A Comprehensive Analysis Of Data Warehouse And Olap Technology Essay

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

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.

In data warehousing, there is a distinction between a data warehouse and a data mart. A data warehouse collects information about subjects that span the entire organization, such as customers, items, sales, assets, and personnel, and thus its scope is enterprise-wide. For data warehouses, the fact constellation schema are commonly used since it can model multiple, interrelated subjects.

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

Information tеchnology is now еssеntial in еach part of our livеs which hеlp businеss and еntеrprisе to makе usе of applications likе dеcision support systеm, rеporting and quеry onlinе analytical procеssing, and prеdictivе еxamination and businеss routinе managеmеnt. A data warеhousе is a rеpository of rеlational databasеs dеsignеd for quеry which is analyzеd by data mining tеchniquе allowing еnormous data sеts to bе еxplorеd so as to yiеld hiddеn and unidеntifiеd еxpеctations that can bе usеd in futurе for еffеctivе dеcision making.

The data warehouse is that portion of an overall Architected Data Environment that serves as the single integrated source of data for processing information. The data warehouse has specific

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.

A data warehouse is a place where data is stored for archival purpose, analysis purpose.

The success of the database and data warehouse (DW) project really depends on the quality of data. If data quality is not good enough, the information will logically be unreliable when the business users retrieve it from the database/DW environment. Good quality of data will be useful for the decision maker to make the right decision, gain more trust and make the organization more efficient. In contrast, the bad quality of data will drive the decision maker to make a wrong decision.

Data warehouse (DW of DWH) also called enterprise data warehouse (EDW) refers to the system utilized in the analysis and reporting of data. The can be described as the main component making up business intelligence. Normalized data warehousing describes the repositories containing integrated data form several dissimilar sources. It contains information which can be utilized in creating investigative reports for the various users within an organization. Examples of reports that can be retrieved from these repositories include annual and periodic trends of sales within the organization. The data contained in these sources is uploaded form the operational systems and hence can be utilized in making accurate reports regarding the operations. Before the data can be used for reporting purposes it could pass through operational data stores. This reports presents summaries of researches conducted in topics seeking to describe various normalized models of data warehousing. The research covers the topics indicated in the table below

Due to the advancement that has been realized, the amount of data being generated may be overwhelming. Many proposals on data warehouses can solve this problem and handle the complex data. However, one challenge often occurs as a result of the analysis. The terminology used by different companies in OLAP is

The term Data Warehouse was first coined by Bill Inmon, who has been commonly recognized as the “father of data warehousing” and is the lead proponent of the normalized or sometimes referred to as the top-down, approach to Data Warehouse design (Reed, M.)(Data

Mainly, in the data warehouse analyzing the large data helps the decision-making process. Indeed, in the data warehouse, the integration of the data from the

The data in a data warehouse comes from operational systems of the organization as well as from other external sources. These are collectively referred to as source systems. The data extracted from source systems is stored in a area called data staging area, where the data is cleaned, transformed, combined, deduplicated to prepare the data for us in the data warehouse. The data staging area is generally a collection of machines where simple activities like sorting and sequential processing takes place. The data staging area does not provide any query or presentation services. As soon as a system provides query or presentation services, it is categorized as a presentation server. A presentation server is the target machine on which the data is loaded from the data staging area organized and stored for direct querying by end users, report writers and other applications. The three different kinds of systems that are required for a data warehouse are: