Mining New Gold Managing Your Business Data Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Mining New Gold Managing Your Business Data book. This book definitely worth reading, it is an incredibly well-written.
Mining New Gold-Managing Your Business Data by Penny Jeffrey and Gillian Garbus Pdf
Data 1. What is the data? 2. Can data be validated? Is it accurate? 3. How do we store the data? 4. Is there a way to make money on the data? 5. How does changing expectations of data change your company's future? In this book, we will be reviewing these issues to help business leaders create a path to protecting, using, and storing data that makes sense and to save money, time, and effort.
Mining New Gold—Managing Your Business Data by Penny,Jeffrey,Gillian Garbus Pdf
Data 1. What is the data? 2. Can data be validated? Is it accurate? 3. How do we store the data? 4. Is there a way to make money on the data? 5. How does changing expectations of data change your companys future? In this book, we will be reviewing these issues to help business leaders create a path to protecting, using, and storing data that makes sense and to save money, time, and effort.
MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT by Michael J. A. Berry,Gordon S. Linoff Pdf
Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers.
Big Data is a growing business trend, but there little advice available on how to use it practically. Written by a data mining expert with over 30 years of experience, this book uses case studies to help marketers, brand managers and IT professionals understand how to capture and measure data for marketing purposes.
This guide teaches data mining from the perspective of IT professionals using Microsoft data management and e-commerce technologies. The book explains major new data mining capabilities in the forthcoming SQL Server 2000, Microsoft Commerce Server, and other products, and details the new Microsoft standard, "OLE DB for Data Mining".
Understand, Manage, and Prevent Algorithmic Bias by Tobias Baer Pdf
Are algorithms friend or foe? The human mind is evolutionarily designed to take shortcuts in order to survive. We jump to conclusions because our brains want to keep us safe. A majority of our biases work in our favor, such as when we feel a car speeding in our direction is dangerous and we instantly move, or when we decide not take a bite of food that appears to have gone bad. However, inherent bias negatively affects work environments and the decision-making surrounding our communities. While the creation of algorithms and machine learning attempts to eliminate bias, they are, after all, created by human beings, and thus are susceptible to what we call algorithmic bias. In Understand, Manage, and Prevent Algorithmic Bias, author Tobias Baer helps you understand where algorithmic bias comes from, how to manage it as a business user or regulator, and how data science can prevent bias from entering statistical algorithms. Baer expertly addresses some of the 100+ varieties of natural bias such as confirmation bias, stability bias, pattern-recognition bias, and many others. Algorithmic bias mirrors—and originates in—these human tendencies. Baer dives into topics as diverse as anomaly detection, hybrid model structures, and self-improving machine learning. While most writings on algorithmic bias focus on the dangers, the core of this positive, fun book points toward a path where bias is kept at bay and even eliminated. You’ll come away with managerial techniques to develop unbiased algorithms, the ability to detect bias more quickly, and knowledge to create unbiased data. Understand, Manage, and Prevent Algorithmic Bias is an innovative, timely, and important book that belongs on your shelf. Whether you are a seasoned business executive, a data scientist, or simply an enthusiast, now is a crucial time to be educated about the impact of algorithmic bias on society and take an active role in fighting bias. What You'll Learn Study the many sources of algorithmic bias, including cognitive biases in the real world, biased data, and statistical artifact Understand the risks of algorithmic biases, how to detect them, and managerial techniques to prevent or manage them Appreciate how machine learning both introduces new sources of algorithmic bias and can be a part of a solutionBe familiar with specific statistical techniques a data scientist can use to detect and overcome algorithmic bias Who This Book is For Business executives of companies using algorithms in daily operations; data scientists (from students to seasoned practitioners) developing algorithms; compliance officials concerned about algorithmic bias; politicians, journalists, and philosophers thinking about algorithmic bias in terms of its impact on society and possible regulatory responses; and consumers concerned about how they might be affected by algorithmic bias
Data mining is definitely not a piece of cake. There are those who spend years in the specialization of this particular field in order to operate businesses smoothly. Are you looking for a data mining course? You too, have the ability and the means to learn all the tricks that go into data mining. This book has been specifically written for those looking for a thorough introduction of data mining from the basic definition of the little details that add up to data mining of businesses of large magnitude. If you feel there is room for better quality assurance and smooth data mining of your business then this is the best possible book for you. The book covers the basics of data mining in a rather comprehensive manner. Don't worry about the technicality and difficulty level of the terminology as the explanation has been simplified to such an extent that anyone and everyone can benefit from it. Here's a preview of what you should expect to learn from this book: What is Data Mining? Types of Digitalized Data and Information Categorization of Data Mining Systems Issues with Data Mining Data mining tips that help you stand out as an effective business manager Continue reading for absolute motivation and superior data mining skills to operate your business flawlessly. ******************* IntroBooks delivers up to the minute information covering everything on a topic in only one hour of reading. This book is written to give essential information in a straight-to-the-point, easy to read format. We have cut out technical jargon, waffle and unnecessary filler to ensure you get the essential information you need to achieve your goals with confidence.
Data Mining and Business Intelligence by Stephan Kudyba,Richard Hoptroff Pdf
Annotation Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implementing data mining techniques in the corporate environment. Explains how the technology evolved, overviews the methodologies that comprise the data mining spectrum, and looks at everyday business applications for data mining, in areas such as marketing and advertising promotions and pricing policies using econometric-based modeling, and using the Internet to help improve an organization's performance. Kudyba is an economic consultant. Hoptroff is an independent consultant with experience in data mining software. Annotation c. Book News, Inc., Portland, OR (booknews.com).
Making Big Data Work for Your Business by Sudhi Sinha Pdf
If your are interested in the power of Big Data to drive improvement in your business, then this book will help you build and initiate a project for positive change.
Organizational Data Mining by Hamid R. Nemati,Christopher D. Barko Pdf
Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems, government organizations and business suppliers and partners. A recent study from the University of California at Berkeley found the amount of data organizations collect and store in enterprise databases doubles every year, and slightly more than half of this data will consist of "reference information," which is the kind of information strategic business applications and decision support systems demand (Kestelyn, 2002). Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). By 2004 the Gartner Group estimates worldwide data volumes will be 30 times those of 1999, which translates into more data having been produced in the last 30 years than during the previous 5,000 (Wurman, 1989).
How to Invest in Gold and Silver by Don Durrett Pdf
Written in clear layman's terms, this forward-thinking book is packed with information to help gold and silver investors navigate an exciting, timely, and largely unexplored market.
"Mike Woods urges his retired father into helping out a friend's failing company. But for Bob Woods, another struggle to introduce lean manufacturing quickly rehashes production battles that he's long since fought. And not even the senior Woods, son Mike, or friend Phil and his colleagues really grasp what's in store for them."--Cover.
This book covers the practical aspects of database design, data cleansing, data analysis, and data protection, among others. The focus is on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue. Databases for Small Business is a practical handbook for entrepreneurs, managers, staff, and professionals in small organizations who are not IT specialists but who recognize the need to ramp up their small organizations’ use of data and to round out their own business expertise and office skills with basic database proficiency. Anna Manning—a data scientist who has worked on database design and data analysis in a computer science university research lab, her own small business, and a nonprofit—walks you through the progression of steps that will enable you to extract actionable intelligence and maximum value from your business data in terms of marketing, sales, customer relations, decision making, and business strategy. Dr. Manning illustrates the steps in the book with four running case studies of a small online business, an engineering startup, a small legal firm, and a nonprofit organization. Databases for Small Business teaches non-techie entrepreneurs and professionals how to: Design a small business database from scratch Extract the maximum profit from your data Follow guidance on data protection law Effectively use data collection and data cleansing techniques Train staff to leverage your data
Author : Peter Ghavami Publisher : Walter de Gruyter GmbH & Co KG Page : 174 pages File Size : 48,8 Mb Release : 2020-11-09 Category : Business & Economics ISBN : 9783110664065
Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
