RWSL Assignment Part two of the Continuous Assessment - Quotation

RWSL Assignment Part two of the Continuous Assessment - Quotation

The original text is taken from the Journal IT Professional

Author: Colleen McCue

Article title: Data Mining and Predictive Analytics in Public Safety and Security
IT Professional (Volume: 8 ,  Issue: 4 ) Page(s): 12 - 18
Date of Publication: July-Aug. 2006; ISSN:  1520-9202
Digital Object Identifier: 10.1109/MITP.2006.84
INSPEC Accession Number: 9137302
Sponsored by: IEEE Computer Society
Sub-section title: Data challenges

Data Analytics is a process that includes the collecting of data, processing the data, cleaning the data, transforming and modelling the data in order to find patterns in the data that can be used to make decisions or predict future trends (Data Analysis, Wikipedia).

Predictive analytics is the process of making future prediction by using analytic techniques from various disciplines like Data Mining, Statistics, Modelling, Machine Learning, to analyse data (Predictive Analytics, Wikipedia).

The use of data mining and predictive analytics technology in almost all areas of life has increased significantly over the years. Its applications areas has extended from the mostly business sphere to include other areas like politics, manufacturing, education and application in general social areas like social security and safety (Colleen McCue, 2006). The data mining and predictive analysis technology has got the intelligence and ability, not just to process large data sets and look for patterns, but also to use the results to predict future trends or to make informed decisions.  The technology is applied a lot in sensitive areas like the public safety and security. This widespread application of the technology notwithstanding, Data Analysts still faces a lot of challenges like how to access the right data for the required analysis or how extract the specific data required from the excessive data that may be available. As Colleen McCue wrote,

The challenges associated with public safety and intelligence data transcend the oft-cited “stove pipes” that limit access and functional integration of data resources. Fundamental issues associated with the fact that most (if not all) public safety and intelligence data resources were collected for reasons other than analysis seriously limit the analyst’s ability to extract meaningful output from these data. Moreover, it is difficult (if not impossible) to anticipate the array of data resources that analysts will encounter during the course of their work. Incident data, narrative reports, financial transactions, telephone records, and Internet activity represent only a few of the many and varied information resources used in crime and intelligence analysis… .

Clearly these factors impede the work of the Analyst but Analysts still work hard enough to achieve effective results that are not affected but these shortcomings

References

1. Wikipedia, Data Analysis. http://en.wikipedia.org/wiki/Data_analytics 
[Accessed 21 November 2013]

2. Wikipedia, Predictive Analytics. http://en.wikipedia.org/wiki/Predictive_analytics  

[Accessed 21 November 2013]

3. McCue, Colleen, "Data Mining and Predictive Analytics in Public Safety and Security," IT Professional , vol.8, no.4, pp.12,18, July-Aug. 2006