Data Model Scorecard
DOWNLOAD
Download Data Model Scorecard PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Model Scorecard book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Model Scorecard
DOWNLOAD
Author : Steve Hoberman
language : en
Publisher: Technics Publications
Release Date : 2015-11-01
Data Model Scorecard written by Steve Hoberman and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-01 with Computers categories.
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: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data 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).
Data Management Fundamentals Dmf Cdmp Exam Preparation
DOWNLOAD
Author : Paul Rakké
language : en
Publisher: Van Haren
Release Date : 1970-01-01
Data Management Fundamentals Dmf Cdmp Exam Preparation written by Paul Rakké and has been published by Van Haren this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970-01-01 with Architecture categories.
Besides this Data Management Fundamentals (DMF) CDMP exam preparation book, you are advised to obtain the publication the Data Management courseware based on CDMP Fundamentals - Revised edition (ISBN: 9789401811491) for your preparation for your Certified Data Management Professional (CDMP) certification. This CDMP certification based on the DAMA DMBok (Data Management Body of Knowledge) is a globally recognized credential that validates the knowledge and skills required in the field of data management.This exam preparation book is a well-balanced guide to help you pass the CDMP exam and earn your certification. All the knowledge areas as described in the related courseware and/or DAMA-DMBOK (2nd edition) of the well-known study book plus extra topics as described in the book too, will be treated with exam-like questions. The number of questions per topic can differ, depending on the weights as used in the formal exam composition. All the questions are newly defined questions by the author. Separately the correct answers and guiding explanations with references to the DAMA-DMBOK book are provided. Besides the set of questions per topic which consist of a set of 140 questions, also a set of 100 extra questions with the same weights per topic is provided to give you the opportunity to prepare yourself on the exam with this similar exam. So this 240 new questions provided in this book make your road to the CDMP certification complete.
The Digital Financial Revolution In China
DOWNLOAD
Author : David Dollar
language : en
Publisher: Bloomsbury Publishing USA
Release Date : 2022-05-10
The Digital Financial Revolution In China written by David Dollar and has been published by Bloomsbury Publishing USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-10 with Business & Economics categories.
Describes how China is in the lead in transforming finance for the digital age This book is the product of a joint research project between economists at the National School of Development, especially the affiliated Institute of Digital Finance, at Peking University and at the Brookings Institution. It investigates the impact of financial technology on job creation, income distribution, and consumer welfare in China. It also examines larger systemic issues such as monetary policy, stability of the banking sector, and international trade and payments.
Executing Data Quality Projects
DOWNLOAD
Author : Danette McGilvray
language : en
Publisher: Academic Press
Release Date : 2021-05-27
Executing Data Quality Projects written by Danette McGilvray and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-27 with Computers categories.
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
Performance Dashboards
DOWNLOAD
Author : Wayne W. Eckerson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-10-13
Performance Dashboards written by Wayne W. Eckerson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-13 with Business & Economics categories.
Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution.
Machine Learning For Decision Makers
DOWNLOAD
Author : Patanjali Kashyap
language : en
Publisher: Apress
Release Date : 2018-01-04
Machine Learning For Decision Makers written by Patanjali Kashyap and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-04 with Computers categories.
Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book usescase studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.
Monthly Bulletin Of The Robert Morris Associates
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1994
Monthly Bulletin Of The Robert Morris Associates written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Bank loans categories.
Simplify Your Ai Journey Ensuring Trustworthy Ai With Ibm Watsonx Governance
DOWNLOAD
Author : Deepak Rangarao
language : en
Publisher: IBM Redbooks
Release Date : 2025-02-18
Simplify Your Ai Journey Ensuring Trustworthy Ai With Ibm Watsonx Governance written by Deepak Rangarao and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Computers categories.
IBM® watsonxTM is the IBM strategic AI and Data platform. This book focuses on watsonx.governance, one of the three main components of the platform. IBM watsonx.governance offers a comprehensive solution for governing data and AI workloads within a secure and scalable environment. Built on an open architecture, it empowers organizations to manage data access, compliance, and security across hybrid multi-cloud deployments. IBM watsonx.governance simplifies data governance with built-in automation tools and integrates seamlessly with existing databases and tools, streamlining workflows and enhancing user experience. This IBM Redbooks publication provides a broad understanding of watsonx.governance concepts and architecture, and the services that are available in the product. In addition, several common use cases and scenarios are included that should help you better understand the capabilities of this product. This publication is for watsonx customers who seek best practices and real-world examples of how to best implement their solutions while optimizing the value of their existing and future technology, AI, data, and skills investments.
The Journal Of Commercial Lending
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1995-03
The Journal Of Commercial Lending written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-03 with Bank loans categories.
Data Modeling Master Class Training Manual
DOWNLOAD
Author : Steve Hoberman
language : en
Publisher:
Release Date : 2015-07
Data Modeling Master Class Training Manual written by Steve Hoberman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07 with categories.
This is the sixth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com. The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard. You will know not just how to build a data model, but how to build a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects. Top 10 Objectives 1.Explain data modeling components and identify them on your projects by following a question-driven approach 2.Demonstrate reading a data model of any size and complexity with the same confidence as reading a book 3.Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard 4.Apply requirements elicitation techniques including interviewing, artifact analysis, prototyping, and job shadowing 5.Build relational and dimensional conceptual and logical data models, and know the tradeoffs on the physical side for both RDBMS and NoSQL solutions 6.Practice finding structural soundness issues and standards violations 7.Recognize when to use abstraction and where patterns and industry data models can give us a great head start 8.Use a series of templates for capturing and validating requirements, and for data profiling 9.Evaluate definitions for clarity, completeness, and correctness 10.Leverage the Data Vault and enterprise data model for a successful