Information Management: Fundamental Impact Of IT Architecture
The techniques it uses were adapted after careful research into the processes and how it effects every aspect of the business and its partners. The evaluation process and decisions made to the infrastructure requirements and development of applications to support each Starbucks franchise was an important function of the IT architecture roadmap.
Information technology has grown increasingly extravagant and although it is a major expense, it has become more of a need than a want. Consumers can tell right away if a company lacks sound IT architecture, as the general public today is becoming increasingly IT savy both in their personal and professional lives. Keeping up with the advancing technologies and developing new IT solutions is an ongoing challenge for not only IT companies, but for consumer-based companies such as …show more content…
First is information life cycle, which considers the accuracy and ownership of the information. Second is data provenance, which considers the origination, collection process, and integrity of the data. Third is technology unknown, which considers the vulnerabilities and security weaknesses that IT professionals must review and make decisions before processing the vast amounts of information (Swindon, 2014). It is very apparent that the public is moving in a fast past environment with busy lives and careers, so an area of importance to focus on would to ensure IT focuses on mobility and cloud computing.
Data warehousing is described as the capture of data from many different sources for analysts to access and review the information. A data mart is useful for the end user who may need access to specific data from one more databases.
There are two approaches to data warehousing, top down and bottom up (Rouse, 2015). The top down approach spins off data marts for specific groups of users after the complete data warehouse has been created. The bottom up approach builds the data marts first and then combines them into a single, all-encompassing data warehouse (Rouse, 2015). The data can be held on a mainframe server or in a cloud