Volume 3, Issue 1 - January 2009

IN THIS ISSUE

Featured Article: Tom Jesionowski: Closing Communication Gaps   

• Nirmalya Ghosh: The Unified Data Modeling    
• Michael Scofield: Connecting Geospatial Data With Business Intelligence - Part 1   
• Simon Eligulashvili: Efficiency Gains in Inbound Data Warehouse Feed Implementation   
• Charles Griffith: Building a Data Warehouse Organization to Deliver Competitive Advantage   

• Tom Jesionowski: Closing Communication Gaps   
  

  Why has it become so challenging for corporate America to establish effective internal communication? Meeting goals and objectives seems increasingly difficult to achieve. A common workplace perception is that others block progressive efforts, either intentionally or through incompetence. Could the technology we designed be pushing us further apart instead of uniting our organizations? Is the specialization of the workplace creating a fragmented environment?
• Nirmalya Ghosh: The Unified Data Modeling    
  

  Data modeling is one of the important building blocks in any enterprise system development. A flexible, consistent data model leads to a stable application, even in the face of changing data requirements. There are numerous data modeling tools available to create the conceptual, logical and physical data models. The learning curve for these tools is short; however achieving excellence in data modeling practice takes time.
• Michael Scofield: Connecting Geospatial Data With Business Intelligence - Part 1   
  

  Most information technology professionals have been immersed in a tabular data paradigm, and thus are unfamiliar with the significant differences geospatial data brings. This article, the first in a short series, attempts to explain the differences, and explain at a very high level how data (or “information”) may move across the gap between BI and GIS for added value to decision-making.
• Simon Eligulashvili: Efficiency Gains in Inbound Data Warehouse Feed Implementation   
  

  The task of building a data warehouse with the objective of making it a long-term strategic platform represents many technical and business challenges. One of the determining factors of a successful implementation of the warehouse system is its ability to expand on the number of inbound data feeds over time with the pace required by the business. Besides the commonly recognized challenges presented by expanding the data inventory, such as ensuring system scalability and acceptable performance levels, capacity planning, and continuous adherence to enterprise guidelines, a critical part of this process lies in the methodology of implementing inbound feeds. While other aspects of the data warehouse lifecycle are equally important, it is imperative to work out an efficient inbound feed implementation methodology that will help reduce costs, time-to-market, and risks associated with development and maintenance of data feeds as the data warehouse evolves.
• Charles Griffith: Building a Data Warehouse Organization to Deliver Competitive Advantage   
  

  Historically, investments in Information Technology (IT) were focused on individual products or services. When a business manager needed to add/change a product or service, he/she owned the application system, people, process and technology that supported the change. With a single business owner, life was simple; people actually came to the same physical location and could rapidly work through issues. In today’s world, decisions are more complicated from the onset; typically multiple business units are located in physical and virtual offices across the country and around the world. As companies strive to become customer-centric, it is increasingly difficult to add or change a product or service without affecting other parts of the enterprise that support the customer. The challenge in Data Warehousing is to develop a Data Warehouse (DW) organization that makes rapid and effective enterprise decisions and delivers business value quickly and accurately.