Assignment $-2$ Chapter: THE ARCHITECTURAL COMPONENTS CHAPTER SUMMARY Architecture is the structure that brings all the components together. Data warehouse architecture consists of distinct components with the read$-$only data repository as the centerpiece. The architectural components support the functioning of the data warehouse in the three major areas of data acquisition, data storage, and information delivery. Data warehouse architecture is wide, complex, expansive, and has several distinguishing characteristics. The architectural framework enables the flow of data from the data sources at one end and the user$$s desktop at the other. The technical architecture of a data warehouse is the complete set of functions and services provided within its components. It includes the procedures and rules needed to perform the functions and to provide the services. It encompasses the data stores needed for each component to provide the services. REVIEW QUESTIONS $1.$ What is your understanding of data warehouse architecture? Describe in one or two paragraphs. $2.$ What are the three major areas in the data warehouse? Is this a logical division? If so$,$ why do you think so$?$ Relate the architectural components to the three major areas. $3.$ Name four distinguishing characteristics of data warehouse architecture. Describe each briefly. $4.$ Trace the flow of data through the data warehouse from beginning to end. $5.$ For information delivery, what is the difference between top$-$down and bottom$-$up approaches to data warehouse implementation? $6.$ In which architectural component does OLAP fit in$?$ What is the function of OLAP? $7.$ Define technical architecture of the data warehouse. How does it relate to the individual architectural components? $8.$ List five major functions and services in the data storage area. $9.$ What are the types of storage repositories in the data staging area? $10.$ List four major functions and services for information delivery. Describe each briefly. EXERCISES $1.$ Indicate if true or false: A$.$ Data warehouse architecture is just an overall guideline. It is not a blueprint for the data warehouse. B$.$ In a data warehouse, the metadata component is unique, with no truly matching component in operational systems. C$.$ Normally, data flows from the data warehouse repository to the data staging area. D$.$ The management and control component does not relate to all operations in a data warehouse. E$.$ Technical architecture simply means the vendor tools. F$.$ SQL$-$based languages are used to extract data from hierarchical databases. G$.$ Sorts and merges of files are common in the staging area. H$.$ MDDBs are generally relational databases. I. Sometimes, results of individual queries are held in temporary data stores for repeated use. J$.$ Downstream specialized applications are fed directly from the source data component. $2.$ You have been recently promoted to administrator for the data warehouse of a nationwide automobile insurance company. You are asked to prepare a checklist for selecting a proper vendor tool to help you with the data warehouse administration. Make a list of the functions in the management and control component of your data warehouse architecture. Use this list to derive the tool$-$selection checklist. $3.$ As the senior analyst responsible for data staging, you are responsible for the design of the data staging area. If your data warehouse gets input from several legacy systems on multiple platforms, and also regular feeds from two external sources, how will you organize your data staging area? Describe the data repositories you will have for data staging. $4.$ You are the data warehouse architect for a leading national department store chain. The data warehouse has been up and running for nearly a year. Now the management has decided to provide the power users with OLAP facilities. How will you alter the information delivery component of your data warehouse architecture? Make realistic assumptions and proceed. $5.$ You recently joined as the data extraction specialist on the data warehouse project team developing a conformed data mart for a local but progressive pharmacy. Make a detailed list of functions and services for data extraction, data transformation, and data staging