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The Data Management Body of Knowledge (DAMA-DMBOK2) presents a comprehensive view of the challenges, complexities, and value of effective data management.

Today’s organizations recognize that managing data is central to their success. They recognize data has value and they want to leverage that value. As our ability and desire to create and exploit data has increased, so too has the need for reliable data management practices.

The second edition of DAMA International’s Guide to the Data Management Body of Knowledge updates and augments the highly successful DMBOK1. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by:

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:

Chapters include:

Standardization of data management disciplines will help data management professionals perform more effectively and consistently. It will also enable organizational leaders to recognize the value and contributions of data management activities.

Many Cultures, One Team is an essential aid for anyone who leads, is a member of, consults with, or supports global teams.  Starting from the premise that the concept of team is culturally bound, Catherine Mercer Bing provides guidance for improving team function and performance. Drawing on her extensive experience in supporting global teams, she challenges team leaders and members to reflect on their cultural assumptions – to improve their cultural metacognition – and provides key advice concerning engagement, productivity, and human process interactions on teams.

Global competition is fierce, and the timeframe within which businesses maintain their competitive advantage is now counted in months rather than years. One important source of competitive advantage is human behavior. Team leaders that manage the subtle, but powerful, forces of group dynamics and culture achieve better business outcomes. Team leaders that fail to identify and manage these subtle forces in real-time risk having their plans thwarted.

that stands the test of time, turbulence and change and despite all that has continued to set the standard for

performance and excellence by which other organizations are measured?

These questions and over 150 more equally stimulating and change-provoking questions are raised and explored within this concise text. As senior executives, you always have many areas where you can focus your attention—paths along which you can guide your organization to enable it to ultimately reach its full competitive potential. Guide your organization to its competitive potential by answering the questions within this text and by applying Dr. Ted Marra’s approach to developing a working business model and crystal clear vision.

Dr. Ted Marra has lived and worked in 37 countries during the past 40 years, helping over 155 organizations from virtually every industry and sector. Here is his summary of this first book in the Wisdom Chronicles Series:

This book is really about focus. Forget all the latest theories. To a large extent, the “secrets” to success have never really been secrets. It’s often about getting back to basics—doing the right things for the business and doing them right. This is the essence of what Peter Drucker considers “leadership.” In addition to my hands-on experience, I have read all the thought leaders: Hamel, Porter, Kotter, Collins and more. I have been in conferences all over the world, interacting with the likes of Juran and Welch as well as many others. All of that, plus my own reflections, and distilling it down has been a lifetime pursuit. This book contains that distillation of my observations providing the reader with what I believe are truly the vital few keys to long-term organizational success – competitiveness and profitable growth and overall higher performance across the board.

Are you struggling to understand the data you need to support your business activities?  Are you frustrated over data that don’t answer your questions or provide the wrong answers to your questions?  Are you worried that your organization is not adequately supporting its citizens or customers?  Are you concerned over civil or criminal liability for the quality and use of your data?  If the answer to any of these questions is Yes, they you need to read Data Resource Understanding to help you and everyone in your organization thoroughly understand the data they need to support the business activities.

Most public and private sector organizations have no formal method for thoroughly understanding the data needed to support their business activities.  They seldom have a method that begins with the organization’s perception of the business world and continues through a formal Data Resource Development Cycle to produce a high quality, thoroughly understood data resource that fully supports the organization’s current and future business information demand.

Data Resource Data provided the complete detailed data resource model for understanding and managing data as a critical resource of the organization.  Data Resource Understanding is the companion book to Data Resource Data.  It provides a detailed explanation of how to thoroughly understand an organization’s data resource and to document that understanding with Data Resource Data. Together they provide an organization with the foundation for properly managing their data as a critical resource.

Like Data Resource Simplexity, Data Resource Integration, Data Resource Design, and Data Resource Data, Michael Brackett draws on over half a century of data management experience, in a wide variety of different public and private sector organizations, to understand and document an organization’s data resource.  He leverages theories, concepts, principles, and techniques from many different and varied disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to the process of formally documenting an organization’s data resource.

Object-Role Modeling (ORM) is a fact-based approach to data modeling that expresses the information requirements of any business domain simply in terms of objects that play roles in relationships. All facts of interest are treated as instances of attribute-free structures known as fact types, where the relationship may be unary (e.g. Person smokes), binary (e.g. Person was born on Date), ternary (e.g. Customer bought Product on Date), or longer. Fact types facilitate natural expression, are easy to populate with examples for validation purposes, and have greater semantic stability than attribute-based structures such as those used in Entity Relationship Modeling (ER) or the Unified Modeling Language (UML).

All relevant facts, constraints and derivation rules are expressed in controlled natural language sentences that are intelligible to users in the business domain being modeled. This allows ORM data models to be validated by business domain experts who are unfamiliar with ORM’s graphical notation. For the data modeler, ORM’s graphical notation covers a much wider range of constraints than can be expressed in industrial ER or UML class diagrams, and thus allows rich visualization of the underlying semantics.

Suitable for both novices and experienced practitioners, this book covers the fundamentals of the ORM approach. Written in easy-to-understand language, it shows how to design an ORM model, illustrating each step with simple examples. Each chapter ends with a practical lab that discusses how to use the freeware NORMA tool to enter ORM models and use it to automatically generate verbalizations of the model and map it to a relational database.

What? Another management book? You will find And People? to be refreshingly different. Its Eastern European perspective, enhanced with best practices and research studies, will reveal the secrets for successfully leading and managing people. Part textbook, part handbook, each word is crafted based upon author Ivica Vrancic’s 20 years of experience in management and consulting, which includes working with hundreds of managers from all hierarchy levels.

And People? dares to ask why so many managers spend more time, resources, and consideration on their company cars than the real greatest asset of any business: people. Early chapters explore motivation and organization culture; later, Vrancic examines the challenge of selecting the right people for your organization and developing those people to maximize their strengths. Through practical real-world examples built on respected theoretical foundations, readers will gain new insight into the dual role of both manager and leader.  

And no, a manager and a leader are not the same thing.

From Dave Ulrich’s Foreword:

Ivica does a masterful job in this well written book of simplifying the complex requirements for business success. He offers metaphors and examples of how leadership and management skills both need to exist in a successful business. His insights are particularly helpful in that he adapts them to his experiences in Eastern Europe but shows how they would apply to businesses throughout the world.

The book does a wonderful job with simplicity and clarity. Ivica distils volumes of management ideas into digestible nuggets. He then brings in research from thought leaders with specific findings along with examples that bring his ideas to life. He also makes sure that the reader is responsible to manage the tensions or tradeoffs between leadership and management; between individuals and organizations. Creating and sustaining a successful business is not a linear progression following a how-to guide. Success comes from navigating a more complex set of choices. Ivica offers a thoughtful roadmap that can be used to help executives at any level of a company make informed choices about building a successful organization.

Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in.

The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models.  Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book.

This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections:

In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3.

In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category:

In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16).

This book offers a complete basic course in Fully Communication Oriented Information Modeling (FCO-IM), a Fact Oriented Modeling (FOM) data modeling technique. The book is suitable for self-study by beginner FCO-IM modelers, whether or not experienced in other modeling techniques. An elaborate case study is used as illustration throughout the book.

The book also illustrates how data models in other techniques can be derived from an elementary FCO-IM model. The context of fact oriented modeling is given as well, and perspectives on information modeling indicate related areas of application and further reading.

Fact Oriented Modeling methods (like FCO-IM) have three major advantages over other data modeling techniques:

Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio’s support for agile development, as well as a description of some of ER/Studio’s newer features for NoSQL, such as MongoDB’s containment structure. You will build many ER/Studio data models along the way, applying best practices to master these ten objectives:

This book contains four sections:           

Section I introduces data modeling and the ER/Studio landscape. Learn why data modeling is so critical to software development and even more importantly, why data modeling is so critical to understanding the business. You will learn about the newest features in ER/Studio (including features on big data and agile), and the ER/Studio environment. By the end of this section, you will have created and saved your first data model in ER/Studio and be ready to start modeling in Section II!

Section II explains all of the symbols and text on a data model, including entities, attributes, relationships, domains, and keys. By the time you finish this section, you will be able to ‘read’ a data model of any size or complexity, and create a complete data model in ER/Studio.

Section III explores the three different levels of models: conceptual, logical, and physical. A conceptual data model (CDM) represents a business need within a defined scope. The logical data model (LDM) represents a detailed business solution, capturing the business requirements without complicating the model with implementation concerns such as software and hardware. The physical data model (PDM) represents a detailed technical solution. The PDM is the logical data model compromised often to improve performance or usability. The PDM makes up for deficiencies in our technology. By the end of this section you will be able to create conceptual, logical, and physical data models in ER/Studio.

Section IV discusses additional features of ER/Studio. These features include data dictionary, data lineage, automating tasks, repository and portal, exporting and reporting, naming standards, and compare and merge functionality.