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A practical guide to making good decisions in a world of missing dataIn the era of big data, it is easy to imagine that we have all the information we need to make good decisions. But in fact the data we have are never complete, and may be only the tip of the iceberg. Just as much of the universe is composed of dark matter, invisible to us but nonetheless present, the universe of information is full of dark data that we overlook at our peril. In Dark Data, data expert David Hand takes us on a fa...

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the currently technological world.

Level up your career by learning best practices for managing the data quality and integrity of your financial data Key Features Accelerate data integrity management using artificial intelligence-powered solutions Learn how business intelligence tools, ledger databases, and database locks solve data integrity issues Find out how to detect fraudulent transactions affecting financial report integrity Book DescriptionData integrity management plays a critical role in the success and effectiveness...

Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira a...

Graph Data Management: Techniques and Applications is a central reference source for different data management techniques for graph data structures and their application. This book discusses graphs for modeling complex structured and schemaless data from the Semantic Web, social networks, protein networks, chemical compounds, and multimedia databases and offers essential research for academics working in the interdisciplinary domains of databases, data mining, and multimedia technology.

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Your Hands-On Guide to SAP Business Information WarehouseGive your company the competitive edge by delivering up-to-date, pertinent business reports to users inside and outside your enterprise. SAP Business Information Warehouse Reporting shows you how to construct Enterprise Data Warehouses, create workbooks...

This book has step-by-step instructions to solve data manipulation problems using PDI in the form of recipes. It has plenty of well-organized tips, screenshots, tables, and examples to aid quick and easy understanding. If you are a software developer or anyone involved or interested in developing ETL solutions, or in general, doing any kind of data manipulation, this book is for you. It does not cover PDI basics, SQL basics, or database concepts. You are expected to have a basic understanding of...

Key Features Book DescriptionWhat you will learn Who this book is for

Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide About This Book • Manipulate your data by exploring, transforming, validating, and integrating it using Pentaho Data Integration 8 CE • A comprehensive guide exploring the features of Pentaho Data Integration 8 CE • Connect to any database engine, explore the databases, and perform all kind of operations on relational databases Who This Book Is For This book is a must-have for software developer...

Doing data science is difficult. Projects are typically very dynamic with requirements that change as data understanding grows. The data itself arrives piecemeal, is added to, replaced, contains undiscovered flaws and comes from a variety of sources. Teams also have mixed skill sets and tooling is often limited. Despite these disruptions, a data science team must get off the ground fast and begin demonstrating value with traceable, tested work products. This is when you need Guerrilla Analytics....

Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved...