Data Analytics In Project Management

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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
Data Analytics in Project Management Book PDF

Author : Seweryn Spalek,J. Davidson Frame,Yanping Chen,Carl Pritchard,Alfonso Bucero,Werner Meyer,Ryan Legard,Michael Bragen,Klas Skogmar,Deanne Larson,Bert Brijs
Publisher : Taylor & Francis Group/CRC Press
Page : 11 pages
File Size : 42,7 Mb
Release : 2019-01-01
Category : Business & Economics
ISBN : 9781138307285

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Data Analytics in Project Management by Seweryn Spalek,J. Davidson Frame,Yanping Chen,Carl Pritchard,Alfonso Bucero,Werner Meyer,Ryan Legard,Michael Bragen,Klas Skogmar,Deanne Larson,Bert Brijs Pdf

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.

Project Management Analytics

Harjit Singh
Project Management Analytics Book PDF

Author : Harjit Singh
Publisher : FT Press
Page : 412 pages
File Size : 46,7 Mb
Release : 2015-11-12
Category : Business & Economics
ISBN : 9780134190495

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Project Management Analytics by Harjit Singh Pdf

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

The Data-Driven Project Manager

Mario Vanhoucke
The Data Driven Project Manager Book PDF

Author : Mario Vanhoucke
Publisher : Apress
Page : 164 pages
File Size : 47,5 Mb
Release : 2018-03-27
Category : Business & Economics
ISBN : 9781484234983

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The Data-Driven Project Manager by Mario Vanhoucke Pdf

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 Analytics for Engineering and Construction Project Risk Management

Ivan Damnjanovic,Kenneth Reinschmidt
Data Analytics for Engineering and Construction Project Risk Management Book PDF

Author : Ivan Damnjanovic,Kenneth Reinschmidt
Publisher : Springer
Page : 379 pages
File Size : 41,5 Mb
Release : 2019-05-23
Category : Technology & Engineering
ISBN : 9783030142513

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Data Analytics for Engineering and Construction Project Risk Management by Ivan Damnjanovic,Kenneth Reinschmidt Pdf

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.

Handbook of Research on Expanding Business Opportunities With Information Systems and Analytics

Jamil, George Leal
Handbook of Research on Expanding Business Opportunities With Information Systems and Analytics Book PDF

Author : Jamil, George Leal
Publisher : IGI Global
Page : 455 pages
File Size : 43,6 Mb
Release : 2018-07-20
Category : Business & Economics
ISBN : 9781522562269

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Handbook of Research on Expanding Business Opportunities With Information Systems and Analytics by Jamil, George Leal Pdf

Recent advancements in data collection will affect all aspects of businesses, improving and bringing complexity to management and demanding integration of all resources, principles, and processes. The interpretation of these new technologies is essential to the advancement of management and business. The Handbook of Research on Expanding Business Opportunities With Information Systems and Analytics is a vital scholarly publication that examines technological advancements in data collection that will influence major change in many aspects of business through a multidisciplinary approach. Featuring coverage on a variety of topics such as market intelligence, knowledge management, and brand management, this book explores new complexities to management and other aspects of business. This publication is designed for entrepreneurs, business managers and executives, researchers, business professionals, data analysts, academicians, and graduate-level students seeking relevant research on data collection advancements.

Data Analytics Initiatives

Ondřej Bothe,Ondřej Kubera,David Bednář,Martin Potančok,Ota Novotný
Data Analytics Initiatives Book PDF

Author : Ondřej Bothe,Ondřej Kubera,David Bednář,Martin Potančok,Ota Novotný
Publisher : CRC Press
Page : 169 pages
File Size : 55,9 Mb
Release : 2022-04-20
Category : Computers
ISBN : 9781000629347

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Data Analytics Initiatives by Ondřej Bothe,Ondřej Kubera,David Bednář,Martin Potančok,Ota Novotný Pdf

The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

Aligning Business Strategies and Analytics

Murugan Anandarajan,Teresa D. Harrison
Aligning Business Strategies and Analytics Book PDF

Author : Murugan Anandarajan,Teresa D. Harrison
Publisher : Springer
Page : 211 pages
File Size : 44,8 Mb
Release : 2018-09-27
Category : Business & Economics
ISBN : 9783319932996

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Aligning Business Strategies and Analytics by Murugan Anandarajan,Teresa D. Harrison Pdf

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.

HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)

Harvard Business Review
HBR Guide to Data Analytics Basics for Managers HBR Guide Series Book PDF

Author : Harvard Business Review
Publisher : Harvard Business Press
Page : 256 pages
File Size : 48,8 Mb
Release : 2018-03-13
Category : Business & Economics
ISBN : 9781633694293

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HBR Guide to Data Analytics Basics for Managers (HBR Guide Series) by Harvard Business Review Pdf

Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

Managing Your Data Science Projects

Robert de Graaf
Managing Your Data Science Projects Book PDF

Author : Robert de Graaf
Publisher : Apress
Page : 146 pages
File Size : 40,6 Mb
Release : 2019-06-07
Category : Computers
ISBN : 9781484249079

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Managing Your Data Science Projects by Robert de Graaf Pdf

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

Big Data Analytics

Kim H. Pries,Robert Dunnigan
Big Data Analytics Book PDF

Author : Kim H. Pries,Robert Dunnigan
Publisher : CRC Press
Page : 576 pages
File Size : 44,6 Mb
Release : 2015-02-05
Category : Computers
ISBN : 9781482234527

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Big Data Analytics by Kim H. Pries,Robert Dunnigan Pdf

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Cross Functional Collaboration in Agile Project Management for International Trade

Bryan Christiansen,Browning Wharton
Cross Functional Collaboration in Agile Project Management for International Trade Book PDF

Author : Bryan Christiansen,Browning Wharton
Publisher : Unknown
Page : 128 pages
File Size : 51,9 Mb
Release : 2021
Category : International business enterprises
ISBN : 1799878724

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Cross Functional Collaboration in Agile Project Management for International Trade by Bryan Christiansen,Browning Wharton Pdf

"This book investigates agile project management, a modern flexible approach to project management, as it pertains to international business/trade within the context of globalization by offering concepts to help organizational teams to adapt to change quickly and deliver work fast"--

R for Data Science

Hadley Wickham,Garrett Grolemund
R for Data Science Book PDF

Author : Hadley Wickham,Garrett Grolemund
Publisher : "O'Reilly Media, Inc."
Page : 521 pages
File Size : 48,9 Mb
Release : 2016-12-12
Category : Computers
ISBN : 9781491910368

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R for Data Science by Hadley Wickham,Garrett Grolemund Pdf

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

Project Management, Planning and Control

Albert Lester
Project Management Planning and Control Book PDF

Author : Albert Lester
Publisher : Butterworth-Heinemann
Page : 460 pages
File Size : 50,8 Mb
Release : 2007
Category : Electronic books
ISBN : 075066956X

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Project Management, Planning and Control by Albert Lester Pdf

This fifth edition provides a comprehensive resource for project managers. It describes the latest project management systems that use critical path methods.

Data Analytics

Subhashish Samaddar,Satish Nargundkar
Data Analytics Book PDF

Author : Subhashish Samaddar,Satish Nargundkar
Publisher : CRC Press
Page : 218 pages
File Size : 50,7 Mb
Release : 2019-02-18
Category : Computers
ISBN : 9781351973403

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Data Analytics by Subhashish Samaddar,Satish Nargundkar Pdf

If you are a manager who receives the results of any data analyst’s work to help with your decision-making, this book is for you. Anyone playing a role in the field of analytics can benefit from this book as well. In the two decades the editors of this book spent teaching and consulting in the field of analytics, they noticed a critical shortcoming in the communication abilities of many analytics professionals. Specifically, analysts have difficulty in articulating in business terms what their analyses showed and what actionable recommendations were made. When analysts made presentations, they tended to lapse into the technicalities of mathematical procedures, rather than focusing on the strategic and tactical impact and meaning of their work. As analytics has become more mainstream and widespread in organizations, this problem has grown more acute. Data Analytics: Effective Methods for Presenting Results tackles this issue. The editors have used their experience as presenters and audience members who have become lost during presentation. Over the years, they experimented with different ways of presenting analytics work to make a more compelling case to top managers. They have discovered tried and true methods for improving presentations, which they share. The book also presents insights from other analysts and managers who share their own experiences. It is truly a collection of experiences and insight from academics and professionals involved with analytics. The book is not a primer on how to draw the most beautiful charts and graphs or about how to perform any specific kind of analysis. Rather, it shares the experiences of professionals in various industries about how they present their analytics results effectively. They tell their stories on how to win over audiences. The book spans multiple functional areas within a business, and in some cases, it discusses how to adapt presentations to the needs of audiences at different levels of management.

The Data and Analytics Playbook

Lowell Fryman,Gregory Lampshire,Dan Meers
The Data and Analytics Playbook Book PDF

Author : Lowell Fryman,Gregory Lampshire,Dan Meers
Publisher : Morgan Kaufmann
Page : 292 pages
File Size : 49,6 Mb
Release : 2016-08-12
Category : Computers
ISBN : 9780128025475

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The Data and Analytics Playbook by Lowell Fryman,Gregory Lampshire,Dan Meers Pdf

The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success