Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse — without them dozing off? Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives. Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization. This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours. Building a high-level data model following the ten step approach you’ll read about is a great way to ensure you will retain the new skills you learn in this book. As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general. This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization—between both businesspeople and IT. Data modeling is one of the under-exploited, and potentially very valuable, business capabilities that are often hidden away in an organization’s Information Technology department. Data Modeling for the Business highlights both the resulting damage to business value, and the opportunities to make things better. As an easy-to follow and comprehensive guide on the ‘why’ and ‘how’ of data modeling, it also reminds us that a successful strategy for exploiting IT depends at least as much on the information as the technology. Chris Potts, Corporate IT Strategist and Author of fruITion: Creating the Ultimate Corporate Strategy for Information Technology One of the most critical systems issues is aligning business with IT and fulfilling business needs using data models. The authors of Data Modeling for the Business do a masterful job at simply and clearly describing the art of using data models to communicate with business representatives and meet business needs. The book provides many valuable tools, analogies, and step-by-step methods for effective data modeling and is an important contribution in bridging the much needed connection between data modeling and realizing business requirements. Len Silverston, author of The Data Model Resource Book series
Did you ever try getting Business and IT to agree on the project scope for a new application? Or try getting the Sales & Marketing department to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off? You can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives. Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach. Know how to evaluate toolsets for building and storing your models. Practice exercises and walk through a case study to reinforce your modelling skills.
Author: Bill Aronson
Release Date: 2010-05-06
Genre: Business enterprises
The Metastorm ProVision 6.2 User Guide is the essential reference. Packed with tips and tricks that go way beyond what you would expect, the book explains how to ask the right questions as well as how to use the program. All the new features are described. Bill shares his expertise in many areas including simulation, strategy and process improvement.
Author: Sharon Lee Allen
Release Date: 2006-11-03
*Immediately accessible to anyone who must design a relational data model—regardless of prior experience *Concise, straightforward explanations to a usually complex/ jargon-rich discipline *Examples are based on extensive author experience modeling for real business systems
Author: Peter J. Capezio
Publisher: McGraw Hill Professional
Release Date: 2009-10-16
Genre: Business & Economics
Get the business results you want by creating and executing a solid plan! One simple thing usually makes the difference between business success and failure: a well-laid plan. Whether you want to enact a long-term strategic initiative or set short-term revenue targets, Manager’s Guide to Business Planning provides the tools and techniques for developing a workable plan everyone will support. You’ll learn how to: Measure success Prioritize initiatives Run business reviews Create a budget Engage employees There’s no reason to experience false starts, waste money, or dissatisfy customers in your business endeavors. Manager’s Guide to Business Planning has tried-and-true methods that can be applied to any situation.
Author: Rob Akkershoek
Publisher: Van Haren
Release Date: 1970-01-01
The IT4IT Management Guide provides guidance on how the IT4IT Reference Architecture can be used within an IT organization to manage the business of IT. It is designed to provide a guide to business managers, CIOs, IT executives, IT professionals, and all individuals involved or interested in how to transition an IT organization to become a Lean and Agile IT service provider.This book includes two case studies from Shell and the Rabobank.After reading this document you should be able to: Understand why the IT4IT approach is needed to improve the performance of the IT function; and support the business to leverage new IT in the digital age Understand the vision, scope, and content of the IT4IT Reference Architecture (from a high-level perspective) Understand the benefits of using the IT4IT Reference Architecture within the IT function Initiate the first steps to implement the IT4IT standard in your own IT organizationThe audience for this Management Guide is: CIOs and other IT executive managers who would like to transform their IT organization to support end-to-end value streams Senior leaders and executives in the business and IT responsible for how IT is organized, managed, and improved Enterprise Architects involved in the implementation of IT management solutions within the IT organization IT professionals and consultants involved in the transition of their organizations to a new streamlined IT factory
Author: Nate Stammer
Publisher: McGraw Hill Professional
Release Date: 2013-10-18
The best fully integrated study system available for the CompTIA Cloud+ Certification exam With hundreds of practice questions, CompTIA Cloud+ Certification Study Guide covers what you need to know—and shows you how to prepare—for this challenging exam. McGraw-Hill Professional is a Gold-Level CompTIA Authorized Partner offering Authorized CompTIA Approved Quality Content to give you the competitive edge on exam day. 100% complete coverage of all official objectives for exam CV0-001 Exam Watch notes call attention to information about, and potential pitfalls in, the exam Exam at Work notes provide real-world examples of cloud computing technologies in the workplace today Two-Minute Drills for quick review at the end of each chapter Simulated exam questions match the format, tone, topics, and difficulty of the real exam Covers all the exam topics, including: Cloud Computing Concepts, Models, and Terminology * Disk Storage Systems * Storage Networking * Network Infrastructure * Virtualization Components * Virtualization and the Cloud * Network Management * Performance Tuning * Systems Management * Testing and Troubleshooting * Security in the Cloud * Business Continuity and Disaster Recovery Electronic content includes: Complete MasterExam practice testing engine, featuring: -One practice exam -Detailed answers with explanations -Score Report performance assessment tool Bonus downloadable MasterExam practice exam with free online registration
Author: Clifford Rossi
Publisher: John Wiley & Sons
Release Date: 2014-10-20
Genre: Business & Economics
Balanced, practical risk management for post – financial crisis institutions Fundamentals of Risk Management fills a critical gap left by existing risk management texts. Instead of focusing only on quantitative risk analysis or only on institutional risk management, this book takes a comprehensive approach. The disasters of the recent financial crisis taught us that managing risk is both an art and a science, and it is critical for practitioners to understand how individual risks are integrated at the enterprise level. This book is the only resource of its kind to introduce all of the key risk management concepts in a cohesive case study spanning each chapter. A hypothetical bank drawn from elements of several real world institutions serves as a backdrop for topics from credit risk and operational risk to understanding big-picture risk exposure. You will be able to see exactly how each rigorous concept is applied in actual risk management contexts. Fundamentals of Risk Management includes: Supplemental Excel-based Visual Basic (VBA) modules, so you can interact directly with risk models Clear explanations of the importance of risk management in preventing financial disasters Real world examples and lessons learned from past crises Risk policies, infrastructure, and activities that balance limited quantitative models This book provides the element of hands-on application necessary to put enterprise risk management into effective practice. The very best risk managers rely on a balanced approach that leverages every aspect of financial operations for an integrative risk management strategy. With Fundamentals of Risk Management, you can identify and control risk at an expert level.
Author: Carol V. Brown
Publisher: CRC Press
Release Date: 1999-10-28
In systems analysis, programming, development, or operations, improving productivity and service - doing more with less - is the major challenge. Regardless of your management level, the Handbook gives you the advice and support you need to survive and prosper in the competitive environment. It is the only comprehensive and timely source of technical and managerial guidance, providing expert information on the latest IT management techniques from top IS experts. This edition explains state-of-the-art technologies, innovative management strategies, and practical step-by-step solutions for surviving and thriving in today's demanding business environment. The IS Management Handbook outlines how to effectively manage, adapt and integrate new technology wisely, providing guidance from 70 leading IS management experts in every important area. This reference enables its readers to ensure quality, contain costs, improve end-user support, speed up systems development time, and solve rapidly changing business problems with today's IS technology.
Work with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data About This Book Unlock and discover how to tackle clusters of raw data through practical examples in R Explore your data and create your own models from scratch Analyze the main aspects of unsupervised learning with this comprehensive, practical step-by-step guide Who This Book Is For This book is intended for professionals who are interested in data analysis using unsupervised learning techniques, as well as data analysts, statisticians, and data scientists seeking to learn to use R to apply data mining techniques. Knowledge of R, machine learning, and mathematics would help, but are not a strict requirement. What You Will Learn Load, manipulate, and explore your data in R using techniques for exploratory data analysis such as summarization, manipulation, correlation, and data visualization Transform your data by using approaches such as scaling, re-centering, scale [0-1], median/MAD, natural log, and imputation data Build and interpret clustering models using K-Means algorithms in R Build and interpret clustering models by Hierarchical Clustering Algorithm's in R Understand and apply dimensionality reduction techniques Create and use learning association rules models, such as recommendation algorithms Use and learn about the techniques of feature selection Install and use end-user tools as an alternative to programming directly in the R console In Detail The R Project for Statistical Computing provides an excellent platform to tackle data processing, data manipulation, modeling, and presentation. The capabilities of this language, its freedom of use, and a very active community of users makes R one of the best tools to learn and implement unsupervised learning. If you are new to R or want to learn about unsupervised learning, this book is for you. Packed with critical information, this book will guide you through a conceptual explanation and practical examples programmed directly into the R console. Starting from the beginning, this book introduces you to unsupervised learning and provides a high-level introduction to the topic. We quickly move on to discuss the application of key concepts and techniques for exploratory data analysis. The book then teaches you to identify groups with the help of clustering methods or building association rules. Finally, it provides alternatives for the treatment of high-dimensional datasets, as well as using dimensionality reduction techniques and feature selection techniques. By the end of this book, you will be able to implement unsupervised learning and various approaches associated with it in real-world projects. Style and approach This book takes a step-by-step approach to unsupervised learning concepts and tools, explained in a conversational and easy-to-follow style. Each topic is explained sequentially, explaining the theory and then putting it into practice by using specialized R packages for each topic.
Author: Cole Nussbaumer Knaflic
Publisher: John Wiley & Sons
Release Date: 2015-10-26
Genre: Business & Economics
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Author: Lance A. Berger
Publisher: McGraw Hill Professional
Release Date: 2017-12-29
Genre: Business & Economics
The definitive guide to finding, developing, and keeping the best talent—expanded with brand new and updated material The Talent Management Handbook is the established go-to guide for HR professionals, managers, and leaders looking for the best ways to use talent management programs to develop a culture of excellence. This third edition features new and updated chapters based on fresh approaches and material for identifying, recruiting, positioning, and developing highly qualified, motivated people to meet current and future business requirements. Filled with expert advice, the book offers a roadmap for developing a comprehensive approach to talent management that will guide professionals in the coming years.