Investigative Task Force. Include Information
¶ … investigative task force. Include information regarding the structure of a multi-agency investigative task force to include: manpower, information sharing, jurisdiction, participation, vehicle assignments,…
Research Paper
Undergraduate
Computer Ethics the Internet\'s Rapid
The Internet's rapid evolution as a publishing and commerce platform further extends its ability to serve as another marketing, selling, and service channel for companies globally, yet with this potential for revenue…
Data mining applications across retail, banking, healthcare, and marketing
In this paper we determine benefits of data mining to the businesses when employing:
1. Predictive analytics to understand the behavior of customers
2. Associations discovery in products sold to customers
3. Web mining to discover business intelligence from Web customers
4. Clustering to find related customer information
The paper also assesses the reliability of the data mining algorithms and then decides if they can be trusted and then predict the errors they are likely to produce. An analysis of the privacy concerns raised by the collection of personal data for mining purposes is also conducted.
Data Warehousing and Data Mining
Analytics, Business Intelligence (BI) and the exponential increase of insight and decision making accuracy and quality in many enterprises today can be directly attributed to the successful implementation of Enterprise Data Warehouse (EDW) and data mining systems. The examples of how Continental Airlines (Watson, Wixom, Hoffer, 2006) and Toyota (Dyer, Nobeoka, 2000) continue to use advanced EDW and data mining systems and processes to streamline their business models are a case in point. The greater the level of economic uncertainty, perceived and actual risk in any given strategy or endeavor, the more the reliance on EDW, data mining and advanced forms of predictive modeling including analytics (Sen, Ramamurthy, Sinha, 2012). From this standpoint, the emerging areas of high growth in the global economy are attracting a high level of investment in EDW, data mining, predictive modeling and analytics. The latest figures illustrate how valued EDW and data mining are in enterprise today. According to industry research and advisory firm Gartner, the EDW and data mining market began 2011 with a global value of $23.2 billion with a projection of market growth of 7% per year through 2015, making it one of the largest and perennially growing enterprise software market (Sen, Ramamurthy, Sinha, 2012). Gartner has defined the EDW and data mining architecture as being comprised of the architectural design, repository and execution platform. These three core components are how this research and advisory firm analyze the market from a software component standpoint, looking at the relative adoption of each EDW and data mining component (Sen, Ramamurthy, Sinha, 2012). The intent of this analysis is to evaluate the benefits and current trends in EDW and data mining, evaluating Continentals' and Toyota's best practices and results achieved. Additional objectives include an assessment of EDW and data mining optimization techniques, recommendations for storage solutions and an analysis of a potential EDW process workflow predicated on a Customer Relationship Management (CRM) system.
The internet and the future of computers in society
Baker, W., Hylender, C., Valentine, J. (2008) Verizon Business Data Breach