Business Intelligence : Knock Down Silos

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

Business Intelligence (BI) is the consolidation and analysis of internal data and / or external data for the purpose of effective decision-making. At the core of all BI initiatives is a data warehouse to hold the data and analytics software. The data warehouse stores data from operational systems in the organization and restructures it to enable queries and models to extract decision support reports.

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.

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 industry today.

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.

Twila Day left the meeting excited, but also a little nervous. Her Technology and Applications Group had just been given approval by the Director’s Council of SYSCO to proceed with a company- wide deployment of business intelligence (BI) software. The effort was intended to help SYSCO, the largest food distributor in North America, make better use of the information generated by its operations and serve its customers better. The Director’s Council, a group of senior managers with substantial power and influence, had been impressed enough by the results of a

Companies are adopting business intelligence system within their organizations because by using the system reports they can gain the advantages of understanding their internal strength and weaknesses to face external competitors and challenges to increase profits and reduce cost on their everyday operations and processes.

Walmart is the biggest retailer in the world and handles more than one million customer transactions every hour and generates more than 2.5 petabytes of data storage (Venkatraman & Brooks, 2012). To put this into perspective, this data is equivalent to 167 times the number of books in America’s Library of Congress (Venkatraman & Brooks, 2012). So how can Wal-Mart use this massive amount of data and what useful information can this data provide? This paper will provide a brief overview of the importance of Business Intelligence (BI) and how the largest retailer in world, Walmart, is using it.

Design, code and deliver user friendly multi-tier business intelligence solutions that utilize data warehouse/data mining technologies to consume data across various database platforms and data stores.

Many large companies have been using business intelligence (BI) computer software for some years to help them gain competitive advantage. With the introduction of cheaper and more generalized products to the market place BI is now in the reach of smaller and medium sized companies.

Business Intelligence information consists of chronicled data, and additionally new information assembled from source frameworks as it is generated, empowering Business Intelligence supports multi-level decision making processes. Initially, Business Intelligence tools were essentially utilized by IT experts and data analysts whose job is to run analyses and generate reports with query results for business clients. Progressively, however, business administrators and workers are utilizing BI software themselves, on account of the advancement of self-administration of BI and data discovery tools

How much will organizations spend on business intelligence (BI) in 2016? According to Gartner, organizations are projected to spend almost $16.9 billion in 2016. That is an increase of 5.2% over 2015 sales . Business Intelligence plays a big role in today’s business, it now used in every part of the organization from supply chain to human resources (www.gartner.com). This paper will compare two business intelligence software tools. First, I will define business intelligence (BI). Then, I will examine the features of each of the BI tools. Next, I will discuss the pros and cons of each software. This paper will focus on the capabilities and costs for each BI software. Lastly, this paper will indicates which choice was made and an explanation of that choice.

Business intelligence involves techniques based on computers that are used in the identification, extraction, as well as the analysis of business data(Electrosmart Ltd). The business data in this case could be revenue from sales made from given products, could also be sales that a given department has made, or

Business intelligence can provide companies with accurate data that can be analyzed to support business strategy therefore enabling companies to better predict effectiveness of their business goals and ultimately result in a business profit. “Business intelligence is already in use in many organizations today, by finance departments to analyze financial performance, sales and marketing to identify customer trends, and operations to enhance the efficiency of supply chains. Using real data helps them answer who, what, where, why and when of related performance” (Rylander,2009).

In the increasingly competitive global business environment, each organization needs to take advantage of every tool, opportunity, and advantage it can to achieve the best products and services, to gain and maintain market share, and keep stakeholders happy from investors and workers to supply chain and customers. The advance of data analysis has opened up new vistas to support decision making. Decision support systems (Sauter, 2010) have emerged that process various forms of data to build outcome models. These have been adopted in every segment of society, in the private and public sector, from political campaigns and the military to corporations and nonprofits alike. As a whole, the new set of tools involving the strategic use of data is called business intelligence. Within that general framework, the term analytics refers to the statistical, quantitative use of data to produce explanatory and predictive models for fact-based decision making. (Sauter, 2010).