A Data Warehouse And Business Intelligence Application

One of the main functions of any business is to be able to use data to leverage a strategic competitive advantage. The use of relational databases is a necessity for contemporary organizations; however, data warehousing has become a strategic priority due to the enormous amounts of data that must be analyzed along with the varying sources from which data comes. Company gathers data by using Web analytics and operational systems, we must design a solution overview that incorporates data warehousing. The executive team needs to be clear about what data warehousing can provide the company.

What information is accessible? The data warehouse offers possibilities to define what’s offered through metadata, published information, and parameterized analytic applications. Is the data of high value? Data warehouse patrons assume reliability and value. The presentation area’s data must be correctly organized and harmless to consume. In terms of design, the presentation area would be planned for the luxury of its consumers. It must be planned based on the preferences articulated by the data warehouse diners, not the staging supervisors. Service is also serious in the data warehouse. Data must be transported, as ordered, promptly in a technique that is pleasing to the business handler or reporting/delivery application designer. Lastly, cost is a feature for the data

Q3: While this case study supports a specific data warehouse product, please locate another case study from another data warehousing Software Company and explain the data warehouse that was designed in that case study?

This report is an analysis of business intelligence systems currently available to our business. As an introduction, I will address in general terms why we need to purchase a business intelligence system and how it will aid our business. Then I will discuss several applications in detail, paying particular attention to the information and analysis capabilities of each, and the hardware and software required for each. Finally, I will conclude with a short evaluation of the products discussed and offer a recommendation as to the best application for our business. I will pay particular attention to IBM, Microsoft, SAP, and Oracle.

A data warehouse is a large databased organized for reporting. It preserves history, integrates data from multiple sources, and is typically not updated in real time. The key components of data warehousing is the ability to access data of the operational systems, data staging area, data presentation area, and data access tools (HIMSS, 2009). The goal of the data warehouse platform is to improve the decision-making for clinical, financial, and operational purposes.

Business intelligence (BI) is defined as the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI has been around long before computers and access to the internet. For example, an old ship building yard would have to keep track of its various transactions, employees, profit, suppliers, materials, etc. The shipyard owner would then turn this collected raw data into useful information in order to figure out where the company is going wrong and where it can improve. If the suppliers have not shipped on time for weeks the shipyard would know to find more reliable suppliers - this is a very simple example of utilizing business intelligence. 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 Warehousing also known in many industries as an Enterprise Data Warehouse is a system that contains a central repository of integrated data, often collected from multiple sources and is used to perform data analysis enabling the creation of detailed reports that contribute significantly to a corporation’s business intelligence. Data Warehousing emerged as a result of advances in the field of information systems over the last several decades. There are two major factors that drive the need for data warehousing in most organizations. First and foremost, businesses require an integrated, company-wide view of high-quality information to maintain and improve upon their strategic position. Secondly, information systems departments must separate information from operational systems to improve performance dramatically in managing company data. Critical to the success of a Data Warehousing system, Data mining allows for companies to create customer profiles, manipulate information easily, and provide knowledgeable access to the current state of their company. However, a reality that many companies often find out the hard way is that data mining and data warehousing does not work for them. As with many new tools or technology, companies may jump on the bandwagon without fully contemplating its potential weaknesses. In order to remain competitive in today’s business world, companies should consider implementing data warehouses, but only with

A Data Warehouse is simply a consolidation of data from a variety of sources that is designed to support strategic and tactical decision making. In other words, a data warehouse consist of different data sources provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence. Its main purpose is to provide a coherent picture of the business at a point in time. Using various Data Warehousing toolsets, users are able to run online queries and 'mine" their data. Companies that build data warehouses and use business intelligence for decision-making ultimately save money and increase profit. Moreover, many successful companies have invested large sums of money in business intelligence and data warehousing tools and technologies. They believe that up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their very survival.

Data warehouse are multiple databases that work together. In other words, data warehouse integrates data from other databases. This will provide a better understanding to the data. Its primary goal is not to just store data, but to enhance the business, in this case, higher education institute, a means to make decisions that can influence their success. This is accomplished, by the data warehouse providing architecture and tools which organizes and understands the

A fundamental concept of a data warehouse is the distinction between data and information. Data is composed of observable and recordable facts that are often found in operational or transactional systems. At Rutgers, these systems include the registrar’s data on students (widely known as the SRDB), human resource and payroll databases, course scheduling data, and data on financial aid. In a data warehouse environment, data only comes to have value to end-users when it is organized and presented as information. Information is an integrated collection of facts and is used as the basis for decision making.

Data warehouse is a central repository integrating data from various operating systems for validation of data, prediction etc .Data Warehouse is a relational database used for analysis and query rather than transactional database. It is used to collect historical data from various sources, integrate, analyze a particular subject, report. Data warehouse is time variant i.e one can retrieve any older data and once data enters data warehouse it cannot change [1]. According to Ralph Kimball Data warehouse is “copy of transaction data constructed for analysis and query”[5]. Data is taken from various sources like marketing, sales, ERP etc.

A data warehouse (DW) can be acknowledged as one of the most complex information system modules available and it is a system that periodically retrieves and consolidates data from the sources into a dimensional or normalized data store. It is an integrated, subject-oriented, nonvolatile and a time-variant collection of data in support of management’s decisions (Inmon, 1993).

The purpose of a data warehouse is to make the company’s information accessible and consistent. They need to have the information immediately available and in the same format. Warehousing is of no benefit to a company if they have to wait any length of time to receive the data. A warehouse has to be an adaptive and durable source of information for the business. The warehouse has to be flexible to meet the needed changes of a business, as the business grows; it is possible that additional information will need to be collected. The warehouse needs to have the ability to expand to meet the needs of the business. Warehousing would not be beneficial to a business if they have to seek a new warehouse source each time a change was needed; it would be costly for a business. A data warehouse must be a secure stronghold that protects the information, which is regarded as an asset to the business. In today’s society it this the utmost concerned of a business to make sure that their systems are not easily hacked by outsiders and their customer’s data is secured. Lastly, a warehouse is considered the foundation for decision making. It is the data that is retrieved from the system that is compiled for presentation to the decision makers of the company.

During ETL process, data from many sources will be extracted and integrated into data warehouse periodically. Extraction is a process to identified and retrieve all relevant data from the sources. The role of transformation is to cleansing the data and integrated different schema to defined schema in data warehouse. Meanwhile, loading is a process to physically move the data from operational system to data warehouse.