Development of a Business Intelligence System

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

The theme of this book is how businesses in today’s world use ever-improving technology to collect data, convert it into information and business intelligence, and combine this information and intelligence with the knowledge of the workers to help make the best decisions they possibly can for the benefit of the company and the customers. Throughout the book, there are discussions on the different ways that technology can help a business with this process. When going into detail about the various information systems, this book also brings into

Business intelligence (BI) merges architectures, tools, databases, analytical tools, applications, and methodologies. It also is context free like DSS. BI deduces the connections between business entities by evaluating copious volumes of historical data which supports decisions. BI has four major components consisting of a data warehouse, business analytics, business performance management, and a user interface.

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.

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.

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).

With the global marketplace becoming increasingly competitive and the insatiable appetite for business information, the volume of data that must be managed and assimilated is growing at an exponential rate. Global corporations take advantage of the current technologies, and infrastructures, require standard processes, consistent data to enable global consolidation and the ability to transform raw data into business intelligence to support better decision making.

A data warehouse and business intelligence application was created as part of the Orion Sword Group project providing business intelligence to order and supply chain management to users. I worked as part of a group of four students to implement a solution. This report reflects on the process undertaken to design and implement the solution as well as my experience and positive learning outcome.

Business intelligence systems are the combination of operational data and analytical tools to aid managers to comprehend the “capabilities available in the firm, the industrial trends, future development in technologies and the market and even their competitor’s actions and the resulting implications” (Wang, 2014, p. 1083). There are many ways managers can use the information a business intelligence system gives them such as understand customer behavior, analyzing competition understanding investment options, and knowledge protection.

IT methods and operating policies that work well for transactional systems and web applications are impeding the ability to do business intelligence in rapid increments with high business impact.

Business Intelligence is all about decision making with a data driven approach. It is a broader term and a super set containing tools, architectures, technologies and techniques that leverage insights from data (various problems or business processes) for analysis, querying, reporting and performance improvement. It is based on measuring or analyzing the historical data and past performance for driving insight and answers to questions like “What occurred?”, “How frequently is occurred?” and “Its impact?”. It includes processes and techniques for data collection, data analysis, data sharing, and reporting using dashboards, illustrative reports and interactive visualizations that laymen understand, all in the service better data driven decision making.

In the enterprise world, business intelligence has become a common necessity in every organization whether big or small. According to Shollo and Kautz (2010, p. 1), business intelligence is defined as ‘a process, a product, and as a set of technologies, or a combination of these’. Input from a wide range of corporate stakeholders is essential to implement an effective corporate business intelligence strategy. The purpose of a corporate business intelligence strategy is to aid business with planning in a long run, to aid middle management with tactical reporting, and help operations with daily decision making to efficiently run a business (Pant 2009). A stakeholder is anybody who has an interest in a particular decision which includes people who influence a decision, or could influence it, as well as those affected by it. Contribution of corporate stakeholders in corporate business intelligence strategy will result in the strategy to be successful as well as yield more positive stakeholders.

“Technology creates visibility across the business, and enterprise-wide operational practices are essential to optimal efficiency and effectiveness. The strategic implementation of business intelligence tools and analytics, along with cross-departmental alignment, can transform data into meaningful, useful information for critical analysis. Proactive and investigative BI reporting techniques can help recognize new business opportunities and provide firms with a competitive industry advantage.” - Scott Lundstrom, group vice president and general manager of IDC Financial, Government and Health Insights (Sungard, 2014a).

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.