Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publsiher: Academic Press
Total Pages: 420
Release: 2021-03-15
ISBN 10: 9780128180150
ISBN 13: 0128180153
Language: EN, FR, DE, ES & NL

Executing Data Quality Projects Book Review:

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work - with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations - for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach. Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book. Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices. A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online. ~

Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publsiher: Elsevier
Total Pages: 352
Release: 2008-09-01
ISBN 10: 0080558399
ISBN 13: 9780080558394
Language: EN, FR, DE, ES & NL

Executing Data Quality Projects Book Review:

Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations. * Includes numerous templates, detailed examples, and practical advice for executing every step of the “Ten Steps approach. * Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices. * A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E

MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E
Author: Alex Berson,Larry Dubov
Publsiher: McGraw Hill Professional
Total Pages: 512
Release: 2010-12-06
ISBN 10: 0071744592
ISBN 13: 9780071744591
Language: EN, FR, DE, ES & NL

MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E Book Review:

The latest techniques for building a customer-focused enterprise environment "The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance

The Practitioner's Guide to Data Quality Improvement

The Practitioner's Guide to Data Quality Improvement
Author: David Loshin
Publsiher: Elsevier
Total Pages: 432
Release: 2010-11-22
ISBN 10: 9780080920344
ISBN 13: 0080920349
Language: EN, FR, DE, ES & NL

The Practitioner's Guide to Data Quality Improvement Book Review:

The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.

Extreme Scoping

Extreme Scoping
Author: Larissa T. Moss
Publsiher: Technics Publications
Total Pages: 306
Release: 2013-09-01
ISBN 10: 1634620240
ISBN 13: 9781634620246
Language: EN, FR, DE, ES & NL

Extreme Scoping Book Review:

Do your business intelligence (BI) projects take too long to deliver? Is the value of the deliverables less than satisfactory? Do these projects propagate poor data management practices? If you screamed “yes” to any of these questions, read this book to master a proven approach to building your enterprise data warehouse and BI initiatives. Extreme Scoping, based on the Business Intelligence Roadmap, will show you how to build analytics applications rapidly yet not sacrifice data management and enterprise architecture. In addition, all of the roles required to deliver all seven steps of this agile methodology are explained along with many real-world examples. From Wayne Eckerson’s Foreword I’ve read many books about data warehousing and business intelligence (BI). This book by Larissa Moss is one of the best. I should not be surprised. Larissa has spent years refining the craft of designing, building, and delivering BI applications. Over the years, she has developed a keen insight about what works and doesn’t work in BI. This book brings to light the wealth of that development experience. Best of all, this is not some dry text that laboriously steps readers through a technical methodology. Larissa expresses her ideas in a clear, concise, and persuasive manner. I highlighted so many beautifully written and insightful paragraphs in her manuscript that it became comical. I desperately wanted the final, published book rather than the manuscript so I could dog-ear it to death and place it front-and-center in my office bookshelf! From David Well’s Foreword Extreme Scoping is rich with advice and guidance for virtually every aspect of BI projects from planning and requirements to deployment and from back-end data management to front-end information and analytics services. Larissa is both a pragmatist and an independent thinker. Those qualities come through in the style of this book. Extreme Scoping is a well-written book that is easy to absorb. It is not full of surprises. It is filled with a lot of common sense and lessons learned through experience.

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
Author: Laura Sebastian-Coleman
Publsiher: Newnes
Total Pages: 376
Release: 2012-12-31
ISBN 10: 0123977541
ISBN 13: 9780123977540
Language: EN, FR, DE, ES & NL

Measuring Data Quality for Ongoing Improvement Book Review:

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You’ll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges Enables discussions between business and IT with a non-technical vocabulary for data quality measurement Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Data Quality Assessment

Data Quality Assessment
Author: Arkady Maydanchik
Publsiher: Technics Publications
Total Pages: 336
Release: 2007-04-01
ISBN 10: 163462047X
ISBN 13: 9781634620475
Language: EN, FR, DE, ES & NL

Data Quality Assessment Book Review:

Imagine a group of prehistoric hunters armed with stone-tipped spears. Their primitive weapons made hunting large animals, such as mammoths, dangerous work. Over time, however, a new breed of hunters developed. They would stretch the skin of a previously killed mammoth on the wall and throw their spears, while observing which spear, thrown from which angle and distance, penetrated the skin the best. The data gathered helped them make better spears and develop better hunting strategies. Quality data is the key to any advancement, whether it’s from the Stone Age to the Bronze Age. Or from the Information Age to whatever Age comes next. The success of corporations and government institutions largely depends on the efficiency with which they can collect, organize, and utilize data about products, customers, competitors, and employees. Fortunately, improving your data quality doesn’t have to be such a mammoth task. DATA QUALITY ASSESSMENT is a must read for anyone who needs to understand, correct, or prevent data quality issues in their organization. Skipping theory and focusing purely on what is practical and what works, this text contains a proven approach to identifying, warehousing, and analyzing data errors – the first step in any data quality program. Master techniques in: • Data profiling and gathering metadata • Identifying, designing, and implementing data quality rules • Organizing rule and error catalogues • Ensuring accuracy and completeness of the data quality assessment • Constructing the dimensional data quality scorecard • Executing a recurrent data quality assessment This is one of those books that marks a milestone in the evolution of a discipline. Arkady's insights and techniques fuel the transition of data quality management from art to science -- from crafting to engineering. From deep experience, with thoughtful structure, and with engaging style Arkady brings the discipline of data quality to practitioners. David Wells, Director of Education, Data Warehousing Institute

Data Quality

Data Quality
Author: Jack E. Olson
Publsiher: Elsevier
Total Pages: 300
Release: 2003-01-09
ISBN 10: 9780080503691
ISBN 13: 0080503691
Language: EN, FR, DE, ES & NL

Data Quality Book Review:

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality. * Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.

Making Enterprise Information Management (EIM) Work for Business

Making Enterprise Information Management (EIM) Work for Business
Author: John Ladley
Publsiher: Morgan Kaufmann
Total Pages: 552
Release: 2010-07-03
ISBN 10: 0123756960
ISBN 13: 9780123756961
Language: EN, FR, DE, ES & NL

Making Enterprise Information Management (EIM) Work for Business Book Review:

Making Enterprise Information Management (EIM) Work for Business: A Guide to Understanding Information as an Asset provides a comprehensive discussion of EIM. It endeavors to explain information asset management and place it into a pragmatic, focused, and relevant light. The book is organized into two parts. Part 1 provides the material required to sell, understand, and validate the EIM program. It explains concepts such as treating Information, Data, and Content as true assets; information management maturity; and how EIM affects organizations. It also reviews the basic process that builds and maintains an EIM program, including two case studies that provide a birds-eye view of the products of the EIM program. Part 2 deals with the methods and artifacts necessary to maintain EIM and have the business manage information. Along with overviews of Information Asset concepts and the EIM process, it discusses how to initiate an EIM program and the necessary building blocks to manage the changes to managed data and content. Organizes information modularly, so you can delve directly into the topics that you need to understand Based in reality with practical case studies and a focus on getting the job done, even when confronted with tight budgets, resistant stakeholders, and security and compliance issues Includes applicatory templates, examples, and advice for executing every step of an EIM program

The R Book

The R Book
Author: Michael J. Crawley
Publsiher: John Wiley & Sons
Total Pages: 950
Release: 2007-06-13
ISBN 10: 9780470515068
ISBN 13: 0470515066
Language: EN, FR, DE, ES & NL

The R Book Book Review:

The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author’s bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

Data Strategy

Data Strategy
Author: Sid Adelman,Larissa Terpeluk Moss,Majid Abai
Publsiher: Addison-Wesley Professional
Total Pages: 342
Release: 2005
ISBN 10:
ISBN 13: UOM:39015061432053
Language: EN, FR, DE, ES & NL

Data Strategy Book Review:

Without a data strategy, the people within an organization have no guidelines for making decisions that are absolutely crucial to the success of the IT organization and to the entire organization. The absence of a strategy gives a blank check to those who want to pursue their own agendas, including those who want to try new database management systems, new technologies (often unproven), and new tools. This type of environment provides no hope for success. Data Strategy should result in the development of systems with less risk, higher quality systems, and reusability of assets. This is key to keeping cost and maintenance down, thus running lean and mean. Data Strategy provides a CIO with a rationale to counter arguments for immature technology and data strategies that are inconsistent with existing strategies. This book uses case studies and best practices to give the reader the tools they need to create the best strategy for the organization.

Data Quality

Data Quality
Author: Rupa Mahanti
Publsiher: Quality Press
Total Pages: 526
Release: 2019-03-18
ISBN 10: 0873899776
ISBN 13: 9780873899772
Language: EN, FR, DE, ES & NL

Data Quality Book Review:

“This is not the kind of book that you’ll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective.” from the foreword by Thomas C. Redman, Ph.D., “the Data Doc” Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: -Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality-Butterfly effect of data quality-A detailed description of data quality dimensions and their measurement-Data quality strategy approach-Six Sigma - DMAIC approach to data quality-Data quality management techniques-Data quality in relation to data initiatives like data migration, MDM, data governance, etc.-Data quality myths, challenges, and critical success factorsStudents, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout.

Project Manager Street Smarts

Project Manager Street Smarts
Author: Linda Kretz Zaval,Terri Wagner
Publsiher: John Wiley & Sons
Total Pages: 432
Release: 2011-08-24
ISBN 10: 1118173171
ISBN 13: 9781118173176
Language: EN, FR, DE, ES & NL

Project Manager Street Smarts Book Review:

The perfect workbook for project managers and PMP exam candidates seeking practical experience New project managers and students pursuing the Project Management Professional certification are looking for practical experience to solidify their skills. The step-by-step tasks presented in this book offer them an opportunity to practice the common tasks project managers face in the real world. The authors, both expert project management trainers and consultants, explore each phase of project management: initiation, planning, execution, monitoring and control, and closing the project, with in-depth instructions for handling the tasks associated with each phase. New project managers and exam candidates need practical experience to perfect their skills; this book helps them learn through real-world scenarios Explores each phase of project management, offering step-by-step instructions to many of the tasks project managers confront each day Covers all phases of project management, including initiating the project, planning, executing, monitoring, controlling, and closing the project Looks at defining scope, developing a project charter, creating a plan to manage change, breaking down the work, managing resource allocation, measuring performance, and releasing resources Fully updated to cover everything required for the 2011 PMP exam PMP exam candidates and anyone new to project management will benefit from the hands-on exercises in this book.

Python for Data Science For Dummies

Python for Data Science For Dummies
Author: John Paul Mueller,Luca Massaron
Publsiher: John Wiley & Sons
Total Pages: 496
Release: 2019-01-29
ISBN 10: 1119547660
ISBN 13: 9781119547662
Language: EN, FR, DE, ES & NL

Python for Data Science For Dummies Book Review:

The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
Author: Robert Nisbet,Gary Miner,Ken Yale
Publsiher: Elsevier
Total Pages: 822
Release: 2017-11-09
ISBN 10: 0124166458
ISBN 13: 9780124166455
Language: EN, FR, DE, ES & NL

Handbook of Statistical Analysis and Data Mining Applications Book Review:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

A Guide to the Project Management Body of Knowledge (PMBOK(R) Guide-Sixth Edition / Agile Practice Guide Bundle (HINDI)

A Guide to the Project Management Body of Knowledge (PMBOK(R) Guide-Sixth Edition / Agile Practice Guide Bundle (HINDI)
Author: Project Management Institute
Publsiher: Project Management Institute
Total Pages: 756
Release: 2019-08-05
ISBN 10: 1628255390
ISBN 13: 9781628255393
Language: EN, FR, DE, ES & NL

A Guide to the Project Management Body of Knowledge (PMBOK(R) Guide-Sixth Edition / Agile Practice Guide Bundle (HINDI) Book Review:

To support the broadening spectrum of project delivery approaches, PMI is offering A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Sixth Edition as a bundle with its latest, the Agile Practice Guide. The PMBOK® Guide – Sixth Edition now contains detailed information about agile; while the Agile Practice Guide, created in partnership with Agile Alliance®, serves as a bridge to connect waterfall and agile. Together they are a powerful tool for project managers. The PMBOK® Guide – Sixth Edition – PMI's flagship publication has been updated to reflect the latest good practices in project management. New to the Sixth Edition, each knowledge area will contain a section entitled Approaches for Agile, Iterative and Adaptive Environments, describing how these practices integrate in project settings. It will also contain more emphasis on strategic and business knowledge—including discussion of project management business documents—and information on the PMI Talent Triangle™ and the essential skills for success in today's market. Agile Practice Guide has been developed as a resource to understand, evaluate, and use agile and hybrid agile approaches. This practice guide provides guidance on when, where, and how to apply agile approaches and provides practical tools for practitioners and organizations wanting to increase agility. This practice guide is aligned with other PMI standards, including A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Sixth Edition, and was developed as the result of collaboration between the Project Management Institute and the Agile Alliance.

Ten Steps to a Results-Based Monitoring and Evaluation System

Ten Steps to a Results-Based Monitoring and Evaluation System
Author: Jody Zall Kusek,Ray C. Rist
Publsiher: World Bank Publications
Total Pages: 264
Release: 2004-06-15
ISBN 10: 0821389076
ISBN 13: 9780821389072
Language: EN, FR, DE, ES & NL

Ten Steps to a Results-Based Monitoring and Evaluation System Book Review:

This Handbook provides a comprehensive ten-step model that will help guide development practitioners through the process of designing and building a results-based monitoring and evaluation system.

Mining of Massive Datasets

Mining of Massive Datasets
Author: Jure Leskovec,Anand Rajaraman,Jeffrey David Ullman
Publsiher: Cambridge University Press
Total Pages: 476
Release: 2014-11-13
ISBN 10: 1107077230
ISBN 13: 9781107077232
Language: EN, FR, DE, ES & NL

Mining of Massive Datasets Book Review:

Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Python for Data Analysis

Python for Data Analysis
Author: Wes McKinney
Publsiher: "O'Reilly Media, Inc."
Total Pages: 452
Release: 2013
ISBN 10: 1449319793
ISBN 13: 9781449319793
Language: EN, FR, DE, ES & NL

Python for Data Analysis Book Review:

Presents case studies and instructions on how to solve data analysis problems using Python.

Project Management Case Studies

Project Management Case Studies
Author: Harold Kerzner
Publsiher: John Wiley & Sons
Total Pages: 816
Release: 2017-04-11
ISBN 10: 111938916X
ISBN 13: 9781119389163
Language: EN, FR, DE, ES & NL

Project Management Case Studies Book Review:

THE #1 PROJECT MANAGEMENT CASE STUDIES BOOK NOW FEATURING NEW CASES FROM DISNEY, THE OLYMPICS, AIRBUS, BOEING, AND MORE After on-the-job experience, case studies are the most important part of every project manager's training. This Fifth Edition of Project Management Case Studies features more than one hundred case studies that detail projects at high-profile companies around the world. These cases offer you a unique opportunity to experience, first-hand, project management in action within a variety of contexts and up against some of the most challenging conditions any project manager will likely face. New to this edition are case studies focusing on agile and scrum methodologies. Contains 100-plus case studies from companies that illustrate both successful and not-so-successful project management Represents an array of industries, including medical and pharmaceutical, aerospace, entertainment, sports, manufacturing, finance, telecommunications, and more Features 18 new case studies, including high-profile cases from Disney, the Olympics, Boeing 787 Dreamliner, and Airbus 380 Follows and supports preparation for the Project Management Professional (PMP)® Certification Exam Experienced PMs, project managers in training, and students alike will find this book to be an indispensable resource whether used as a standalone or combined with the bestselling Project Management: A Systems Approach to Planning, Scheduling, and Controlling, 12th Edition. PMI, CAPM, PMBOK, PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.