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by Bill Inmon Content type: Downloads
Category: Data Warehouse Document

Glossary of Data Warehousing Terms

Compiled by Bill Inmon
President, Inmon Data Systems

Content type: Prior Events
Category: Prior Events

DATA WAREHOUSE DESIGN & ARCHITECTURE - SEMINAR Featuring Michael Hermida, "One of the World's Leading Experts in Data Warehouse Design", World Renowned Author, Lecturer and Consultant- President, K3MP Technologies

Content type: Images
Category: Business Images



Content type: Images
Category: Business Images



by Wayne P. Milano Content type: Downloads
Category: Data Warehouse Document



Content type: Downloads
Category: Big Data Document

DMForum and the BIG DATA AND ENTERPRISE ARCHITECTURE CONFERENCE 2013 Theme: Award-Winning BIG DATA Programs – Best Practices in Technologies and Techniques By Anne Marie Smith, Ph.D. Alabama Yankee Systems, LLC Independent Consultant, Enterprise Information Management and Data Governance Conference Background Each year, DMForum (http://www.dmforum.org) hosts a Data Warehouse conference in Washington, DC, where experts in enterprise data management and data warehousing gather to present their approaches to challenges faced in all industries concerning the use of data and information. This event is co-sponsored annually by the National Capital Region of DAMA International (http://www.dama-ncr.org). The 2013 conference is scheduled for Friday, November 22 at the Crystal City Hilton Hotel, and the focus will be on the exciting developments in BIG DATA.

by Ron Daniel and Joseph Busch Content type: Downloads
Category: Metadata Design Document

Dublin Core for Enterprise-Wide Metadata Applications

by Pete Stiglich Content type: Downloads
Category: Data Warehouse Document

Enabling high quality analytics through a Data Validity Dimension
While working on an Enterprise Data Warehouse for a state court system the issue of poor data quality in the source systems became apparent. Referential integrity was not strictly enforced and there was very little in the way of attribute level constraints. One normally expects that these types of constraints be enforced for an OLTP application, whether through the application, in the database, or both. Of course, one should never be surprised when there is poor data quality in the source systems – poor data quality is the norm rather than the exception. According to The Data Warehouse Institute (TDWI) over $600 billion a year is lost due to poor data quality.

by Stu Carty Content type: Downloads
Category: Metadata Design Document

The term “Enterprise Metadata Management” has been in use since the late 1980’s when many of us worked in classic “mainframe environments” using “corporate data dictionaries” to manage our COBOL programs, Job Control Language (JCL), screens, reports, copybooks, and database schema definitions. Fast-forward to 2005 ~ has anything changed? What does “enterprise metadata management” mean today ? I recently surveyed a number of leading metadata management vendors, Global 5000 companies, and industry thought-leaders seeking their input.

by Pete Stiglich Content type: Downloads
Category: Data Warehouse Document

Facilitate Customer Integration using Generic Dimensional Modeling Techniques
If you are undertaking a Customer Data Integration (CDI) or Customer Master Data Management (MDM) project as part of a Dimensional Modeling endeavor, how will you tackle the problem of how to store customer addresses?

by Jane Griffin Content type: Downloads
Category: Documents

There is none - life after Sarbanes-Oxley compliance, I mean. Why? Because there is no "after" when it comes to being in compliance with the 2002 Sarbanes-Oxley Act. Sarbanes-Oxley (SOX) compels public corporations to file annual reports with the SEC that detail the process by which corporate management has established and maintained internal governance structures and processes for financial reporting. It also requires companies to report on the effectiveness of those efforts. In short, SOX compliance requires an ongoing effort on the part of all public (and a growing number of private) companies to put their financial reporting houses in order and to keep them that way.

Content type: Images
Category: People and Portraits

Ipod Nano winner Vivek Parikh, from Freddie Mac, at the Data Warehouse Conference 2007 in Arlington, VA.

Content type: Downloads
Category: Newsletter

July 2007 newsletter

Content type: Images
Category: Business Images



Content type: Images
Category: Business Images



by Krish Krishnan Content type: Downloads
Category: Big Data Document

Social media has captured business owners’ attention from across the world and it is now fanned by the giant wave or tsunami called big data. While Facebook, Twitter or any forum or blog can give you platforms where communities of customers gather to share opinions and ideas about products, services and much more, the content and context are not often clear and are completely devoid of emotion. Here is where the topic of this article comes from – what is the business value of social media data? The biggest issue that faces every organization wanting to implement a social media integration strategy is identifying the business value. Understanding one’s customer is very critical, and there are several channels to help you do this, including research firms such as Nielsen; agencies that specialize in aggregating metrics, such as Gnip and Infochimps; data and metrics providers such as Visible Technologies, and expert marketing consultants who can explain a dozen metrics that you need from social media. But where is the business value? Customer lifetime value (LTV) or wallet share are not metrics that justify such data integration nor is the notion of social customer relationship management (CRM) or supplier relationship management (SRM).

by Dave Marco Content type: Downloads
Category: Metadata Design Document

This article is adapted from the book "Universal Meta Data Models" by David Marco & Michael Jennings, John Wiley & Sons Almost every corporation and government agency has already built, is in the process of building, or is looking to build a Managed Meta Data Environment (MME). Many organizations, however, are making fundamental mistakes. An enterprise may build many meta data repositories, or “islands of meta data” that are not linked together, and as a result do not provide as much value

by Bill Inmon Content type: Downloads
Category: Metadata Design Document

Metadata is an important component of the data warehouse. This white paper discusses why, and what the different components of metadata are for the data warehouse.

by Richard Mark Soley, Ph.D. Content type: Downloads
Category: Object Design Document

Where Can We Agree? • There will not be consensus on hardware platforms • There will not be consensus on operating systems • There will not be consensus on network protocols • There will not be consensus on programming languages • There must be consensus on models, interfaces and interoperability!

by Richard Mark Soley, Ph.D. Content type: Downloads
Category: Object Design Document

Model Driven Architecture: An Introduction Richard Mark Soley, Ph.D. A New Way to Specify and Build Systems Based on modeling with UML Supports full lifecycle: analysis, design, implementation, deployment, maintenance, evolution & integration with later systems Builds in Interoperability and Portability Lowers initial cost and maximizes ROI Applies directly to the mix you face: Programming language  Network Operating system  Middleware

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