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Data Normalization A Complete Guide - 2020 Edition.
What is effective Data Normalization? How do you manage Data Normalization Knowledge Management (KM)? Are Data Normalization vulnerabilities categorized and prioritized? What Data Normalization data should be collected? How do you ensure that the Data Normalization opportunity is realistic? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Normalization investments work better. This Data Normalization All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data Normalization Self-Assessment. Featuring 954 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Normalization improvements can be made. In using the questions you will be better able to: - diagnose Data Normalization projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data Normalization and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data Normalization Scorecard, you will develop a clear picture of which Data Normalization areas need attention. Your purchase includes access details to the Data Normalization self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Normalization Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Giving comprehensive, soup-to-nuts coverage of database administration, this guide is written from a platform-independent viewpoint, emphasizing best practices.
Given the exponential growth of Artificial Intelligence (AI) over the past few decades, AI and its related applications have become part of daily life in ways that we could never have dreamt of only a century ago. Our routines have been changed beyond measure by robotics and AI, which are now used in a vast array of services. Though AI is still in its infancy, we have already benefited immensely. This book introduces readers to basic Artificial Intelligence concepts, and helps them understand the relationship between AI and daily life. In the interest of clarity, the content is divided into four major parts. Part I (AI Concepts) presents fundamental concepts of and information on AI; while Part II (AI Technology) introduces readers to the five core AI Technologies that provide the building blocks for various AI applications, namely: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), and Ontology-based Search Engine (OSE). In turn, Part III (AI Applications) reviews major contemporary applications that are impacting our ways of life, working styles and environment, ranging from intelligent agents and robotics to smart campus and smart city projects. Lastly, Part IV (Beyond AI) addresses related topics that are vital to the future development of AI. It also discusses a number of critical issues, such as AI ethics and privacy, the development of a conscious mind, and autonomous robotics in our daily lives.
The aim of this work is to provide a correct and up-to-date understanding of the practical aspects of crucial, yet little- understood core database issues. The author identifies fundamental concepts, principles, and techniques and assesses the treatment of those issues in SQL (both the standard and commercial implementations) and gives advice on how to deal with them. Topics covered include complex data types, missing information, data hierarchies, and quota queries. Annotation copyrighted by Book News, Inc., Portland, OR
Data Design A Complete Guide - 2020 Edition.
Data Redaction A Complete Guide - 2020 Edition.