenges by enhancing visibility, tracking dependencies and risks, and using reports for real-time, distributed decision making. Throughout the book, you’ll explore features such as remote agile ceremonies, live roadmaps, and objectives and key results (OKRs). You’ll also get to grips with lean portfolio management, financial reporting, and using the program board for planning and execution.By the end of this book, you’ll be well versed in the key features of Jira Align and be able to leverage them to support all levels of agile at scale.
Hrishikesh Vijay Karambelkar
This book is a step-by-step guide for readers who would like to learn how to build complete enterprise search solutions, with ample real-world examples and case studies. If you are a developer, designer, or architect who would like to build enterprise search solutions for your customers or organization, but have no prior knowledge of Apache Solr/Lucene technologies, this is the book for you.
Hrishikesh Vijay Karambelkar
This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.
Cecil 'Gary' Rupp
Scaled Scrum and Lean-Agile practices provide essential strategies to address large and complex product development challenges not addressed in traditional Scrum. This Scrum/ Lean-Agile handbook provides a comprehensive review and analysis of industry-proven scaling strategies that enable business agility on an enterprise scale. Free of marketing hype or vendor bias, this book helps you decide which practices best fit your situation.You'll start with an introduction to Scrum as a lightweight software development framework and then explore common approaches to scaling it for more complex development scenarios. The book will then guide you through systems theory, lean development, and the application of holistic thinking to more complex software and system development activities. Throughout, you'll learn how to support multiple teams working in collaboration to develop large and complex products and explore how to manage cross-team integration, dependency, and synchronization issues. Later, you'll learn how to improve enterprise operational efficiency across value creation and value delivery activities, before discovering how to align product portfolio investments with corporate strategies.By the end of this Scrum book, you and your product teams will be able to get the most value out of Agile at scale, even in complex cyber-physical system development environments.
Claus Führer, Claus Fuhrer, Jan Erik Solem,...
Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
Claus Führer, Claus Fuhrer, Jan Erik Solem,...
Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python.This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations.By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.