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| data and project management: Data Analytics in Project Management Seweryn Spalek, J. Davidson Frame, Yanping Chen, Carl Pritchard, Alfonso Bucero, Werner Meyer, Ryan Legard, Michael Bragen, Klas Skogmar, Deanne Larson, Bert Brijs, 2019-01-01 Data Analytics in Project Management. Data analytics plays a crucial role in business analytics. Without a rigid approach to analyzing data, there is no way to glean insights from it. Business analytics ensures the expected value of change while that change is implemented by projects in the business environment. Due to the significant increase in the number of projects and the amount of data associated with them, it is crucial to understand the areas in which data analytics can be applied in project management. This book addresses data analytics in relation to key areas, approaches, and methods in project management. It examines: • Risk management • The role of the project management office (PMO) • Planning and resource management • Project portfolio management • Earned value method (EVM) • Big Data • Software support • Data mining • Decision-making • Agile project management Data analytics in project management is of increasing importance and extremely challenging. There is rapid multiplication of data volumes, and, at the same time, the structure of the data is more complex. Digging through exabytes and zettabytes of data is a technological challenge in and of itself. How project management creates value through data analytics is crucial. Data Analytics in Project Management addresses the most common issues of applying data analytics in project management. The book supports theory with numerous examples and case studies and is a resource for academics and practitioners alike. It is a thought-provoking examination of data analytics applications that is valuable for projects today and those in the future. |
| data and project management: The Data-Driven Project Manager Mario Vanhoucke, 2018-03-27 Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as “dynamic scheduling” or “integrated project management and control.” It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project’s time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project’s time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project’s performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as dynamic scheduling) which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or dynamic scheduling) via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles |
| data and project management: Project Management Analytics Harjit Singh, 2015-11-12 To manage projects, you must not only control schedules and costs: you must also manage growing operational uncertainty. Today’s powerful analytics tools and methods can help you do all of this far more successfully. In Project Management Analytics, Harjit Singh shows how to bring greater evidence-based clarity and rationality to all your key decisions throughout the full project lifecycle. Singh identifies the components and characteristics of a good project decision and shows how to improve decisions by using predictive, prescriptive, statistical, and other methods. You’ll learn how to mitigate risks by identifying meaningful historical patterns and trends; optimize allocation and use of scarce resources within project constraints; automate data-driven decision-making processes based on huge data sets; and effectively handle multiple interrelated decision criteria. Singh also helps you integrate analytics into the project management methods you already use, combining today’s best analytical techniques with proven approaches such as PMI PMBOK® and Lean Six Sigma. Project managers can no longer rely on vague impressions or seat-of-the-pants intuition. Fortunately, you don’t have to. With Project Management Analytics, you can use facts, evidence, and knowledge—and get far better results. Achieve efficient, reliable, consistent, and fact-based project decision-making Systematically bring data and objective analysis to key project decisions Avoid “garbage in, garbage out” Properly collect, store, analyze, and interpret your project-related data Optimize multi-criteria decisions in large group environments Use the Analytic Hierarchy Process (AHP) to improve complex real-world decisions Streamline projects the way you streamline other business processes Leverage data-driven Lean Six Sigma to manage projects more effectively |
| data and project management: Agile Data Warehousing Project Management Ralph Hughes, 2012-12-28 You have to make sense of enormous amounts of data, and while the notion of agile data warehousing might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes. Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious data mart. Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. - Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on track - Includes strategies for getting accurate and actionable requirements from a team's business partner - Revolutionary estimating techniques that make forecasting labor far more understandable and accurate - Demonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialties - Enables you and your teams to start simple and progress steadily to world-class performance levels |
| data and project management: Data Warehouse Project Management Sid Adelman, Larissa T. Moss, 2010-07-15 |
| data and project management: Data Analytics in Project Management Seweryn Spalek, 2018-10-25 This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book’s integrated approach to investigating both fields enhances the value of research findings. |
| data and project management: Leading Complex Projects Edward W. Merrow, Neeraj Nandurdikar, 2018-05-01 Quantitative analysis of outcomes vs PMs at the individual level Leading Complex Projects takes a unique approach to post-mortem analysis to provide project managers with invaluable insight. For the first time, individual PM characteristics are quantitatively linked to project outcomes through a major study investigating the role of project leadership in the success and failure of complex industrial projects; hard data on the backgrounds, education, and personality characteristics of over 100 directors of complex projects is analyzed against the backdrop of project performance to provide insight into controllable determinants of outcomes. By placing these analyses alongside their own data, PMs will gain greater insight into areas of weakness and strength, locate recurring obstacles, and identify project components in need of greater planning, oversight, or control. The role of leadership is to deliver results; in project management, this means taking responsibility for project outcomes. PMs are driven by continuous improvement, and this book provides a wealth of insight to help you achieve the next step forward. Understand why small, simple projects consistently outperform larger, more complex projects Delve into the project manager's role in generating successful outcomes Examine the data from over 100 PMs of complex industrial projects Link PM characteristics to project outcome to find areas for improvement Complex industrial projects from around the world provide a solid basis for quantitative analysis of outcomes—and the PMs who drive them. Although the majority of the data is taken from projects in the petroleum industry, the insights gleaned from analysis are widely applicable across industry lines for PMs who lead complex projects of any stripe. Leading Complex Projects provides clear, data-backed improvement guidance for anyone in a project management role. |
| data and project management: Data Analytics for Engineering and Construction Project Risk Management Ivan Damnjanovic, Kenneth Reinschmidt, 2019-05-23 This book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes. The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts’ judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory. The book is organized in three parts and fourteen chapters. In Part I the authors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution. |
| data and project management: Data Center Handbook Hwaiyu Geng, 2014-12-22 Provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers Organizations in need of high-speed connectivity and nonstop systems operations depend upon data centers for a range of deployment solutions. A data center is a facility used to house computer systems and associated components, such as telecommunications and storage systems. It generally includes multiple power sources, redundant data communications connections, environmental controls (e.g., air conditioning, fire suppression) and security devices. With contributions from an international list of experts, The Data Center Handbook instructs readers to: Prepare strategic plan that includes location plan, site selection, roadmap and capacity planning Design and build green data centers, with mission critical and energy-efficient infrastructure Apply best practices to reduce energy consumption and carbon emissions Apply IT technologies such as cloud and virtualization Manage data centers in order to sustain operations with minimum costs Prepare and practice disaster reovery and business continuity plan The book imparts essential knowledge needed to implement data center design and construction, apply IT technologies, and continually improve data center operations. |
| data and project management: Applying Artificial Intelligence in Project Management Paul Boudreau, 2024-10-10 This book describes the AI tools in concept and how they apply directly to project success. It also demonstrates the strategy and methods used to purchase and implement AI tools for project management. You will understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using artificial intelligence for project management improves project success rates. The book features project management success stories and demonstrates how to leave behind that low project success rate for one that is 95 percent or higher. Supplemental teaching materials are available for use as a textbook. FEATURES: Covers a practical approach to using AI in project management Features a chapter on combining AI with other technologies such as IoT, Blockchain, and virtual reality for further insights into leading-edge changes for project management Demonstrates how to achieve higher productivity and incredible project performance by applying AI concepts Includes supplemental teaching materials for use as a textbook |
| data and project management: Managing Your Data Science Projects Robert de Graaf, 2019-06-07 At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way. The value of data science within an organization cannot be overstated. Thus, it is vital that strategies and communication between teams are dexterously managed. Three main ways that data science strategy is used in a company is to research its customers, assess risk analytics, and log operational measurements. These all require different managerial instincts, backgrounds, and experiences, and de Graaf cogently breaks down the unique reasons behind each. They must align seamlessly to eventually be adopted as dynamic models. Data science is a relatively new discipline, and as such, internal processes for it are not as well-developed within an operational business as others. With Managing Your Data Science Projects, you will learn how to create products that solve important problems for your customers and ensure that the initial success is sustained throughout the product’s intended life. Your users will trust you and your models, and most importantly, you will be a more well-rounded and effectual data scientist throughout your career. Who This Book Is For Early-career data scientists, managers of data scientists, and those interested in entering the field of data science |
| data and project management: Software Project Management in Practice Pankaj Jalote, 2005 |
| data and project management: Data Warehouse Project Management Sid Adelman, Larissa Terpeluk Moss, 2000 Data warehouse development projects present a unique set of management challenges that can confound even the most experienced project manager. This work addresses these challenges and provides a roadmap to managing every aspect of data warehouse design, development, and implementation. It also reveals many pitfalls to watch out for. |
| data and project management: Researching the Value of Project Management Mark Mullaly, PMP, Janice Thomas, 2008-12-01 Consulting and practitioner literature often discusses and proclaims project management value; however the actual value resulting from investments in project management has been hard to define, let alone measure. In the past, few rigorous studies have been conducted to seek out the measurable value of project management. The Project Management Institute requested proposals in 2004 for research designed to quantify the value of project management. This monograph, Researching the Value of Project Management Research, documents the three years of fieldwork and cross-disciplinary analysis conducted between May 2005 and June 2008 by the research team that won the proposal. |
| data and project management: Performance-Based Project Management Glen Alleman, 2014-02-13 Even the most experienced project managers aren’t immune to the more common and destructive reasons for project collapses. Poor time and budget performance, failure to deal with complexity, uncontrolled changes in scope . . . they can catch anyone off guard. Performance-Based Project Management can help radically improve your project’s success rate, despite these and other obstacles that will try to take it down. Readers will discover how they can increase the probability of project success, detailing a step-by-step plan for avoiding surprises, forecasting performance, identifying risk, and taking corrective action to keep a project a success. Project leaders wishing to stand out among their peers who are continually hampered by these unexpected failures will learn how to:• Assess the business capabilities needed for a project• Plan and schedule the work• Determine the resources required to complete on time and on budget• Identify and manage risks to success• Measure performance in units meaningful to decision makersBy connecting mission strategy with project execution, this invaluable resource for project managers in every industry will help bring projects to successful, career-enhancing completion. |
| data and project management: The Project Management Answer Book Jeff Furman PMP, 2014-12-01 If it's essential to project management... it's in here! The first edition of The Project Management Answer Book addressed all the key principles of project management that every project manager needs to know. With a new chapter on scrum agile, updates throughout, and many new PMP® test tips, this new edition builds on that solid foundation. The structure of this update maps closely to the PMBOK® Guide, Fifth Edition, and is designed to assist anyone studying for the PMP® and other certification exams. Helpful sections cover: • Networking and social media tips for PMs, including the best professional organizations, virtual groups, and podcast resources • The formulas PMs need to know, plus a template to help certification candidates prepare and self-test for their exams • Quick study sheet for the processes covered on the PMP® exam • Key changes in PMBOK® Guide, Fifth Edition, for readers familiar with earlier versions who want “the skinny” on the new version. PMs at every level will find real gold in the information nuggets provided in this new edition. Those new to project management will find the comprehensive coverage and the depth of the answers especially valuable, and will like the easy-to-read style and Q&A format. For experienced managers looking for new tools and skills to help them pass their PMP® or other certification exams, this is a must-have resource. |
| data and project management: Information Systems Project Management David L. Olson, 2014-12-19 Information Systems Project Management addresses project management in the context of information systems. It deals with general project management principles, with focus on the special characteristics of information systems. It is based on an earlier text, but shortened to focus on essential project management elements.This updated version presents various statistics indicating endemic problems in completing information system projects on time, within budget, at designed functionality. While successful completion of an information systems project is a challenge, there are some things that can be done to improve the probability of project success. This book reviews a number of project management tools, including, developing organizational ability to work on projects, better systems analysis and design, project estimation, and project control and termination. |
| data and project management: Risk Management for Project Driven Organizations Andy Jordan, 2013-05-13 Organizations invest a lot of time, money, and energy into developing and utilizing risk management practices as part of their project management disciplines. Yet, when you move beyond the project to the program, portfolio, PMO and even organizational level, that same level of risk command and control rarely exists. With this in mind, well-known subject matter expert and author Andy Jordan starts where most leave off. He explores risk management in detail at the portfolio, program, and PMO levels. Using an engaging and easy-to-read writing style, Mr. Jordan takes readers from concepts to a process model, and then to the application of that customizable model in the user’s unique environment, helping dramatically improve their risk command and control at the organizational level. He also provides a detailed discussion of some of the challenges involved in this process. Risk Management for Project Driven Organizations is designed to aid strategic C-level decision makers and those involved in the project, program, portfolio, and PMO levels of an organization. J. Ross Publishing offers an add-on for a nominal fee -- Downloadable tools and templates for easy customization and implementation. |
| data and project management: Project Management for Information Professionals Margot Note, 2015-11-03 Aimed at practitioners, this handbook imparts guidance on project management techniques in the cultural heritage sector. Information professionals often direct complex endeavors with limited project management training or resources. Project Management for Information Professionals demystifies the tools and processes essential to successful project management and advises on how to manage the interpersonal dynamics and organizational culture that influence the effectiveness of these methods. With this book, readers will gain the knowledge to initiate, plan, execute, monitor, and close projects. - offers guidance based on real-world experience - prepares readers without prior project management knowledge or experience - provides lean, easy-to-read, and jargon-free instructions - aimed at information professionals working in libraries, archives, museums |
| data and project management: Fundamentals of Project Management James P. Lewis, 2002 Updated concepts and tools to set up project plans, schedule work, monitor progress-and consistently achieve desired project results.In today's time-based and cost-conscious global business environment, tight project deadlines and stringent expectations are the norm. This classic book provides businesspeople with an excellent introduction to project management, supplying sound, basic information (along with updated tools and techniques) to understand and master the complexities and nuances of project management. Clear and down-to-earth, this step-by-step guide explains how to effectively spearhead every stage of a project-from developing the goals and objectives to managing the project team-and make project management work in any company. This updated second edition includes: * New material on the Project Management Body of Knowledge (PMBOK) * Do's and don'ts of implementing scheduling software* Coverage of the PMP certification offered by the Project Management Institute* Updated information on developing problem statements and mission statements* Techniques for implementing today's project management technologies in any organization-in any industry. |
| data and project management: Managing Change in Organizations Project Management Institute, 2013-08-01 Managing Change in Organizations: A Practice Guide is unique in that it integrates two traditionally disparate world views on managing change: organizational development/human resources and portfolio/program/project management. By bringing these together, professionals from both worlds can use project management approaches to effectively create and manage change. This practice guide begins by providing the reader with a framework for creating organizational agility and judging change readiness. |
| data and project management: Digital Project Management Taylor Olson, 2016 The digital world is growing and changing at a rate that can seem overwhelming to those project managers who have to keep up with it to build customer-facing solutions and applications. It's rare for project managers working in this field to be provided with much direction or a process by which to carry out a project, and there has been almost nothing available specific to these types of projects in the literary marketplace. Digital Project Management: The Complete Step-by-Step Guide to a Successful Launch was developed to fill this gap by providing the knowledge, best practices, and proven steps to successfully manage digital projects from end-to-end and was created to be easily adaptable to different project types and technological advances. |
| data and project management: Project Management, Planning and Control Albert Lester, 2007 This fifth edition provides a comprehensive resource for project managers. It describes the latest project management systems that use critical path methods. |
| data and project management: Software Project Management in a Changing World Günther Ruhe, Claes Wohlin, 2014-09-04 By bringing together various current directions, Software Project Management in a Changing World focuses on how people and organizations can make their processes more change-adaptive. The selected chapters closely correspond to the project management knowledge areas introduced by the Project Management Body of Knowledge, including its extension for managing software projects. The contributions are grouped into four parts, preceded by a general introduction. Part I “Fundamentals” provides in-depth insights into fundamental topics including resource allocation, cost estimation and risk management. Part II “Supporting Areas” presents recent experiences and results related to the management of quality systems, knowledge, product portfolios and global and virtual software teams. Part III “New Paradigms” details new and evolving software-development practices including agile, distributed and open and inner-source development. Finally, Part IV “Emerging Techniques” introduces search-based techniques, social media, software process simulation and the efficient use of empirical data and their effects on software-management practices. This book will attract readers from both academia and practice with its excellent balance between new findings and experience of their usage in new contexts. Whenever appropriate, the presentation is based on evidence from empirical evaluation of the proposed approaches. For researchers and graduate students, it presents some of the latest methods and techniques to accommodate new challenges facing the discipline. For professionals, it serves as a source of inspiration for refining their project-management skills in new areas. |
| data and project management: Managing Complex, High Risk Projects Franck Marle, Ludovic-Alexandre Vidal, 2015-12-18 Maximizing reader insights into project management and handling complexity-driven risks, this book explores propagation effects, non-linear consequences, loops, and the emergence of positive properties that may occur over the course of a project. This book presents an introduction to project management and analysis of traditional project management approaches and their limits regarding complexity. It also includes overviews of recent research works about project complexity modelling and management as well as project complexity-driven issues. Moreover, the authors propose their own new approaches, new methodologies and new tools which may be used by project managers and/or researchers and/or students in the management of their projects. These new elements include project complexity definitions and frameworks, multi-criteria approaches for project complexity measurement, advanced methodologies for project management (propagation studies to anticipate potential behaviour of the project, and clustering approaches to improve coordination between project actors) and industrial case studies (automotive industry, civil engineering, railroad industry, performing arts,...) and exercises (with their solutions) which will allow readers to improve and strengthen their knowledge and skills in the management of complex and (thus) risky projects. |
| data and project management: Complete Guide to Digital Project Management Shailesh Kumar Shivakumar, 2018-02-19 Get a 360-degree view of digital project management. Learn proven best practices from case studies and real-world scenarios. A variety of project management tools, templates, models, and frameworks are covered. This book provides an in-depth view of digital project management from initiation to execution to monitoring and maintenance. Covering end-to-end topics from pre-sales to post-production, the book explores project management from various dimensions. Each core concept is complemented by case studies and real-world scenarios. The Complete Guide to Digital Project Management provides valuable tools for your use such as: Frameworks: governance, quality, knowledge transfer, root cause analysis, digital product evaluation, digital consulting, estimation Templates: estimation, staffing, resource induction, RACI Models: governance, estimation, pricing, digital maturity continuous execution, earned value management and effort forecast Metrics: project management, quality What You’ll Learn Study best practices and failure scenarios in digital projects, including common challenges, recurring problem themes, and leading indicators of project failures Explore an in-depth discussion of topics related to project quality and project governance Understand Agile and Scrum practices for Agile execution See how to apply Quality Management in digital projects, including a quality strategy, a quality framework, achieving quality in various project phases, and quality best practices Be able to use proven metrics and KPIs to track, monitor, and measure project performance Discover upcoming trends and innovations in digital project management Read more than 20 real-world scenarios in digital project management with proven best practices to handle the scenarios, and a chapter on a digital transformation case study Who This Book Is For Software project managers, software program managers, account managers, software architects, lead developers, and digital enthusiasts |
| data and project management: Project Management Ofer Zwikael, John R. Smyrk, 2019-03-19 Winner of 2020 PMI David I. Cleland Project Management Literature Award This book is a complete project management toolkit for project leaders in business, research and industry. Projects are approved and financed to generate benefits. Project Management: A Benefit Realisation Approach proposes a complete framework that supports this objective – from project selection and definition, through execution, and beyond implementation of deliverables until benefits are secured. The book is the first to explain the creation of organisational value by suggesting a complete, internally-consistent and theoretically rigorous benefit-focused project management methodology, supported with an analytical technique: benefit engineering. Benefit engineering offers a practical approach to the design and maintenance of an organisation’s project portfolio. Building upon the authors’ earlier successful book, Project Management for the Creation of Organisational Value, this comprehensively revised and expanded new book contains the addition of new chapters on project realisation. The book offers a rigorous explanation of how benefits emerge from a project. This approach is developed and strengthened — resulting in a completely client-oriented view of a project. Senior executives, practitioners, students and academics will find in this book a comprehensive guide to the conduct of projects, which includes robust models, a set of consistent principles, an integrated glossary, enabling tools, illustrative examples and case studies. |
| data and project management: Drawdown Paul Hawken, 2017-04-18 • New York Times bestseller • The 100 most substantive solutions to reverse global warming, based on meticulous research by leading scientists and policymakers around the world “At this point in time, the Drawdown book is exactly what is needed; a credible, conservative solution-by-solution narrative that we can do it. Reading it is an effective inoculation against the widespread perception of doom that humanity cannot and will not solve the climate crisis. Reported by-effects include increased determination and a sense of grounded hope.” —Per Espen Stoknes, Author, What We Think About When We Try Not To Think About Global Warming “There’s been no real way for ordinary people to get an understanding of what they can do and what impact it can have. There remains no single, comprehensive, reliable compendium of carbon-reduction solutions across sectors. At least until now. . . . The public is hungry for this kind of practical wisdom.” —David Roberts, Vox “This is the ideal environmental sciences textbook—only it is too interesting and inspiring to be called a textbook.” —Peter Kareiva, Director of the Institute of the Environment and Sustainability, UCLA In the face of widespread fear and apathy, an international coalition of researchers, professionals, and scientists have come together to offer a set of realistic and bold solutions to climate change. One hundred techniques and practices are described here—some are well known; some you may have never heard of. They range from clean energy to educating girls in lower-income countries to land use practices that pull carbon out of the air. The solutions exist, are economically viable, and communities throughout the world are currently enacting them with skill and determination. If deployed collectively on a global scale over the next thirty years, they represent a credible path forward, not just to slow the earth’s warming but to reach drawdown, that point in time when greenhouse gases in the atmosphere peak and begin to decline. These measures promise cascading benefits to human health, security, prosperity, and well-being—giving us every reason to see this planetary crisis as an opportunity to create a just and livable world. |
| data and project management: Project Management All-in-One For Dummies Stanley E. Portny, 2020-09-15 Your ultimate go-to project management bible Perform Be Agile! Time-crunch! Right now, the business world has never moved so fast and project managers have never been so much in demand—the Project Management Institute has estimated that industries will need at least 87 million employees with the full spectrum of PM skills by 2027. To help you meet those needs and expectations in time, Project Management All-in-One For Dummies provides with all the hands-on information and advice you need to take your organizational, planning, and execution skills to new heights. Packed with on-point PM wisdom, these 7 mini-books—including the bestselling Project Management and Agile Project Management For Dummies—help you and your team hit maximum productivity by razor-honing your skills in sizing, organizing, and scheduling projects for ultimate effectiveness. You’ll also find everything you need to overdeliver in a good way when choosing the right tech and software, assessing risk, and dodging the pitfalls that can snarl up even the best-laid plans. Apply formats and formulas and checklists Manage Continuous Process Improvement Resolve conflict in teams and hierarchies Rescue distressed projects |
| data and project management: Project Management Analytics Harjit Singh, 2016 |
| data and project management: Green Project Management Richard Maltzman, David Shirley, 2010-08-31 Winner of PMI's 2011 David I. Cleland Project Management Literature AwardDetailing cutting-edge green techniques and methods, this book teaches project managers how to maximize resources and get the most out of limited budgets. It supplies proven techniques and best practices in green project management, including risk and opportunity assessments. |
| data and project management: Aligning Business Strategies and Analytics Murugan Anandarajan, Teresa D. Harrison, 2018-09-27 This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap. Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry. |
| data and project management: Project Management for Non-project Managers Jack Ferraro, 2012 A seasoned project management consultant introduces critical project management skills, tools and techniques. Includes case studies, checklists and exercises. |
| data and project management: Project Management That Works Rick A. MORRIS, Brette MCWHORTER SEMBER, 2008-08-18 Project management is one of the fastest-growing occupations in the world. The Project Management Institute has seen membership growth of more than 1000% in the last 10 years. But while many of these managers know how to plan a successful project in theory, very few have the practical tools needed to navigate the politics of today’s corporate world. Project managers need more than just technical skills; they need the right communication skills to succeed. Filled with real-world examples, Project Management That Works gives readers the tools they need to: communicate with their team as well as stakeholders • get their teams to function well • run fewer and more productive meetings • turn around failing projects • utilize data properly to make emotional conversations unemotional • know when a project is really done The only book that addresses the real challenges project managers face today, this is an accessible and invaluable tool that will show every reader how to accomplish his mission—no matter the obstacles. |
| data and project management: Integrated IT Project Management Kenneth R. Bainey, 2004 Annotation Integrated IT Project Management: A Model-Centric Approach utilizes practical applications of real-world policies, roles and responsibilities, templates, process flows, and checklists for each of these three component processes. It shows how such processes ensure optimum utilization of people, process, and technology resources during the management and delivery of IT projects. The book provides insight into the key components of the Rational Unified Process from IBM Rational Corporation and the Project Management Body of knowledge PMBOK from the Project Management Institute (PMI) illustrating how they work together and align based on industry processing standards.--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved |
| data and project management: Project Management M. Spinner, 1997 This book is intended to train the readers in basic project management principles for directing the course of a project. The hands-on approach presented in this book takes them through the necessary details for a good understanding of what to expect to complete a successful project. Users of this book will have an understanding, after following through the step-by-step stages, of how to plan and schedule projects. This systematic approach includes the application of project management software. |
| data and project management: Think Like a Data Scientist Brian Godsey, 2017-03-09 Summary Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there. About the Book Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you'll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you'll put this knowledge together using a structured process for data science. When you've finished, you'll have a strong foundation for a lifetime of data science learning and practice. What's Inside The data science process, step-by-step How to anticipate problems Dealing with uncertainty Best practices in software and scientific thinking About the Reader Readers need beginner programming skills and knowledge of basic statistics. About the Author Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups. Table of Contents PART 1 - PREPARING AND GATHERING DATA AND KNOWLEDGE Philosophies of data science Setting goals by asking good questions Data all around us: the virtual wilderness Data wrangling: from capture to domestication Data assessment: poking and prodding PART 2 - BUILDING A PRODUCT WITH SOFTWARE AND STATISTICS Developing a plan Statistics and modeling: concepts and foundations Software: statistics in action Supplementary software: bigger, faster, more efficient Plan execution: putting it all together PART 3 - FINISHING OFF THE PRODUCT AND WRAPPING UP Delivering a product After product delivery: problems and revisions Wrapping up: putting the project away |
| data and project management: Effective Project Management Garth G.F. Ward, 2018-06-19 A practical and accessible guide to managing a successful project Effective Project Management is based around an activities and action check list approach to project management. It provides a guide to the basic principles and the disciplines that managers need to master in order to be successful. The author’s check lists approach (based on his years of practical experience on projects) ensure that project managers are following valid processes, helping them to be innovative in their approach to developing plans and resolving problems. In addition, the author’s check list pick and mix format is designed to be flexible in order to meet the individual needs of the reader. Effective Project Management also contains some information on the theories underpinning project management. Knowledge of the theory helps in the understanding of how project management works in practice. In addition to the book’s check lists of what activities need to be performed, the author offers suggestions on how tasks could be carried out. This important resource: Covers a wide range of project management topics including the project management process, programme and portfolio management, initiating and contracting a project, personal skills and more Offers a highly accessible guide to the author’s verified check list approach Presents flexible guidelines applicable for a wide range projects Includes guidance for project managers at all levels of experience Written for project managers working on engineering or construction projects, Effective Project Management reviews all aspects of a project from initiation and execution to project completion together with the specialist topics and personal skills needed to manage projects effectively. |
| data and project management: Foundations for Architecting Data Solutions Ted Malaska, Jonathan Seidman, 2018-08-29 While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect |
| data and project management: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
