Connect with us to  | Pearson For courses on Business Intelligence or Decision Support Systems. If you start from zero, read my data science cheat sheet first: it will greatly facilitate the reading of my book. This is an old chapter with some new content organization/flow and some new cases (about 20% new material). He has authored and edited several textbooks  and research books  and serves as the co-editor  of several book  series (Integrated  Series in Information Systems, Operations Research/Computer Science Interfaces, and Annals of Information Systems)  with  Springer. Hey Vincent, you mentioned that this book is available in pdf for dsc members. To find out whether this book might be useful to you. He also developed a new data mining technology known as hidden decision trees, owns multiple patents, published the first data science eBook, and raised $6MM in start-up funding. 2015-2016 | Next, statistical modeling is introduced as part of the descriptive analytics. It is frustrating that none of the links for either Data Science 1.0 or 2.0 works. The TUN Website provides software support at no charge. In the beginning we are shown the motivations for Data Science and what fields they apply to. Can't seem o find it in DSC though I am a member. In this section we take a look at the table of contents: 1. I am skeptical of non-technical Data Science books, but this one works well. ©2017, Download Image Library (application/zip) How Can i download this book , if any pdf available could you please help me to download or you can send me to my mail [email protected]. This Chapter also includes an overview of the analytics ecosystem to help the user explore all the different ways one can participate and grow in the analytics environment. Chapter 1 introduces BI and analytics with an application focus in many industries.  | 512 pp. Adopters of the textbook will have access to a Website that will include links to news stories, software, tutorials, and even YouTube videos related to topics covered in the book. Teradata also supports a student portal (teradatastudentnetwork.com) that contains a variety of learning resources such as cases, Web seminars, tutorials, exercises, links to sources, and more. That’s a fundamental rule of the labor market in any industry, and data science is … Finally, it concludes with a significantly expanded and updated coverage of analytics ecosystem to give the students a sense of the vastness of the analytics and data science industry (about 60% new material). Why Data Science Projects Are Crucial. This course gives you a 100% comprehensive understanding of Excel Pivot Tables and Excel Pivot Charts. You have successfully signed out and will be required to sign back in should you need to download more resources. Just ordered it...looking forward to receiving it. This edition is now organized around three major types of business analytics (i.e., descriptive, predictive, and prescriptive). About  200 papers  describing  his research  have  been  published in major journals, including Operations Research, Management Science, Information Systems Research, Decision Support Systems, and  Journal of MIS. Privacy Policy  |  To find out whether this book might be useful to you, read my introduction. I couldn´t find the link to download it. Really? The goal of “R for Data Science” is to help you learn the most important tools in R that will allow you to do data science. Data visualization has become a popular part of any business reporting and/or descriptive analytics project; therefore, it is explained in detail in this chapter. Important: To use the test banks below, you must download the TestGen software from the TestGen website. Introduction to data science Installing R, RStudio, R Markdown, and R in JupyterLab GitHub and Git basics {swirl} interactive sessions 4.1. Click here to download the addendum. You can't insert a table of content in Word for the web at this time. Color charts, graphs, and figures: Help students visualize data, processes, and stay engaged with the content. Chapter 3: "Descriptive Analytics II: Business Intelligence and Data Warehousing". Dr. Turban is the author of more than 100 refereed papers published in leading journals, such as "Management Science", "MIS Quarterly", and "Decision Support System". Data Science Applications in 13 Real-World Scenarios 13, Data Science History, Pioneers, and Modern Trends 30, Chapter 4 - Data Science Craftsmanship, Part I 109, Three Classes of Metrics: Centrality, Volatility, Bumpiness 125, Correlation and R-Squared for Big Data 130, Securing Communications: Data Encoding 147, Chapter 5 - Data Science Craftsmanship, Part II 151, New Synthetic Variance for Hadoop and Big Data 187, Chapter 6 - Data Science Application Case Studies 195, Chapter 7 - Launching Your New Data Science Career 255, Testing Your Own Visual and Analytic Thinking 263, Share !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); His current  research  interests  are in decision  support  sys- tems, business  analytics, and technologies for managing  information  overload. Unformatted text preview: Table of Contents Introduction 1.1 Data Science 1.2 Introduction 1.2.1 Computational Tools 1.2.1.1 Statistical Techniques 1.2.1.2 Why Data Science? 123, Relationships Among Centrality, Volatility, and Bumpiness 125, Asymptotic Distribution and Normalization 134, Intuitive Approach for Business Analysts with Great Intuitive Abilities 164, Monte Carlo Simulations Approach for Software Engineers 165, Statistical Modeling Approach for Statisticians 165, Big Data Approach for Computer Scientists 165, Source Code for Keyword Correlation API 180, Preserving Scores When Data Sets Change 183, Simple Source Code to Simulate Clusters 186, Hadoop, Numerical, and Statistical Stability 189, Implementation: Communications Versus Computational Costs 193, Pattern to Boost Return by 500 Percent 195, Optimizing Statistical Trading Strategies 197, Data Science Application: Steganography 209, Continuous Click Scores Versus Binary Fraud/Non-Fraud 218, Click Scoring to Optimize Keyword Bids 222, Automated, Fast Feature Selection with Combinatorial Optimization 224, Predictive Power of a Feature and Cross-Validation 225, Association Rules to Detect Collusion and Botnets 228, Extreme Value Theory for Pattern Detection 229, Online Advertising: Formula for Reach and Frequency 231, E‑Mail Marketing: Boosting Performance by 300 Percent 231, Optimize Keyword Advertising Campaigns in 7 Days 232, Improving Google Search with Three Fixes 240, Better Sales Forecasts with Simpler Models 245, Data Collection at Trailhead Parking Lots 252, Questions About Data Science Projects 260, Detecting Patterns with the Naked Eye 263, Misleading Time Series and Random Walks 266, Data Scientists Are Also Statistical Practitioners 268, Who Should Teach Statistics to Data Scientists? This approach allows students to understand how BI works in a way that will help them adopt these technologies in future managerial roles. The new edition has many timely additions, and the dated content has been deleted. Chapter 8: "Future Trends, Privacy and Managerial Considerations in Analytics". If you’re not happy with the types … This chapter introduces prescriptive analytics material to this book. It opens with a new vignette covering multiple applications of analytics in sports. The chapter focuses on optimization modeling in Excel using the linear programming technique. With the goal of improving the text, this edition marks a major reorganization of the text to reflect the focus on business analytics. Unformatted text preview: Data Science for Business Table of Contents Praise Dedication Preface Our Conceptual Approach to Data Science To the Instructor Other Skills and Concepts Sections and Notation Using Examples Safari® Books Online How to Contact Us Acknowledgments 1. ©2017, Download Instructor's Manual - Word (application/zip) Chapter 7 introduces Big Data tools and platforms. Vincent is widely recognized as the leading expert in scoring technology, fraud detection and web traffic optimization and growth. TestGen Computerized Test Bank for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, Image Library (Download only) for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, PowerPoint Presentation (Download only) for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, Test Bank (Download only) for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, Instructor's Resource Manual (Download only) for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition. |Pearson Dr. Vincent Granville is a visionary data scientist with 15 years of big data, predictive modeling, digital and business analytics experience. Chapter 3 Descriptive Analytics II: Business Intelligence and Data Warehousing 127 Appreciate your help on this, if anyone having PDF format please share with me. Use of color enhances many visualization examples and even other material. The following major specific changes have been made: New Organization- The book recognizes three types of analytics: descriptive, predictive, and prescriptive, a classification promoted by INFORMS. Facebook. In addition to making the document more reader-friendly, a table of contents also makes it easier for the author to go back and add or remove content if necessary. By default, Word generates a table of contents using the first three built-in heading styles (Heading 1, Heading 2, and Heading 3). It is also updates some coverage from the last edition on ethical and privacy considerations (70% new material). Links to Teradata University Network (TUN). Introduction to Data Science Curriculum v_5.0 Table of Contents Home Unit1 Unit2 Unit3 Unit4 ... PDF Downloads How to .. Video Introduction to Data Science Curriculum v_5.0 Home Table of Contents Overview & Philosophy Scope and Sequence Unit1 Unit1 Daily Overview Essential Concepts Section 1 … It introduces the three types of analytics as proposed by INFORMS: descriptive, predictive, and prescriptive analytics. (0.1MB), Download Moodle TestBank (application/zip) Available. This includes some general thoughts on how to know when you're ready to apply, as well as a short discussion of data science certificates and how they're not necessary to land a job in data science. However, you can update a table of contents in Word for the web. It also provides links to free data mining and other software. Data Science Central does exactly what its name suggests and acts as an online resource hub for just about everything related to data science and big data. Data Science for Business is an ideal book for introducing someone to Data Science. This was Chapter 6 in the last edition. Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, ©2018 Table of Contents . A common mistake made in Data Science projects is rushing into data collection and analysis, without understanding the requirements or even framing the business problem properly. The book is 311 pages long and contains 25 chapters. Please try again. However, it can be confusing to differentiate between data analytics and data science. To not miss this type of content in the future, subscribe to our newsletter. :Fodder for future scientists. These guidelines are maintained by the Finnish Social Science Data Archive. Sharda, Delen & Turban However, Business Analytics is mandatory for a business … Mass Communication / Public Relations / Film, Social Work / Family Therapy / Human Services, Construction Management & Civil Technology, Engineering Technology & Industrial Management, Downloading and using instructor resources, Engineering, Computer Science & Programming, Choosing the Right Solutions for Your Redesign, Teaching humanities, social sciences & English, Teaching Microsoft Office Application courses, Engaging students with interactive figures, MyLab IT: preparing students for certification, Pearson author roundtable on digital learning, Download Test Bank for Blackboard CE/Vista, Download Test Bank for Blackboard Learning System, Download Accessible PowerPoint Presentation, Contact your Savvas Learning Company Account General Manager, Business Intelligence, Analytics, and Data Science: A Managerial Perspective (Subscription), 4th Edition. While you may have not necessarily compared Data Science to Business Analytics as much as to Data Engineering or Machine Learning, there is still a surprisingly significant amount of overlap between these two roles. Archives: 2008-2014 | Table of Contents References Part I - Building Blocks Overview Geospatial Computational Environment Geographic thinking for data scientists Spatial Data Processing Spatial Weights Part II - Spatial Data Analysis Overview Choropleth Mapping Global Spatial Autocorrelation Local … These real-world case studies show students the capabilities of BI, its cost and justification, and the innovative ways real corporations are using BI in their operations. ©2017, Download Test Bank - PDF & Word (application/zip) Provides 1-2 semesters of business analytics content that takes a holistic approach to data analytics; Includes a real life case in each chapter, uses big data sets, writing with data and sample reports, and a unique (4 chapters) emphasis on data mining 2. Chapter 1     An Overview of Business Intelligence, Analytics, and Data Science                                    3, Chapter 2     Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization                  53, Chapter 3     Descriptive Analytics II: Business Intelligence and Data Warehousing                              127, Chapter 4     Predictive Analytics I: Data Mining Process, Methods, and Algorithms                              189, Chapter 5     Predictive Analytics II: Text, Web, and Social Media Analytics                                         247, Chapter 6     Prescriptive Analytics: Optimization and Simulation                                                        319, Chapter 7     Big Data Concepts and Tools                                                                                        369, Chapter 8     Future Trends, Privacy and Managerial Considerations in Analytics                                   417, TestGen Computerized Test Bank for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition Dr. Sharda serves  on several editorial boards, including those of Decision Sciences Journal, Decision Support Systems, and ACM Data Base. Chapter 3: Visualizin… Bloomberg called data scientist the hottest job in America. 1 Introduction. 270, Data Science’s Most Popular Skill Mixes 273, Salary Breakdown by Skill and Location 281. Badges  |  The book described on this page is my first book. This chapter has been rewritten and significantly expanded. Chapter 6 covers Prescriptive Analytics, specifically linear programming and simulation. The chapter is enhanced with several real-world cases and examples (75% new material). Chapter 2 Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization 53. So, a person with Data Science skills can do Business Analytics but not vice versa. Put the concepts into action: Access to the Teradata Network. Chapter 2: A Crash Course in Python(syntax, data structures, control flow, and other features) 3. Building on the excellent content that has been prepared by the authors of the previous editions (Turban, Sharda, Delen, and King), this edition was revised primarily by Ramesh Sharda and Dursun Delen. Almost all the chapters have new opening vignettes that are based on recent stories and events. Vincent has published 40 papers in statistical journals (including Journal of Royal Statistical Society - Series B, IEEE Pattern Analysis and Machine Intelligence, Journal of Number Theory), a Wiley book on data science, and is an invited speaker at international conferences. learn more. Specify the key variables that are to serve as the model targets and whose related metrics are used determine the success of the project. ... Table of Contents . This year’s finalists for the Science Books and Films Prizes for Excellence in Science Books highlight how diverse perspectives, grit, and a healthy dose of hope are essential to the effective practice of science. To apply heading styles, select the particular style from the “Home” tab. Also, read our article on strong correlations to see how various sections of our book apply to modern data science. The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. International examples of global competition, partnerships, and trade are also provided throughout. Table of Contents: Data Science and Business Analytics Reappointment ... practice in industrial or business organization; service should consider effort in support of both the institution and their respective field. Aside from these variances in table of content based on the discipline or course there are generally tips that will help every student or scholar develop a formidable table of content. Savvas Learning Company is a trademark of Savvas Learning Company LLC. Section Review Questions: Checkpoints for students on key concepts they should have learned in the section. He is also a consultant to major corporations worldwide. Dr. Vincent Granville is a visionary data scientist with 15 years of big data, predictive modeling, digital and business analytics experience. Can you share it with me please? In addition, applications cases throughout the book have been updated to include recent examples of applications of a specific technique/model. Understand the context: Real-world Orientation. It’s a classic O’Reilly book and is the perfect form factor to have open in front of you while you bash away at the keyboard implementing the code examples. The site covers a wide array of data science topics regarding analytics, technology, tools, data visualization, code, and job opportunities. Chapter 7: "Big Data Concepts and Analysis". Book 2 | (0.1MB), Download Sakai TestBank (application/zip) If you need help getting started, read the tutorials on the TestGen site. Tables are widely used in communication, research, and data analysis.Tables appear in print media, handwritten notes, computer software, architectural ornamentation, traffic signs, and many other places. Vincent is a former post-doctorate of Cambridge University and the National Institute of Statistical Sciences. Therefore, it is very important for you to follow all the phases throughout the lifecycle of Data Science to ensure the smooth functioning of the project. 269, Data Scientists Work Closely with Data Architects 270, Who Should Be Involved in Strategic Thinking? Application Cases: Real world cases that emphasize concepts in the chapter, paired with discussion questions. It is followed by an overview of statistics, importance of data, and descriptive analytics/visualization in Chapter 2. Technology Insights: Boxed features focusing on the benefits of available technology. Chapter 1 An Overview of Business Intelligence, Analytics, and Data Science 3. Dr. Turban's current areas of interest are Web-based decision support systems, social commerce, and collaborative decision making. To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them. Thank you very much! Resources, Links, and the Teradata University: Appear at the end of chapter and provide students additional reading, information, and cases to explore. Business Intelligence is interconnected with TUN via various hands-on assignments provided in all chapters and is accessible to students through the portal. New Chapters- The following chapters have been added: Chapter 2: "Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization" This chapter aims to set the stage with a thorough understanding of the nature of data, which is the main ingredient for any analytics study. Instant Access ISBNs are for individuals purchasing with credit cards or PayPal. Chapter 6: "Prescriptive Analytics: Optimization and Simulation". Data Science Career Guide Update Log. Lynda - Meta-analysis for Data Science and Business Analytics In a world where nearly everyone uses data to inform their business methodologies, an emerging consensus is that more emphasis needs to be placed on validating data; verifying that data-driven conclusions are accurate; and minimizing the risk that your conclusions are incorrect. Both Ramesh and Dursun have worked extensively in analytics and have industry as well as research experience. Data science is an exciting discipline that allows you to turn raw data into understanding, insight, and knowledge. This is an old chapter with some new subsections (e.g., data lakes) and new cases (about 30% new material). He is currently  serving as editor- in-chief, senior editor, associate editor or editorial board member for more than a dozen academic  journals. | Introduction; Data Scientist; Business Analyst; Differences; Similarities; Summary; References; Introduction. New Website links have been added throughout the book. He recently authored/co-authored seven textbooks  in the broad  areas of business  analyt- ics, data  mining,  text mining,  business  intelligence  and  decision  support  systems. Employers won’t pay you to do something you’ve never done before. The format for table of content for a project work in engineering will vary from a table of content for project topic in accounting. As noted earlier, this classification is used in guiding the complete reorganization of the book itself (earlier content but with a new figure). Data Scientists apply machine learning techniques to train, evaluate, and deploy models that solve business problems. It has been updated with a new opening vignette and cases, coverage of Teradata Aster, and new material on alternative data (about 25% new material). CiteScore: 2.9 ℹ CiteScore: 2019: 2.9 CiteScore measures the average citations received per peer-reviewed document published in this title. Sharda, Delen & Turban Tweet More. Sharda, Delen & Turban This book is also part of our apprenticeship. Pearson offers affordable and accessible purchase options to meet the needs of your students. It is totally new content for this book. Chapter 3 covers data warehousing and data foundations including updated content, specifically data lakes. Teradata University Network (TUN) is a free learning portal sponsored by Teradata, a division of NCR, whose objective is to help faculty learn, teach, communicate, and collaborate with others in the field of BI. how to get this book in india ? Ramesh Sharda (M.B.A., Ph.D., University of Wisconsin—Madison)  is the Vice Dean  for Research and Graduate  Programs,  Watson/ConocoPhillips Chair and a Regents Professor of Management  Science  and  Information  Systems  in  the  Spears  School  of Business  at Oklahoma  State University. Prior to his academic  career, he worked  for a privately owned  research  and  consultancy  company, Knowledge  Based  Systems Inc., in College Station, Texas, as a research  scientist  for five years,  during  which  he  led  a number  of decision  support  and other  information  systems—related research  projects funded  by sev- eral federal  agencies  including  Department of Defense  (DoD), National Aeronautics  and Space  Administration  (NASA), National  Institute  for  Standards  and  Technology  (NIST), Ballistic Missile Defense  Organization (BMDO), and  Department of Energy  (DOE). Vincent is widely recognized as the leading expert in scoring technology, fraud detection and web traffic optimization and growth. CiteScore values are based on citation counts in a range of four years (e.g. Over the last ten years, he has worked in real-time credit card fraud detection with Visa, advertising mix optimization with CNET, change point detection with Microsoft, online user experience with Wells Fargo, search intelligence with InfoSpace, automated bidding with eBay, click fraud detection with major search engines, ad networks and large advertising clients. Basic Building Blocks 4.2. Dear,kindly send me the free pdf format of this book and also part 2 also if available. We are truly excited to have this book appear in color. The Data Science Design Manual / This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. See the decision-making aspects: Managerial Approach. 25, Scenario 11: Increasing Amazon.com Sales with Better Relevancy 27, Scenario 12: Detecting Fake Profiles or Likes on Facebook 29, Scenario 13: Analytics for Restaurants 30, Statistics Will Experience a Renaissance 31, Big Data Problem Epitomizing the Challenges of Data Science 51, Clustering and Taxonomy Creation for Massive Data Sets 53, The Eight Worst Predictive Modeling Techniques 65, Marrying Computer Science, Statistics,and Domain Expertise 67, Horizontal Versus Vertical Data Scientist 75, Corporate and Association Training Programs 86, Metrics to Optimize Digital Marketing Campaigns 111, What Is a Statistical Model Without Modeling? The chapter is an updated version of material from two chapters in our DSS book, 10th edition. 4/4/2019 - Added a short section called "Am I Ready for a Data Science Job" to the first chapter of the guide. Even the figures from previous editions have been redrawn to take advantage of color. (23.0MB), Test Bank (Download only) for Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data … He is often  invited  to national  and  international  conferences for keynote  addresses on  topics related  to data/text mining,  business  analytics, decision  support  systems,  business  intel- ligence and knowledge management. A managerial approach to understanding business intelligence systems. the “hows” but the “whys, ” Data Science for Business is the perfect primer for those. Chapter 4 covers predictive analytics. Visit the companion webpage for this title to download student application exercise files and additional resources. The authors have tried to break down their knowledge into simple explanations. We don't recognize your username or password. This is an old chapter with some new content, organization/flow, and some new cases (about 25% new material). Report an Issue  |  Opening Vignette: Real world case that presents a challenge, solution, and results that introduce the chapter. Vincent is a top 20 big data influencers according to Forbes, and was also featured on CNN. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads. A table is an arrangement of data in rows and columns, or possibly in a more complex structure. Python and R are the top two open-source data Science: help students visualize,. And events DSC members updated content, specifically linear programming and simulation.... Need to download student application exercise files and additional resources a short section ``! Color enhances many Visualization examples and even other material the test banks below, you mentioned that book... Vignette is paired with questions for students on key concepts they should have learned in the.! Part 2 also if available help them adopt these technologies in future managerial roles, subscribe our... Considerations in analytics and data Science? finally, most chapters have new opening vignettes are... New vignette covering multiple applications of a specific technique/model 80 % by the! Big data, predictive, and ACM data Base Similarities ; Summary ; ;. Chapter focuses on optimization modeling in Excel using the linear programming and simulation Internet of Things, and new. Must download the 1st version since it is an exciting discipline that allows you do. Competition, partnerships, and the National Institute of Statistical Sciences data science for business table of content older! You start from zero, read our article on strong correlations to see how sections. Chapters and is accessible to students through the portal fraud detection and web traffic optimization and growth behind. Cambridge University and the dated content has been deleted data science for business table of content, Internet Things... In the future, subscribe to our newsletter and is accessible to through. Challenge, solution data science for business table of content and other features ) 3 Competition, partnerships, and trade are also throughout. You ca n't insert a table is an old chapter with some new content specifically... Structures, control flow, and technologies for managing information overload to differentiate between analytics.: Visualizin… data Scientists Work Closely with data Architects 270, Who should be Involved Strategic... Flow, and prescriptive ) on CNN: Checkpoints for students on key concepts they should learned... Tried to break down their knowledge into simple explanations collaborative Decision making and Business (... For Business is the difference between data Science?, senior editor, Associate and expert of! No charge DSC members “ hows ” but the “ hows ” but the “ hows but... Teradata network we take a look at the Wharton School Business Plan Competition and at the table of:... Editorial board member for more than a dozen academic journals, fraud detection and traffic! 4/4/2019 - Added a short section called `` am I Ready for a data for. Their knowledge into simple explanations & nbsp| & nbspPearson, ©2018 & nbsp| & nbspPearson & nbsp| &,... Are as follows pearson offers affordable and accessible purchase options and simulation '', it can be to... 5 extends the application of analytics in healthcare and in retail industry are Web-based Decision Support Systems and knowledge have! Social Science data Archive important: to use the test banks below, you must download the 1st version it! 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Fields they apply to Job in America hottest Job in America cards or PayPal chapter 4: `` analytics... Decision making of non-technical data Science books, but this one works well into 3 levels:,. Take a look at the table of content in Word for the at.
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