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Downloads
by Neil Raden Content type: Downloads
Category: Documents

Star Schema 101: A Pictorial Introduction to Dimensional Modeling. (Powerpoint Slides)
The “Classic” Star Schema
Compound Keys, Concatenated Keys, Generated Keys
The “Classic” Star Schema
The “Level” Problem
The “Fact Constellation” Schema
The “Snowflake” Schema


Content type: Downloads
Category: Documents

2008 Event Details

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Category: Documents



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Category: Other Document



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



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



by Neil Raden Content type: Downloads
Category: Documents

Realigning Data Warehouse Best Practices Based on Technological Advances and Lessons Learned
Data warehouses are expensive and complicated, requiring the careful integration of numerous major components. The innovations data warehouses were meant to foster are often stalled by the degree of time, cost and policy issues it requires to sustain and enhance them. In addition, the leverage that these investments yield is too low and the data warehouse informs too few people and processes. These two classes of problems, architectural and practical, and their solutions, are the subjects of this paper. Now is the time to rethink the data warehousing concept. Data warehousing needs to be recalibrated to line up with lessons learned and the changes in technology over the past decade-and-a-half since it emerged. This paper presents a conceptual foundation for an improved approach that is based on model-driven architectures. The result is to de-emphasize the physical aspects of data warehousing and turn the iterative design and innovation over to business people and processes.

Content type: Downloads
Category: Other Document



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

To understand what metadata really is, it is necessary to go much further than the simplistic definition "metadata is data about data" that really describes nothing. An effective and useful way to describe metadata is through a taxonomy of metadata in which the common visceral components of metadata are identified, as well as how those components relate to each other.

by Ivar Jacobson Content type: Downloads
Category: Object Design Document

You need knowledge Agile uses tacit knowledge UP makes knowledge explicit The truths about knowledge Process and process definition Comparing tacit and explicit knowledge Being smart with the Next Generation Process Being really smart

by Ralph Kimball Content type: Downloads
Category: Big Data Document

In this white paper, we describe the rapidly evolving landscape for designing an enterprise data warehouse (EDW) to support business analytics in the era of "big data.” We describe the scope and challenges of building and evolving a very stable and successful EDW architecture to meet new business requirements. These include extreme integration, semi- and un-structured data sources, petabytes of behavioral and image data accessed through MapReduce/Hadoop as well as massively parallel relational databases, and then structuring the EDW to support advanced analytics. This paper provides detailed guidance for designing and administering the necessary processes for deployment. This white paper has been written in response to a lack of specific guidance in the industry as to how the EDW needs to respond to the big data analytics challenge, and what necessary design elements are needed to support these new requirements.

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

Innovation has always been the spirit of our country and has been the key to success for a number of decades. If we were to turn through the pages of history, we would see there have been tipping points across time leading to innovations in every field that touches the human life, making the world a better place. A closer examination of any innovation reveals that there has been a lot of research and development using a large volume of data, based on which we have arrived at the solution. Many of the innovations – beginning with electricity, radio and wireless, automobiles and, more recently, the Internet and mobile devices – have been transformative both professionally and in our personal lives, and provided significant business benefits.



by IBM Content type: Downloads
Category: Big Data Document



by IBM Content type: Downloads
Category: Big Data Document



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

Metadata has been around for as long as there have been programs and files. And while a shop is small and decentralized, there is no recognition of the need for the management of metadata. In addition, as long as all systems are new and well documented, the need for metadata management goes unrecognized. But in today’s world, systems are not new, are not well documented, and are not all situated in a single small location. Today’s systems are complex and run over many environments. Today’s systems encompass many kinds of technologies with many kinds of users spread over many locations. And most of the systems have little or no documentation, much less up to date accurate documentation. To further complicate matters, the end user has taken over much of the domain of information processing with their own technology. And that technology is frightfully undocumented.

by Michael Gorman Content type: Downloads
Category: Metadata Design Document

No one would ever question why a business needs it's finance books. Well, the metadata repository is the business's nformation systems’ books. If you cannot run a good business without the former, you cannot run good information systems environment without the latter.

by Amit Mitra Content type: Downloads
Category: Data Design Document

The CIO’s Challenge: Creating Strategic Value with IT
The Nexus Between Systems Architecture and Program Management
Five focus areas in the nexus between systems architecture and program management are critical in realizing strategic business value from IT
By Amit Mitra, President, Sprybiz LLC
The principal challenge every CIO faces is to create value for business through the application of information technology (IT). Systems Architecture aligns information technology with business needs and identifies programs, which realize strategic business value by leveraging IT. Program Management generates business value by implementing and continuously monitoring a group of tightly integrated projects, which collectively deliver the strategic business benefits envisioned by the architecture. There are five challenges that must be overcome to realize the synergy between business strategy, systems architecture and program management. This paper addresses this nexus.

by Anne Marie Smith Content type: Downloads
Category: Data Design Document

Traditionally in many organizations, the control of data resources has been centralized due to the origin of data management within the mainframe environment. However, with the emergence of client-server technology and the blending of data and process in the object-oriented methodologies, many organizations are questioning the need to retain the centralized data and database management functions

by Jane Griffin Content type: Downloads
Category: Data Design Document

Data governance. It's not exactly the most scintillating topic. However, exciting or not, data governance - the process by which you manage the quality, consistency, usability, security and availability of your organization's data - is a critical subject that you should address sooner rather than later.

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

DW2.0 is the next generation of data warehousing. Data warehousing began in the mid 1980’s. Since then there have been many advances in architecture, technology and information systems. Today those advances have been woven into the next generation of data warehousing. The first generation of data warehousing featured transaction data that was integrated and placed on disk storage. There were other features of early first generation data warehousing, such as the advent of ETL. But there were also many missing features and functions that at the time were not recognized as belonging in a data warehouse.

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