Enterprise Business Intelligence Report: Mobile Data Analysis

This report delves into the application of business intelligence within a mobile business context. It begins with an introduction to business intelligence and its role in data analysis, particularly for price structure planning. The report then identifies data anomalies through univariate statistics, focusing on factors like battery power, clock speed, RAM capacity, and microprocessor performance. It addresses issues related to R-studio, such as battery storage and RAM limitations, and proposes solutions including k-mean clustering to determine value proposition improvements. The analysis aims to enhance microprocessors and battery capacity to boost sales and competitiveness. The conclusion emphasizes the value of business intelligence for organizational planning and profitability, highlighting the resolution of R-studio queries through appropriate techniques and data analysis tools. The report references key literature on business intelligence and its implementation in enterprise environments.

Enterprise Business
Intelligence

Content covered
• Introduction
• Identification of abnormalities
• Evaluation of issues
• Resolution to those queries
• Conclusion
• References

Introduction
Business intelligence is one of the most effective technology which
used for analysing data and presenting actionable data to assist
company to plan their price structure for their mobile business.

Identification of anomalies
Univariate Statistics
N Mean Std. Deviation Missing No. of Extremes
Count Percent Low High
battery power 2276 1244.58 438.164 4 .2 0 0
blue 2276 .50 .500 4 .2 0 0
clock speed 2272 1.535 .8166 8 .4 0 0
dual_sim 2261 .52 .500 19 .8 0 0
fc 2259 4.38 4.367 21 .9 0 104
four_g 2258 .51 .500 22 1.0 0 0
int_memory 2269 32.39 18.210 11 .5 0 0
m_dep 2272 .504 .2849 8 .4 0 0
mobile_wt 2267 139.45 35.142 13 .6 0 0
n_cores 2274 4.45 2.283 6 .3 0 0
pc 2268 9.92 6.046 12 .5 0 0
px_height 2269 641.69 439.098 11 .5 0 90
px_width 2257 1241.65 432.550 23 1.0 0 0
ram 2268 2120.74 1086.254 12 .5 0 0
sc_h 2273 12.15 4.224 7 .3 0 0
sc_w 2280 5.62 4.273 0 .0 0 88
talk_time 2280 10.98 5.479 0 .0 0 0
three_g 2280 .76 .427 0 .0 0 0
touch_screen 2280 .50 .500 0 .0 0 0
wifi 2280 .50 .500 0 .0 0 0
a. Number of cases outside the range (Mean - 2*SD, Mean + 2*SD).

Issues related to R-studio
This first issues they are facing is related with the below
mentioned terms:
•Battery storage
•Ram capacity
•Microprocessors
•Other

Solution to queries
• They are using k-mean clustering test to resolve various
issues. It will assist them to determine the total value
proposition to the company as well as the client.
• Improvement in the overall microprocessors and battery
capacity.
• This will lead to increase the total number of sales in the
mobile phone and assist in facing their competitors.

Conclusion
From the above discussion, it can be said business
intelligence is valuable aspects for an organisation in order
to plan their activity to attain maximum profit in near future
time. All the queries that are faced by the R-studio can be
resolve by using appropriate techniques and data analysis
tools.

References
Loshin, D., 2012. Business intelligence: the savvy
manager's guide. Newnes.
Zeng, L., Li, L. and Duan, L., 2012. Business intelligence in
enterprise computing environment. Information
Technology and Management. 13(4). pp.297-310.

Thank You