Master Data Management in Practice

Master Data Management in Practice

In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach.

Author: Dalton Cervo

Publisher: John Wiley & Sons

ISBN: 9780470910559

Category: Business & Economics

Page: 272

View: 918

In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM.
Categories: Business & Economics

Multi Domain Master Data Management

Multi Domain Master Data Management

Mark is the coauthor of Master Data Management in Practice: Achieving True
Customer MDM (John Wiley & Sons, 2011), has been a speaker at data
governance and information quality conferences, and has served on various
customer ...

Author: Mark Allen

Publisher: Morgan Kaufmann

ISBN: 9780128011478

Category: Computers

Page: 244

View: 905

Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data.
Categories: Computers

COBIT 5 Enabling Information

COBIT 5  Enabling Information

Replicate master data values only from the database of record. • There must be a
set of data classification guidelines, information model guidelines, data integrity
policies, data security, and governance and management practice guidelines.

Author: ISACA

Publisher: ISACA

ISBN: 9781604203493

Category:

Page: 90

View: 315

Categories:

Handbook of Data Quality

Handbook of Data Quality

An important finding came from a survey of master data management practices in
different operating units. The survey found that over 2,000 people had update
access to master data in ERPs but were managing master data mostly on a ...

Author: Shazia Sadiq

Publisher: Springer Science & Business Media

ISBN: 9783642362576

Category: Computers

Page: 438

View: 195

The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.
Categories: Computers

Microsoft SQL Server 2008 R2 Master Data Services

Microsoft SQL Server 2008 R2 Master Data Services

In recent years, however, a body of practice has emerged that is aptly named “
master data management,” or MDM. Practitioners don't stop atjust compiling a
reference data set, but implement architectures, data-driven processes, practices,
and ...

Author: Tyler Graham

Publisher: McGraw Hill Professional

ISBN: 9780071756242

Category: Computers

Page: 352

View: 284

Best Practices for Deploying and Managing Master Data Services (MDS) Effectively manage master data and drive better decision making across your enterprise with detailed instruction from two MDS experts. Microsoft SQL Server 2008 R2 Master Data Services Implementation & Administration shows you how to use MDS to centralize the management of key data within your organization. Find out how to build an MDS model, establish hierarchies, govern data access, and enforce business rules. Legacy system integration and security are also covered. Real-world programming examples illustrate the material presented in this comprehensive guide. Create a process-agnostic solution for managing your business domains Learn how to take advantage of the data modeling capabilities of MDS Manage hierarchies and consolidations across your organization Import data by using SQL Server Integration Services and T-SQL statements Ensure data accuracy and completeness by using business rules and versioning Employ role-based security at functional, object, and attribute levels Design export views and publish data to subscribing systems Use Web services to progrmmatically interact with your implementation
Categories: Computers

Microsoft SQL Server 2012 Master Data Services 2 E

Microsoft SQL Server 2012 Master Data Services 2 E

In recent years, however, a body of practice has emerged that is aptly named “
master data management,” or MDM. Practitioners don't stop at just compiling a
reference data set, but implement architectures, data-driven processes, practices,
 ...

Author: Tyler Graham

Publisher: McGraw Hill Professional

ISBN: 9780071797863

Category: Computers

Page: 416

View: 928

Deploy and Maintain an Integrated MDS Architecture Harness your master data and grow revenue while reducing administrative costs. Thoroughly revised to cover the latest MDS features, Microsoft SQL Server 2012 Master Data Services, Second Edition shows how to implement and manage a centralized, customer-focused MDS framework. See how to accurately model business processes, load and cleanse data, enforce business rules, eliminate redundancies, and publish data to external systems. Security, SOA and Web services, and legacy data integration are also covered in this practical guide. Install Microsoft SQL Server 2012 Master Data Services Build custom MDS models and entityspecific staging tables Load and cleanse data from disparate sources Logically group assets into collections and hierarchies Ensure integrity using versioning and business rules Configure security at functional, object, and attribute levels Extend functionality with SOA and Web services Facilitate collaboration using the MDS Excel Add-In Export data to subscribing systems through SQL views
Categories: Computers

SAP Master Data Governance

SAP Master Data Governance

Ready to improve the handling of your master data? Walk through implementing, configuring, and using SAP Master Data Governance (SAP MDG)!

Author: Homiar Kalwachwala

Publisher: SAP PRESS

ISBN: 1493218352

Category: Computers

Page: 772

View: 815

Ready to improve the handling of your master data? Walk through implementing, configuring, and using SAP Master Data Governance (SAP MDG)! Whether your organization requires custom applications or works with out-of-the-box central governance, consolidation, and mass processing, you'll find detailed instructions for every step. From data, process, and UI modeling to data replication, master your data! Highlights include: 1) Deployment 2) Data modeling 3) Process modeling 4) Data quality 5) Data replication 6) Data migration 7) Consolidation 8) Operations 9) Mass processing 10) Integrations 11) Extensions 12) Analytics
Categories: Computers

Master Data Management and Customer Data Integration for a Global Enterprise

Master Data Management and Customer Data Integration for a Global Enterprise

Using this integrated data approach, the advanced sales management system
would be able to recognize the individual as a high-potential-value ... There are
some industry-specific marketing areas, though, e.g. Communities of Practice.

Author: Alex Berson

Publisher: McGraw Hill Professional

ISBN: 9780071510899

Category: Computers

Page: 406

View: 905

Transform your business into a customer-centric enterprise Gain a complete and timely understanding of your customers using MDM-CDI and the real-world information contained in this comprehensive volume. Master Data Management and Customer Data Integration for a Global Enterprise explains how to grow revenue, reduce administrative costs, and improve client retention by adopting a customer-focused business framework. Learn to build and use customer hubs and associated technologies, secure and protect confidential corporate and customer information, provide personalized services, and set up an effective data governance team. You'll also get full details on regulatory compliance and the latest pre-packaged MDM-CDI software solutions. Design and implement a dynamic MDM-CDI architecture that fits the needs of your business Implement MDM-CDI holistically as an integrated multi-disciplinary set of technologies, services, and processes Improve solution agility and flexibility using SOA and Web services Recognize customers and their relationships with the enterprise across channels and lines of business Ensure compliance with local, state, federal, and international regulations Deploy network, perimeter, platform, application, data, and user-level security Protect against identity and data theft, worm infection, and phishing and pharming scams Create an Enterprise Information Governance Group Perform development, QA, and business acceptance testing and data verification
Categories: Computers

Information Systems Management in Practice

Information Systems Management in Practice

The master reference data integrates these distributed components . ...
management . These warehouses focus on the big picture of the company and
contain data from internal and external sources that can be “ sliced and diced "
with drill ...

Author: Barbara Canning McNurlin

Publisher: Prentice Hall

ISBN: UVA:X004708786

Category: Business & Economics

Page: 582

View: 141

For use as a capstone course text in MIS and in Management of Information Technology/Systems Courses. This text deals with the management of information technology (IT) as it is being practiced in organizations today. Its emphasis is on the current material that information systems executives find important, and organizes it around a framework that provides guidance to students. In this sixth edition, the key themes are the Internet economy, the global marketplace, e-enablement, knowledge management and knowledge sharing. It continues to merge theory with practice through case examples of real companies' use of IT.
Categories: Business & Economics

Successful Business Intelligence Second Edition

Successful Business Intelligence  Second Edition

Master Data Management Phillip Russom, director of research at The Data
Warehousing Institute (TDWI), defines master data management (MDM) as
follows: Master data management is the practice of defining and maintaining
consistent ...

Author: Cindi Howson

Publisher: McGraw Hill Professional

ISBN: 9780071809191

Category: Computers

Page: 336

View: 550

Revised to cover new advances in business intelligence—big data, cloud, mobile, and more—this fully updated bestseller reveals the latest techniques to exploit BI for the highest ROI. “Cindi has created, with her typical attention to details that matter, a contemporary forward-looking guide that organizations could use to evaluate existing or create a foundation for evolving business intelligence / analytics programs. The book touches on strategy, value, people, process, and technology, all of which must be considered for program success. Among other topics, the data, data warehousing, and ROI comments were spot on. The ‘technobabble’ chapter was brilliant!” —Bill Frank, Business Intelligence and Data Warehousing Program Manager, Johnson & Johnson “If you want to be an analytical competitor, you’ve got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It’s required reading for quantitatively oriented strategists and the technologists who support them.” —Thomas H. Davenport, President’s Distinguished Professor, Babson College and co-author, Competing on Analytics “Cindi has created an exceptional, authoritative description of the end-to-end business intelligence ecosystem. This is a great read for those who are just trying to better understand the business intelligence space, as well as for the seasoned BI practitioner.” —Sully McConnell, Vice President, Business Intelligence and Information Management, Time Warner Cable “Cindi’s book succinctly yet completely lays out what it takes to deliver BI successfully. IT and business leaders will benefit from Cindi’s deep BI experience, which she shares through helpful, real-world definitions, frameworks, examples, and stories. This is a must-read for companies engaged in – or considering – BI.” —Barbara Wixom, PhD, Principal Research Scientist, MIT Sloan Center for Information Systems Research Expanded to cover the latest advances in business intelligence such as big data, cloud, mobile, visual data discovery, and in-memory computing, this fully updated bestseller by BI guru Cindi Howson provides cutting-edge techniques to exploit BI for maximum value. Successful Business Intelligence: Unlock the Value of BI & Big Data, Second Edition describes best practices for an effective BI strategy. Find out how to: Garner executive support to foster an analytic culture Align the BI strategy with business goals Develop an analytic ecosystem to exploit data warehousing, analytic appliances, and Hadoop for the right BI workload Continuously improve the quality, breadth, and timeliness of data Find the relevance of BI for everyone in the company Use agile development processes to deliver BI capabilities and improvements at the pace of business change Select the right BI tools to meet user and business needs Measure success in multiple ways Embrace innovation, promote successes and applications, and invest in training Monitor your evolution and maturity across various factors for impact Exclusive industry survey data and real-world case studies from Medtronic, Macy’s, 1-800 CONTACTS, The Dow Chemical Company, Netflix, Constant Contact, and other companies show successful BI initiatives in action. From Moneyball to Nate Silver, BI and big data have permeated our cultural, political, and economic landscape. This timely, up-to-date guide reveals how to plan and deploy an agile, state-of-the-art BI solution that links insight to action and delivers a sustained competitive advantage.
Categories: Computers

Performing Information Governance

Performing Information Governance

Depending on how MDM is implemented, it can either be the golden source of
master data or simply a coordinator that tags or ... and registry from both a data
management architectural approach and information governance best practice.

Author: Anthony David Giordano

Publisher: IBM Press

ISBN: 9780133385632

Category: Business & Economics

Page: 672

View: 512

Make Information Governance Work : Best Practices, Step-by-Step Tasks, and Detailed Deliverables Most enterprises recognize the crucial importance of effective information governance. However, few are satisfied with the value of their efforts to date. Information governance is difficult because it is a pervasive function, touching multiple processes, systems, and stakeholders. Fortunately, there are best practices that work. Now, a leading expert in the field offers a complete, step-by-step guide to successfully governing information in your organization. Using case studies and hands-on activities, Anthony Giordano fully illuminates the “who, what, how, and when” of information governance. He explains how core governance components link with other enterprise information management disciplines, and provides workable “job descriptions” for each project participant. Giordano helps you successfully integrate key data stewardship processes as you develop large-scale applications and Master Data Management (MDM) environments. Then, once you’ve deployed an information asset, he shows how to consistently get reliable regulatory and financial information from it. Performing Information Governance will be indispensable to CIOs and Chief Data Officers…data quality, metadata, and MDM specialists…anyone responsible for making information governance work. Coverage Includes Recognizing the hidden development and operational implications of information governance—and why it needs to be integrated in the broader organization Integrating information governance activities with transactional processing, BI, MDM, and other enterprise information management functions Establishing the information governance organization: defining roles, launching projects, and integrating with ongoing operations Performing information governance in transactional projects, including those using agile methods and COTS products Bringing stronger information governance to MDM: strategy, architecture, development, and beyond Governing information throughout your BI or Big Data project lifecycle Effectively performing ongoing information governance and data stewardship operational processes Auditing and enforcing data quality management in the context of enterprise information management Maintaining and evolving metadata management for maximum business value
Categories: Business & Economics

Run Grow Transform

Run Grow Transform

Data management practices have continued to evolve since the 1980s in an
effort to address the full-data lifecycle needs of an enterprise. The data ...
Reference and master data management—managing golden versions and
replicas 7.

Author: Steven Bell

Publisher: CRC Press

ISBN: 9781466581081

Category: Business & Economics

Page: 372

View: 175

Your customers want innovation and value, and they want it now. How can you apply Lean principles and practices throughout your enterprise to drive operational excellence, reduce costs while improving quality, enable efficient growth, and accelerate idea-to-value innovation? Shingo Prize-winning author Steve Bell and other thought leaders show you
Categories: Business & Economics

Data Management a gentle introduction

Data Management  a gentle introduction

The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc.

Author: Bas van Gils

Publisher: Van Haren

ISBN: 9789401805551

Category: Education

Page: 306

View: 128

The overall objective of this book is to show that data management is an exciting and valuable capability that is worth time and effort. More specifically it aims to achieve the following goals: 1. To give a “gentle” introduction to the field of DM by explaining and illustrating its core concepts, based on a mix of theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, as well as results from real-world assignments. 2. To offer guidance on how to build an effective DM capability in an organization.This is illustrated by various use cases, linked to the previously mentioned theoretical exploration as well as the stories of practitioners in the field. The primary target groups are: busy professionals who “are actively involved with managing data”. The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc. Typical roles for which this book is intended: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. The book is divided into three main parts: theory, practice, and closing remarks. Furthermore, the chapters are as short and to the point as possible and also make a clear distinction between the main text and the examples. If the reader is already familiar with the topic of a chapter, he/she can easily skip it and move on to the next.
Categories: Education

Product Information Management

Product Information Management

Theory and Practice Jorij Abraham ... 4.1 Master Data Management The first PIM
process is called Master Data Management. Master Data defines the core
information of the products. Typical master data include its creation date, the
product ...

Author: Jorij Abraham

Publisher: Springer

ISBN: 9783319048857

Category: Business & Economics

Page: 179

View: 630

Product Information Management is the latest topic that companies across the world are deliberating upon. As companies sell online, they are confronted with the fact that not all information necessary to sell their products is available. Where marketing, sales and finance have been core processes of the corporate world for a long time, PIM is a new business process with its own unique implementation and management challenges. The book describes the core PIM processes; their strategic, tactical and operational benefits and implementation challenges. The book has been written for managers, business users as well as students, and illustrates the different concepts with practical cases from companies like Coca Cola, Nikon and Thomas Cook.
Categories: Business & Economics

Information Systems Management in Practice

Information Systems Management in Practice

Enterprise Reference Data . ERD , a separate use of SAP , is the repository for
most master table information in the company . The information includes vendors
, customers , suppliers , people , materials , finance , and control tables .

Author: Ralph H. Sprague

Publisher:

ISBN: 0138479712

Category: Information resources management

Page: 554

View: 739

A text for undergraduate and graduate students in information systems (IS) management who have had at east one IS course. Deals with the management of information technology as it is being practiced in today's organizations, and incorporates some 75 real-life company case examples. Includes review a
Categories: Information resources management

Beyond Big Data

Beyond Big Data

Typical functions applied on metadata are data lineage to understand where the
data is coming from and impact analysis to ... Appropriate, central management of
master data has become a common practice in many enterprises today, with a ...

Author: Martin Oberhofer

Publisher: IBM Press

ISBN: 9780133509816

Category: Computers

Page: 272

View: 377

Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends
Categories: Computers

Open Source Data Warehousing and Business Intelligence

Open Source Data Warehousing and Business Intelligence

Ideal master data management (MDM)—An integral component of any and every
data warehouse, data mart, and/or BI ... a shared definition of master data by
putting policies into practice and ensuring data quality: Data quality management
 ...

Author: Lakshman Bulusu

Publisher: CRC Press

ISBN: 9781466578760

Category: Computers

Page: 432

View: 945

Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW &
Categories: Computers

DAMA DMBOK

DAMA DMBOK

Over 200 experts have invested seven years of research to create this work which provides principles, frameworks, techniques, and vocabulary to better understand and leverage information.

Author: Dama International

Publisher:

ISBN: 1634622340

Category: Database management

Page: 628

View: 761

Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Categories: Database management

Enterprise Information Management in Practice

Enterprise Information Management in Practice

With Fortune 100 consultant Saumya Chaki as your guide, Enterprise Information Management in Practice covers each of these and the other pillars of EIM in depth, which provide readers with a comprehensive view of the building blocks for EIM ...

Author: Saumya Chaki

Publisher: Apress

ISBN: 9781484212189

Category: Computers

Page: 197

View: 431

Learn how to form and execute an enterprise information strategy: topics include data governance strategy, data architecture strategy, information security strategy, big data strategy, and cloud strategy. Manage information like a pro, to achieve much better financial results for the enterprise, more efficient processes, and multiple advantages over competitors. As you’ll discover in Enterprise Information Management in Practice, EIM deals with both structured data (e.g. sales data and customer data) as well as unstructured data (like customer satisfaction forms, emails, documents, social network sentiments, and so forth). With the deluge of information that enterprises face given their global operations and complex business models, as well as the advent of big data technology, it is not surprising that making sense of the large piles of data is of paramount importance. Enterprises must therefore put much greater emphasis on managing and monetizing both structured and unstructured data. As Saumya Chaki—an information management expert and consultant with IBM—explains in Enterprise Information Management in Practice, it is now more important than ever before to have an enterprise information strategy that covers the entire life cycle of information and its consumption while providing security controls. With Fortune 100 consultant Saumya Chaki as your guide, Enterprise Information Management in Practice covers each of these and the other pillars of EIM in depth, which provide readers with a comprehensive view of the building blocks for EIM. Enterprises today deal with complex business environments where information demands take place in real time, are complex, and often serve as the differentiator among competitors. The effective management of information is thus crucial in managing enterprises. EIM has evolved as a specialized discipline in the business intelligence and enterprise data warehousing space to address the complex needs of information processing and delivery—and to ensure the enterprise is making the most of its information assets.
Categories: Computers

Practical Guide to Clinical Data Management Third Edition

Practical Guide to Clinical Data Management  Third Edition

Some of the documents created as part of clinical data management need to be
submitted to the trial master file (TMF). ... many companies consider study
validation documents to be good clinical practice (GCP) records (see also
Chapter 5).

Author: Susanne Prokscha

Publisher: CRC Press

ISBN: 9781439848319

Category: Computers

Page: 296

View: 238

The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then, the third edition of Practical Guide to Clinical Data Management includes important updates to all chapters to reflect the current industry approach to using electronic data capture (EDC) for most studies. See what’s new in the Third Edition: A chapter on the clinical trial process that explains the high level flow of a clinical trial from creation of the protocol through the study lock and provides the context for the clinical data management activities that follow Reorganized content reflects an industry trend that divides training and standard operating procedures for clinical data management into the categories of study startup, study conduct, and study closeout Coverage of current industry and Food and Drug Administration (FDA) approaches and concerns The book provides a comprehensive overview of the tasks involved in clinical data management and the computer systems used to perform those tasks. It also details the context of regulations that guide how those systems are used and how those regulations are applied to their installation and maintenance. Keeping the coverage practical rather than academic, the author hones in on the most critical information that impacts clinical trial conduct, providing a full end-to-end overview or introduction for clinical data managers.
Categories: Computers