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Annotation The Linux professionals' guide to effectively and efficiently diagnosing software problems and system crashes in the Linux environment.
Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization
Most marketing scholars implicitly consider independent merchants as conservative and passive actors, and study the modernization of retailing via department stores, chains and supermarkets. In this innovative study, Franck Cochoy challenges this perspective and takes a close look at the transformation of commerce through the lens of Progressive Grocer, an American trade magazine launched in 1922. Aimed at modernizing small independent grocery stores, Progressive Grocer sowed the seeds for modern self-service which spread in small retail outlets, sometimes well before the advent of the large retail spaces which are traditionally viewed as the origin of the self-service economy. The author illustrates how this publication had a highly influential role on what the trade considered to be best practice and shaped what was considered to be cutting edge. By displacing the consumer and their agency from the centre of analytic attention, this innovative book highlights the complex impact of social, technical and retailing environment factors that structure and delimit consumer freedom in the marketplace. This detailed critical analysis of the origins of self-service will be of interest to a wide variety of scholars not only in marketing and consumer research, but also in business history, sociology and cultural studies.
This book documents and examines the history of technology used by consumers to serve oneself. The telephone’s development as a self-service technology functions as the narrative spine, beginning with the advent of rotary dialing eliminating most operator services and transforming every local connection into an instance of self-service. Today, nearly a century later, consumers manipulate 0-9 keypads on a plethora of digital machines. Throughout the book Palm employs a combination of historical, political-economic and cultural analysis to describe how the telephone keypad was absorbed into business models across media, retail and financial industries, as the interface on everyday machines including the ATM, cell phone and debit card reader. He argues that the naturalization of self-service telephony shaped consumers’ attitudes and expectations about digital technology.
Self-organisation, self-regulation, self-repair, and self-maintenance are promising conceptual approaches to deal with the ever increasing complexity of distributed interacting software and information handling systems. Self-organising applications are able to dynamically change their functionality and structure without direct user intervention to respond to changes in requirements and the environment. This book comprises revised and extended papers presented at the International Workshop on Engineering Self-Organising Applications, ESOA 2004, held in New York, NY, USA in July 2004 at AAMAS as well as invited papers from leading researchers. The papers are organized in topical sections on state of the art, synthesis and design methods, self-assembly and robots, stigmergy and related topics, and industrial applications.
The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use
Achieving faster, better, cheaper, and more creative innovation outcomes with the 5x5 framework: 5 people, 5 days, 5 experiments, $5,000, and 5 weeks What is the best way for a company to innovate? Advice recommending “innovation vacations” and the luxury of failure may be wonderful for organizations with time to spend and money to waste. The Innovator’s Hypothesis addresses the innovation priorities of companies that live in the real world of limits. Michael Schrage advocates a cultural and strategic shift: small teams, collaboratively—and competitively—crafting business experiments that make top management sit up and take notice. He introduces the 5x5 framework: giving diverse teams of five people up to five days to come up with portfolios of five business experiments costing no more than $5,000 each and taking no longer than five weeks to run. Successful 5x5s, Schrage shows, make people more effective innovators, and more effective innovators mean more effective innovations.
Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.