Implementation Of Sql Server Database And Business Intellegince

As we discuss the possibility of emerging into business intelligence software we must keep in mind the overall purpose of using any type of software is to reach strategic goals in order to increase market shares. I will discuss how business intelligence software will allow us to meet those strategic goals. We will establish what type of information and analysis capabilities will be available once this business intelligence software is implemented. We will discuss hardware and system software that will be required to run specific business intelligence software. Lastly, I will give a brief synopsis on three vendors (IBM, Microsoft Microsoft and Oracle) that are dominating the business information software

Foremost, I would like to express my sincere gratitude to my advisor Ms. Upekha Manamendra for the continuous support of create this report, for her patience, motivation, enthusiasm and immense knowledge. I could not have imagined having a better advisor and mentor for create my report.

Wikipedia, http://en.wikipedia.org/wiki/Business_intelligence, defines business intelligence as “computer based techniques used in spotting, digging out and analyzing business data.” SQL Server’s Business Intelligence tools include the Reporting Services, Analysis Services, and Integration Services among others. A complete overview can be found at

I would like to thank the researchers who provided the information to help make this research possible and searchable. At Capella University, I owe so much to the mentors, the instructors and all of my wonderful cohorts that helped give feedback and offered personal assistance

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.

24) Before it can be loaded into the data warehouse, operational data must be extracted and

My deepest gratitude to my adviser Dr. Sayeed R. Mehmood for his continuous guidance, encouragement and support. Also, I am grateful to my graduate committee advisers Dr. Pelkki H. Matthew and Dr. Tamara Walkingstick for their guidance and support.

Data is fed into centralized data logging system and reporting tools to derive actionable reports

An important measure of any database management system is how effectively related data can be collected, organized and presented as reports, and also for business intelligence. What techniques from data warehousing and data mining would be used to facilitate this.

Data collected by a business includes internal data, such as financial or operational information, as well as external data, such as customer or website usage information. Properly analyzing and acting on this vast amount of data can transform the way companies do business and can become their biggest competitive advantage. Leaders of the organization no longer have to rely on their “gut instincts” to make key decisions, instead they will make decisions off historic data and will be able to more easily measure and track the effectiveness of those decisions.

Fact and data based decision making is a crucial element for success in today’s ultra-competitive business world. Many companies employ a multitude of analysts and statisticians to gather, organize and evaluate the mounds of data collected through various information systems. Late into the twentieth century companies finally halted the ancient ritual of storing data in basement file cabinets and began to rely on information technology systems to store enormous amounts of data on computer servers. Large amounts of data was being collected and stored but businesses lacked an effective way to utilize the data. During the same time period, numerous emerging technologies in computer science promised to enable the practical use of large amounts of data. SAS, originally referred to as Statistical Analysis Systems, is a company whose purpose is to create a way for users of its technology to access and utilize large amounts of data for analytical decision-making. SAS has made this possible through the creation of variety products and services that can manage a business’s data and customize its statistical analysis to improve business performance.

This thesis dissertation is a milestone of my academic career. I would like to express my sincere gratitude to my advisor Prof. Erick. C. Jones for his support for my MS thesis, for his immense knowledge, patience and motivation.

In the current business world, enterprises have developed strategies and technologies which are useful for data analysis of the associated business information. This information obtained is essential in making prudent business decisions. This developed strategies and technologies used for data analysis are known as business intelligence which is abbreviated as BI. Business Intelligence is associated with businesses issues which go around its history, current situation and a future analysis of the trend of business operation. In business intelligence technologies which are key to business survival include; reporting, online analytical processing, data mining, process mining, benchmarking, predictive analysis among others. This essay discusses issues associated with business intelligence, showing an historical background, its software applications, advantages and disadvantages of business intelligence as well as describing the competition that is witnessed between Google and IBM.

business intelligence finds accessible reports and analysis which may include dataware housing , datamining, analysis matrices, etc.

Increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have allowed the building of repositories to store this data. Improved ETL and enterprise application integration tools have increased the timely collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. As of 2010[update], business intelligence has become the art of sieving through large amounts of data, extracting useful information and turning that information into actionable knowledge.[citation needed]