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Data Warehouse Business Technology - Essay Example

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The essay "Data Warehouse Business Technology" focuses on the critical analysis of the major issues in data warehouse business technology. In the era of the development of business technology data warehouses - data mining is a crucial tool in the business environment…
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Data Warehouse Business Technology
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Data Warehouse College: Data Warehouse In the era of development of business technology data warehouse - data mining are crucial tools in the business environment. Data warehouse is a system used for reporting and data analysis of information within organizations. This is a critical tool that many managers use for synthesis of decisions that affect the organizational path. In the contemporary competitive business environment, this has become one of the most popular technologies as decisions become an important determiner of the organizational development. Some of the advantages of data warehousing involves integrating data from different sources and combining it on a common platform, and keeping the data history as a way of tracking the information coverage within an organization. Understanding the features of the data warehouse and the issues surrounding this technology is crucial for its application in the public domain. Data warehouse has a number of key features that aid in the storage, processing and analysis of information. One of the key features is the data integration feature within its core. This feature is particular crucial in combining information from both external and internal sources. External sources include the external market factors such as the competition while the internal features include sales from different branches of the organization. The integration features helps to combine information required in processing decisions that affect the whole organization. Secondly, the data warehouse has the SQL Server that allows in merging of information, changing data capture and management of information. The analysis feature in the data warehouse helps in processing of the information depending on the particular queries. The queries are inputs that allow computation of specific variables that the management requires. Another key feature includes the reporting services that include the reporting scalability and server scalability. This is the output feature that presents key information required for decision making (Bhansali, 2009). The combination of these features makes it possible to obtain data, combine it and synthesise it according to specific requirements of the user. One unique function of data warehouse is to aggregate information and store it. The warehouse architecture comprises of operational databases that provide information for the data warehouse. The warehouse gathers information from all these operational databases and combines it. Another crucial function of the warehouse is the storage of information within a common platform. In the data driven business market, information has become an important aspect of the organization. For an organization to make viable decisions, it is crucial that it focuses on the big data of the organization. Therefore, the warehouse technology enables to store information that can be used later for management decision making. The key function of the data warehouse is information processing function. Information process refers to the process of analysing data depending on specific queries that are important for decision making. For instance, the data analysis feature can be able to process the available information and provide the highest sale and the lowest sales within an organization. This is the principle reason why the data warehouse technology came into being. The purpose was to process information quickly to enhance rapid decision making within organizations (Bhansali, 2009). This allows management to act on complex data which would be a challenge to process in the absence of a data warehouse. The main difference between data mining and online analytical processing (OLAP) is that OLAP deals with low volume of transactions and has a latency of just a few hours. The evolution of the data warehousing technology has come along with the increase in legal and ethical issues. One ethical issue comes along with the collection of information from the public. In some occasions, the organizations collect information from the public without their consent. For instance, the Angry Birds, a popular mobile application was designed to collect the information of customers’ location without their awareness. Later, they became the targets of product advertisements. Collecting information from the customers without their consent is an issue of ethical concern. At times, rogue internet hackers may use information on location of the public to perpetrate crime. Therefore, this a major issue that requires attention in data warehousing. The sale of personal data is an issue of ethical concern. At times, the data warehouse may contain persona information that workers can sell illegally to outsiders for selfish benefits. Therefore, the security of data and its confidentiality has become an issue of concern as this technology proliferates within organizations (Bhansali, 2009). It is the role of the managers to address any ethical issues that come along with the use of this technology. Knowledge discovery in data mining focuses on the procedures and methods that are applied in the extraction of useful intelligence from a big set of data. With the proliferation of technology, the information is becoming more available making it a hard task to process information (Bhansali, 2009). The knowledge discovery methods have come as a solution to the complexity of processing bundles of mixed up data that contains both irrelevant and relevant data. The knowledge discovery process includes the use of lightweight data analysis techniques and high performance mining techniques in synthesis information that is crucial for business decision making. However, some issues emanate from the process hence posing challenges to the knowledge discovery process. One issue arises in processing of rapid time-varying information. Such rapid changing data is a big challenge to extract knowledge. On this ground, the knowledge discovery methodologies are still evolving in an effort to overcome the challenges that are coming up within this field. In conclusion, the data warehousing technology is an important discovery in the business environment. The data warehouse is an important platform for organizational decision making. Its function involves the collection, aggregation, processing and reporting of information from other minor databases. In the era of big data, data processing is an important aspect of organizations. The managers use information to model the organizational strategies within organizations. This technology came along with ethical, privacy and legal issues that come along with the storage of personal information, its collection and abuse while under storage. For this technology to survive, the designers of the data mining architectures must provide ways to alleviate various legal issues that come along with the use of this technology within organizations. References Bhansali, N., (2009). Strategic Data Warehousing: Achieving Alignment with Business. New York: CRC Press. Read More
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