discussion

Siddhartha Annamaneni 

week 13

COLLAPSE

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Combating proliferation of Drugs

Social problems such as Drug use and abuse are in the hands of policy makers who need to make decisions that are likely to reduce the impact of drug abuse in developing countries such as the case of Petersburg. In the public sector, the decision-making process has been improved, thanks to the availability of big data-based tool. According to Höchtl, Parycek, & Schöllhammer (2016), data mining process has made the process of decision making to be highly informative as policy makers are using data to make informed decision.

In the above case, a number of analytical concepts can be applied and enhance the decision makers in the above area to make informed decision. First, data has to be collected from the area of study and the policy makers should define the various objectives within the analyzed data set. In the above case, there are a number of analytical tools that can be used in analyzing the data and be able to carry out predictive and forecast analysis. One of the tools that is available for business intelligence and data mining processes is RapidMiner, Tableau, and SAS (Höchtl, Parycek, & Schöllhammer, 2016). With these tools, data can be uploaded to the platform, analyze it and then present the results. According to Charalabidis, Alexopoulos, & Loukis (2016), in dealing with societal problems, the policy makers can follow simple analytical model processes that includes formulating the hypothesis, deploy the relevant analytical tools, with the tools uncover new patters, and then inform an enrich.

For example, out of the analyzed data, the policy makers can be able to understand and predict a pattern in which they can get to know which age bracket is highly consuming the drug substances, the patterns in drug consumption in specific localities, the areas that are highly affected and the areas that are not affected. Therefore, this can help the policy makers to make decisions that are motivated by data. Furthermore, these analytical tools can be use in creating dashboards which will represent a summary of the mined data whereby the policy makers can get a glimpse of the whole data mining process and get a clear picture of the social problem (Charalabidis, Alexopoulos, & Loukis, 2016). For the areas that highly affected, corrective measures can be deployed such as drug rehabilitation and even deploying authorities to deal with the peddlers. On the other hand, the areas that are less affected, motivational speakers can be sent to educate the masses and inform them the negative side associated with these substances.

References

Charalabidis, Y., Alexopoulos, C., & Loukis, E. (2016). A taxonomy of open government data research areas and topics. Journal of Organizational Computing and Electronic Commerce, 26(1-2), 41-63.

Höchtl, J., Parycek, P., & Schöllhammer, R. (2016). Big data in the policy cycle: Policy decision making in the digital era. Journal of Organizational Computing and Electronic Commerce, 26(1-2), 147-169.

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