The Execution Challenge: Delivering Great Strategy at Scale by
An expert playbook for effective strategy execution with a focus on proven, real-world, implementation In The Execution Challenge: Delivering Great Strategy at Scale, a team of renowned strategy execution researchers and consultants delivers a practical and insightful new take on how to effectively execute strategy in today's complex, fast-changing environments. The authors focus on the often missing "HOW" of strategy execution -- exploring the holistic perspectives, skills, and approaches needed to inform and translate strategy and create and maintain a "line-of-sight" between your strategy and its execution. You'll find proven techniques that you can implement to ensure that changes in business strategy are reflected in complementary changes to the organizational project portfolio. The Execution Challenge includes over 70 diagrams and figures, an organizational assessment, and reusable frameworks. You'll also discover: A comprehensive leadership toolkit of approaches, skills, knowledge, processes, and examples you can employ immediately to translate and execute on even the most ambitious strategies A multidimensional and nuanced perspective on understanding modern organizational structures and design that provides a comprehensive view of your firm's value proposition How to align business strategy with project-level execution and maintain the alignment as strategy evolves A can't-miss toolkit for converting words and ideas into coordinated action and momentum, The Execution Challenge is the real-world guide to strategy execution that executives, strategists, transformation and innovation leaders, strategic planners, managers, directors, entrepreneurs, and other business leaders have been waiting for.
Database Performance at Scale by
Discover critical considerations and best practices for improving database performance based on what has worked, and failed, across thousands of teams and use cases in the field. This open access book provides practical guidance for understanding the database-related opportunities, trade-offs, and traps you might encounter while trying to optimize data-intensive applications for high throughput and low latency. Whether you are building a new system from the ground up or trying to optimize an existing use case for increased demand, this book covers the essentials. The book begins with a look at the many factors impacting database performance at the extreme scale that today's game changing applications face--or at least hope to achieve. You'll gain insight into the performance impact of both technical and business requirements, and how those should influence your decisions around database infrastructure and topology. The authors share an inside perspective on often-overlooked engineering details that could be constraining--or helping--your team's database performance. The book also covers benchmarking and monitoring practices by which to measure and validate the outcomes from the decisions that you make. The ultimate goal of the book is to help you discover new ways to optimize database performance for your team's specific use cases, requirements, and expectations. What You Will Learn Understand often overlooked factors that impact database performance at scale Recognize data-related performance and scalability challenges associated with your project Select a database architecture that's suited to your workloads, use cases, and requirements Avoid common mistakes that could impede your long-term agility and growth Jumpstart teamwide adoption of best practices for optimizing database performance at scale Who This Book Is For Individuals and teams looking to optimize distributed database performance for an existing project or to begin a new performance-sensitive project with a solid and scalable foundation. This will likely include software architects, database architects, and senior software engineers who are either experiencing or anticipating pain related to database latency and/or throughput.
Networked, Scaled, and Agile by
While technology and geopolitical forces change the face of business today, the patterns and challenges of organizing humans to work together across organization, culture, language and time zone boundaries remain. To face these challenges, all organizations need to be agile, networked and scalable. Networked, Scaled, and Agile reveals how to shape organizations that will enable people to make faster and better decisions in a more complex world. By outlining the tension between the need for agility/differentiation and scale/integration, the book offers a new way to think about this debate using the models of the Tower (vertical integration) and the Square (horizontal integration). It addresses the role of the leadership team and how the organization design process can build C-suite leaders and successors. Each chapter concludes with a series of reflection questions for leaders as well as a summary of key concepts and tips. Including case studies from global organizations, Networked, Scaled, and Agile reveals how organization design can address three of the biggest business challenges organizations face today: how to build a new capability across the entire enterprise; how to make the entire organization more customer-centric; and how to allow for faster innovation.
Practical DataOps by
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making. Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles. This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output. What You Will Learn Develop a data strategy for your organization to help it reach its long-term goals Recognize and eliminate barriers to delivering data to users at scale Work on the right things for the right stakeholders through agile collaboration Create trust in data via rigorous testing and effective data management Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes Create cross-functional self-organizing teams focused on goals not reporting lines Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products Who This Book Is For Data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams who want to dramatically increase the value their organization derives from data. The book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production.
