Advanced Topics in Information Resources Management, Volume 2 (Advances in Information Resources Management)
Annotation Advanced Topics in Information Resources Management features the latest research findings dealing with all aspects of information resources management, managerial and organizational applications, as well as implications of information technology organizations. It aims to be instrumental in the improvement and development of the theory and practice of information resources management, appealing to both practicing managers and academics.
A complete hand on guide to assist IS Managers in understanding data warehousing and how to incorporate this technology into their own company's business operations. The book includes a CD-ROM containing templates, spreadsheet forms, and sample presentations that can be used to quick start a data warehouse development process.
This is the first book to be published on the topic of data quality exploration, analytics and quantitative data cleaning. The author provides a sound technical grounding in the subject and shows readers, through examples and practical case studies, how to apply statistics and data mining techniques to their own data quality issues. An overview of data quality analytics and techniques for data quality improvement is provided, and the author also present an iterative framework for the detection,...
Oracle Essbase & Oracle OLAP (Oracle Press)
by Schrader, Vlamis, Michael Schrader, and Dan Vlamis
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.The only book to cover and compare Oracle's online analytic processing productsWith the acquisition of Hyperion Systems in 2007, Oracle finds itself owning the two most capable OLAP products on the market--Essbase and the OLAP Option to the Oracle Database. Written by the most knowledgeable experts on both Essb...
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A practical guide with easy-to-follow recipes helping developers to quickly and effectively collect data from disparate sources such as databases, files, and applications, and turn the data into a unified format that is accessible and relevant to end users.Any IT professional working on PDI and is a valid support for either learning how to use the command line tools efficiently or for...
Using Open Source Platforms for Business Intelligence (The Morgan Kaufmann Series on Business Intelligence)
by Lyndsay Wise
Open Source BI solutions have many advantages over traditional proprietary software, from offering lower initial costs to more flexible support and integration options; but, until now, there has been no comprehensive guide to the complete offerings of the OS BI market. Writing for IT managers and business analysts without bias toward any BI suite, industry insider Lyndsay Wise covers the benefits and challenges of all available open source BI systems and tools, enabling readers to identify the s...
Azure Data Factory Cookbook
by Dmitry Anoshin, Dmitry Foshin, Roman Storchak, and Xenia Ireton
Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data FactoryKey FeaturesLearn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory’s visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook DescriptionAzure Data Factory (ADF) is a modern data integration tool available on Microsoft...
Feature Engineering for Machine Learning
by Alice Zheng and Amanda Casari
Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you'll learn techniques for extracting and transforming features-the numeric representations of raw data-into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach th...
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.Deploy and Maintain an Integrated MDS ArchitectureHarness your master data and grow revenue while reducing administrative costs. Thoroughly revised to cover the latest MDS features, Microsoft SQL Server 2012Master Data Services, Second Edition shows how to implement and manage a centralized, customer-focused MD...
Teradata for Executives (Tera-Tom Genius)
by Tom Coffing and Leslie Nolander
Tietovarastointi Ja Tietohallinnon Strateginen Suunnittelu
by A Tormanen
Impala in Action:Querying and mining big data
by Richard L Saltzer and Istvan Szegedi
DESCRIPTION Hadoop queries in Pig or Hive can be too slow for real-time data analysis. Impala, an ultra-speedy query engine from Cloudera, supercharges Hadoop by avoiding the typical Map-Reduce overhead and parallelizing queries so that they can run on multiple nodes. This is a big deal for big data, because with Impala, querying Hadoop takes seconds rather than minutes. Impala's dialect is close to standard SQL, and Impala seamlessly accesses HBase and HDFS (Hadoop Distributed File Sys...
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....