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  • With RFID, the System is the System
    . To use the data, it has to be communicated to and integrated into appropriate back-end software systems and these systems need to be integrated with each other. Collecting receiving data may help improve warehouse systems and inventory accuracy, but unless this data is also linked to order entry
  • Backtalk 8/20/2009
    A group of 15 students from the Hong Kong Polytechnic University 's (PolyU) School of Design (SD) participated in a six-week workshop aimed at creating a new generation of "Asian Fit " protective facemasks. The masks, designed to specifically fit the Asian population in terms of size and purpose

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  • Advanced Data Warehouse Design
    Advanced Data Warehouse Design .
  • Data Warehouse Systems
    Regarding data warehouse design , we make a clear distinction between the three abstraction levels of the American National Standards Institute (ANSI) database architecture, that is, conceptual, logical, and physical, unlike the usual approaches, which do not distinguish clearly between the conceptual and...
  • Data Warehousing and Knowledge Discovery
    The top- ics included data warehouse modeling, spatial data warehouses, mining social networks and graphs, physical data warehouse design , dependency mining, busi- ness intelligence and analytics, outlier and image mining, pattern mining, and data cleaning and variable selection.
  • Pro SQL Server 2012 BI Solutions
    I’ve seen a lot of students struggle with topics such as data warehouse design , ETL processing, or OLAP cubes.
  • Oracle Warehouse Builder 11g R2: Getting Started 2011
    He has also been performing various tasks, including data warehouse design and implementation, administration, backup and recovery, development of Perl code for web-based database access, writing Java code utilizing JDBC, migrating legacy databases to Oracle, and developing Developer/2000 Oracle Forms applications.
  • Encyclopedia of Database Systems
    The active data warehouse design extends the technol- ogy behind active database systems.
  • DataWarehousing and Knowledge Discovery
    Data Warehouse Design .
  • Microsoft SQL Server 2014 Business Intelligence Development Beginner’s Guide
    Preface Chapter 1: Data Warehouse Design .
  • Expert Cube Development with SSAS Multidimensional Models
    In this chapter, we will touch on just about every aspect of data warehouse design , and mention several subjects that cannot be analyzed in depth in a single chapter.
  • Data Warehousing and Knowledge Discovery
    The topics included data warehouse modeling, spatial data warehouses, mining social net- works and graphs, physical data warehouse design , dependency mining, business intelligence and analytics, outlier and image mining, pattern mining, and data cleaning and variable selection.
  • Advances in Conceptual Modeling. Recent Developments and New Directions
    Current approaches for data warehouse design advocate to start the development by defining a conceptual model in order to describe real-world situations by using MD structures [13].
  • Data Warehousing and Knowledge Discovery
    The topics included data warehouse modeling, spatial data warehouses, mining social networks and graphs, physical data warehouse design , dependency mining, business intelli- gence and analytics, outlier and image mining, pattern mining, and data cleaning and variable selection.
  • Database and Expert Systems Applications
    This section then discusses multi-granular data storage, both at the detail and the aggregated levels, according to the needs of the application domain and highlights the inappropriateness of the standard data warehousing design approaches to handle multi-granular data.
  • Journal on Data Semantics XIII
    The main purpose of DLs is to provide a formal theory that can be used to validate conceptual schemata (Franconi & Ng, 2000) of heterogeneous databases (Mena et al., 2000), data warehousing design and multidimensional aggregation modelling (Baader & Sattler, 2003).