Abstract The expansion of today’s technology has lead to the ability to now extend BI applications to handheld mobile devices such as tablets and mobile phones.
With the current availability of mobile business intelligence applications companies can now data mine, create reports and analyse data all in real time.
Mobile Business Intelligence empowers managers to be able to make decisions in real time by being able to process and create their reports remotely. Whereas before they would have had to make several calls and emails to receive the information they desire, which takes time and jeopardises making an accurate and timely decision.
For a company to introduce the use mobile business intelligence there are a number of factors they must consider in order to make for a smooth implementation. These factors include hardware, software, training and documentation, bandwidth, and security.
Ensuring implementation is smooth and all factors are considered, mobile business Intelligence has the potential to improve decision making capabilities, data verification, time saving, resource allocation, productivity, environmental sustainability and revenue.
A number of software applications have been developed to make mobile business intelligence possible. MicroStrategy is one of the leading mobile business intelligence tools that have appeared in this new era of mobile intelligence. MicroStrategy allows the user to create reports and view dashboards, mine into multidimensional data, complete transactions, view rich multimedia, display data visualisation, and much more. What makes MicroStrategy different is that users can design the application to meet their own requirements, all in a low cost solution.
MicroStrategy has been used in a number of companies with great success. A few examples of their excellence is through their involvement in eHarmony and GUESS.
With mobile business intelligence companies can continue to compete for market share as without it, they would most probably be left behind.
Contents Abstract 2 Introduction 4 Security 6 Bandwidth 7 Users 7 Return on investment 9 Facts and Figures 9 Business Value 10 1. Improved productivity 10 2. Improved Agility 10 MicroStrategy 11 Software Tool 13 Case Study 16 Conclusion and implications 18 References 20
Introduction
Business intelligence is a very wide category including the use of technologies and the applications in order to gather, store, analyse and provide access to the data and information for the benefit and help of enterprise users to make better decisions for the business. The processes involved in BI applications include decision making, support systems, query and reporting and online analytical processing (OLAP), forecasting, statistical analysis and data mining. The BI applications can be of different types like these can be critical to missions, and these can also be integral to the operations of the enterprise or occasional in order to meet special requirements. These applications can also be enterprise wide or these can also be local to one division, project or department. The BI applications can also be initiated centrally or can be driven by user demand. The main aim of the business intelligence is to support the decision making for the business for the maximum efficiency and output. So it can also be called decision support system (DSS). (Negash, 2004)
Figure 1: Business Intelligence processes
The first process involved in the Business Intelligence is Gathering the data, which is concerned with the collection and the access of the data which can be utilized to inform for the making of the decisions. The gathering of data can also come in many formats and it is basically referred to the automated measurement and the performance data collection. The major challenge in gathering the data is making sure that relevant and related data is collected in a right way at the time
