Assignment 3 Business Intelligence and Data Warehouses

According to Wikipedia (2006) several decision making models have be developed for organizational use such as:

3. Management information systems - used to collect qualitative as well as quantitative information for decision making within organizations

In this paper the writer will seek to respond to the questions designated for both scenarios. This paper will list typical fields for each type of data. Provide an example of two relationships that you need to track. This paper will also answer the questions of: Do you need a database system? If not, can Excel® handle the data and the output? What are the advantages and disadvantages? Would you use a personal database or an enterprise database? Explain your answer. Would a decision support system (DSS) be helpful? Explain your answer.

In the future, the development is more focused on Big Data where the requirement of availability of information increase directly with the complexities of decision making increase, thus the requirement of data infrastructure need larger and more analytically to align with knowledge and decision-supporting technologies (Hosack et al., 2012). Increasing information available to KMDSS through data warehouse capabilities may be useful to the several industries. DSS has been on the forefront not only of new technologies, but of new ways to address existing business problems and processes. The nature of DSS is to continuously improve the decision-making processes that, in turn, improve the efficiencies of

According to Silva (2005), in order to gain competitive advantage, information is by far the most important key to accomplish it. The essential information for making decision-making is on its operational database, where we have to derive insight and analyzing these data out, called Data Warehousing (DW). DW enables managements to access the critical information they would like to know, which along with making business decisions and establishing business strategy. However, DW technology takes a lot of time to develop as well as is high-priced. In

In Philip Russom’s webinar he provides an overview of what a Data Warehouse (DW) modernization is, why many users’ DWs need modernization. The top five most common reasons for DW modernization including: Advanced Analytics, Scale, Speed, Productivity and Cost Control, what is the result from modernization, and his recommendations

Data warehouses are targeted for decision supporting. Old, summarized and consolidated data is very much important than detailed as well as individual records. As data warehouses store consolidated data, possibly from several operational databases, for perhaps a very long time, they tend to be in orders of magnitude much greater than operational databases; enterprise data warehouses are projected to be hundreds of gigabytes to terabytes in size.

The data warehouse DBMS market is going through a transformation due to the rise of "big data" and logical data Warehouses. Surprisingly, many establishments entered the data warehouse market in 2012 for the first time, swelling demand for professional services and causing vital changes in vendors' positions.

Data warehouse solve a lot of problems to companies as it helps to structure files and avoid unnecessary duplication of data.

Making decisions is an important part of the business world. However, without the proper information and data, it is easy for decisions to be made poorly. For this reason, business intelligence has been simplifying the process of delivering information and data to key decision-makers ever since it was first developed.

To understand what an organization’s database requirements may be, it is vital to discern what uses can be had from a database. Databases are key in a business operation, they allow for the quick access to company data, and help to quickly sort and deliver information when needed. A few examples of the functions a database can provide for a business is the ability to track customers, their inventory, and even employees.

This database provides general reports for. E.g. Daily Sales report by product or by customer or by route. These reports are helpful— particularly for real-time reporting —but they don’t allow in-depth analysis. The possibilities for reporting and analysis are endless. When it comes to analyzing data, a static list is insufficient. There’s an intrinsic need for aggregating, summarizing, and drilling down into the data. A data warehouse enables you to perform many types of analysis:

The worldwide information landscape is changing rapidly due to innovation in technological solutions. Technological solutions play a crucial role in decision-making through analysis of a massive data or big data. The explosives changes in the supply and demand of the market require firms to respond proactively and spontaneous. Accordingly, enterprises managers should be able to collect, filter and analyze the enormous amount of data from many sources in real-time. Therefore, organizations turned to use technologies for decision-making, solve the complex and challenging business problems. The tools used to support decision-making has become very wide and filled with the buzzwords. In this report, we will outline the connection between the two types of software solutions that support the decision-making process; Decision Support Systems (DSS) and Business Intelligence (BI).

is often rolled-up and summarized into higher-level decision support systems to help firms understand what is happening in their organizations and how best to respond. In order to achieve seamless handling of this data, organizations must ensure that their business information systems are tightly integrated across the enterprise. Doing so allows organizations to manage and process basic business

With the development of technology, information storage and management have been vital of importance. Information effectiveness and efficiency are determined by how well data is organised and processed. The term ‘data’ have been widely employed in different human activities, including science, business, education, law and the like. Here, data is a means for representation of facts, concepts, and instructions in order to communicate (Sumathi & Esakkirajan 2007). Nevertheless, if data management is ineffective, and relevant information cannot be found quickly, a large amount data will become a liability rather than an asset of an organisation; thus, tools used for data management give rise to the occurrence of database