Synthesis with Data Warehouse Applications and Utilities

Today’s fast moving business world faces continuous challenges and abrupt changes in real-life situations at the context of data and information management. In the current trend of information explosion, businesses recognize the value of the information they can gather from various sources. The information that drives business decisions can have many forms, including archived data, transactional data, e-mail, Web input, surveyed data, data repositories, and data marts. The organization’s business strategy should be to deliver high-quality information to the right people at the right time. Business analysis desires that some data must be absolutely current. Other data may be comprised of historical or summary information and are less time sensitive. To overcome the data loss, improve efficiency, make real-time update, and maintain a wellmarked path to other data, a high-speed connectivity is always needed. It also needs to protect the information the systems gather, while ensuring that it is readily available, consistent, accurate, and reliable. It also must consider how the software environment has been designed and what impact that design has on the performance, availability, and maintainability of the system. Among all these parameters, defining the basic layout of a storage environment is critical for creating an effective storage system. With data residing on numerous platforms and servers in a multitude of formats, gaining efficient and complete access to all relevant organizational data is essential. While designing the data warehouse, the network topology, data consistency, data modeling, reporting tool, storage, and enactment of data need to be clearly understood. In recent days, data warehouse database(s) grew at such a pace that the traditional concept of database management needed to be revisited, redesigned, and refocused with increased demand, availability, and frequent updates by putting pressure on data warehouse methodologies and application tools. Innovative applications and techniques have evolved to handle data warehousing more efficiently and to provide easier data access. BACKGROUND