By Matteo Golfarelli
Foreword through Mark Stephen LaRow, vp of goods, MicroStrategy
"A precise and authoritative e-book that blends fresh learn advancements with industry-level practices for researchers, scholars, and practitioners." Il-Yeol music, Professor, university of knowledge technology and expertise, Drexel University
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Additional resources for Data Warehouse Design, Modern Principles and Methodologies
We introduce additional requirements artifacts, roles, organizational constructs, and practices designed for this purpose. We describe the role that larger-scale, intentional, system-level architectures play in agile development. We introduce a kanban system for reasoning about how to evolve and, when necessary, rearchitect, such systems in an agile manner. We also describe some of the legacy thinking in portfolio and project management and give some suggestions as to what to do about it. We conclude with a chapter describing investment themes, epics, and, finally, one of the ultimate objectives—agile portfolio planning.
In support of our efforts over the past 40 to 50 years, we have implemented various software development methodologies—process frameworks we use to structure, manage, and control our work. Early on, it was a “cut-and-try” approach—ad hoc—as and where necessary. In large part, that worked. Over time, the scope and reach of our endeavors, along with the power of the computers we programmed, increased by 10,000 fold. It seems like very quickly we went from simple simulations to flying commercial airliners internationally.
Decentralize control. Because these provide much of the underlying lean philosophy in this book, we’ll describe each here. Take an economic view: Take an economic view to establish the decision framework for your specific context, whether it is at the team, program, or enterprise level. Understand the full value chain. Do not consider money already spent. Sequence high-risk, low-cost activities first. If you quantify only one thing, quantify the cost of delay. Actively manage queues: Long queues are universally bad because they create longer cycle times, increase risk, lower quality, and decrease motivation.