Proper enterprise architecture must include business focus and business involvement, and models of business requirements at all levels are needed as well as models for hardware, software, network, data, etc.… Introduction Recently, I received a letter from a friend of
Realizing the most value from cloud migration can be achieved through adopting a new architecture to suit legacy and current databases Introduction Cloud adoption rates continue to increase due to the cost savings, flexibility, reliability, scalability, and often improved security
The business value of text is immense, but it is not well understood by most organizations. Analysis of textual data can provide a wide variety of benefits. It is intuitively obvious to many people that there is great business value
Data warehouse / business intelligence / analytics environments require business and IT cooperation for successful architecture and design Introduction In working with many large corporations across a variety of industries, it is clear that we all face the reality of
The increasing value of data and information demonstrates the need to know the lineage of the data and its metadata to understand its relevance to operations and decisions Introduction The data landscape is changing faster than before. Big data, legacy
Database operations is the development, maintenance, and support of structured data to maximize the value of data across the organization. This function includes database support and data technology management. The management of database operations provide support to the organization for
Textual data is a valuable component for business analytics, but the responsibility for gathering and managing textual data is unclear. Consider textual processing for delivering business value. Where does the end user turn? The end user certainly recognizes the value
Organizations need a strategy for managing metadata. This strategy should be part of an enterprise data strategy, enabling the management of data as an organizational resource. Introduction Traditional systems development and implementation has focused on processes, rather than on data
Following some proven guidelines for data integration will ensure success in data warehousing and business intelligence, analytics and related systems initiatives. Introduction Almost every Chief Information Officer (CIO) has the goal of integrating their organization’s data. In fact, the issue
Physical data models should follow the logical data model as closely as possible, while adding the optimizing items to conform to a specific database and platform. Introduction Physical data modeling involves transforming the logical model from a purely business design
