Putting all together involves communicating and operationalizing an analytics project. Creating the final deliverables and using a core set of material for different audiences. Comparing main focus areas for sponsors and analysts and understanding simple data visualization principles including cleaning up a chart or visualization. Several industries have led the way in developing their ability to gather and exploit data: –
1.Credit card companies monitor every purchase their customers make and can identify fraudulent purchases with a high degree of accuracy using rules derived by processing billions of transactions.
2. Mobile phone companies analyze subscribers’ calling patterns to determine, for example, whether a caller’s frequent contacts are on a rival network. If that rival network is offering an attractive promotion that might cause the subscriber to defect, the mobile phone company can proactively offer the subscriber an incentive to remain in her contract.
3. For companies such as LinkedIn and Facebook, data itself is their primary product. The valuations of these companies are heavily derived from the data they gather and host, which contains more and more intrinsic value as the data grows.
References: Data Science and Big Data Analytics. Wiley Professional, Reference & Trade, 20150105. VitalBook file.
1. Select your case study organization from one of the following sectors; credit card, mobile, phone, or social media: LinkedIn or Facebook. Describe the five common deliverables for an analytics project applicable to the organization selected.
2. Explain how the company gather and exploit data by giving examples of the appropriate charts. Explain why the charts are appropriate to show each audience.
3. Explain what types of graphs would be appropriate to show data changing over time and why. As part of operationalizing an analytics project, describe which deliverable would you expect to provide to a Business Intelligence analyst.
4. Ensure to integrate the final deliverables using a core set of material for different audiences. Comparing focus areas for sponsors and analysts and understanding simple data visualization principles including data cleaning up, visualization, ability to gather and exploit data, communicating and operationalizing an analytics project.
• About 6-8 pages. Maximum allowed submission is two.
• Follow standard APA guidelines, including an abstract, conclusion, and a reference page with a minimum of three references.
• Include a cover page that should contain the following: Title, Student’s name, University’s name, Course name, Course number, Professor’s name, and Date. • Clickable auto-generated Table of Content is required
• Figures and Tables used should be labeled according to APA guidelines •
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