Homework answers / question archive / DBA-806: EMPIRICAL ENTREPRENEURSHIP: DATA, TECHNOLOGY, AND BUSINESS INTELLIGENCE   Final Project     OVERVIEW Complete a final project based on the following scenario

DBA-806: EMPIRICAL ENTREPRENEURSHIP: DATA, TECHNOLOGY, AND BUSINESS INTELLIGENCE   Final Project     OVERVIEW Complete a final project based on the following scenario

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DBA-806: EMPIRICAL ENTREPRENEURSHIP: DATA, TECHNOLOGY, AND BUSINESS INTELLIGENCE

 

Final Project

 

 

OVERVIEW

Complete a final project based on the following scenario.

 

DAKOKOO Distribution Corporation supports Wal-Mart, Walgreens, and Target stores with product ordering, storage, and distribution. The company does not have big data technologies and is experiencing challenges in satisfying these customers’ contracts. The major issues are global product stockouts, lack of order lead-time data, and increased charges for expedited service.

 

As a newly hired DAKOKOO senior data scientist, you will develop a 16- to 20-page white paper on how to implement big data in DAKOKOO Distribution Corporation to solve their global supply chain company challenges.

 

Course objectives covered in this project include CO 1, CO 2, CO 3, CO 4, CO 5

 

 

GUIDELINES

Write this white paper to the company’s chief technology officer and chief information officer on the benefits of big data, business intelligence, analytics, and how to implement these technologies. The report should be 16 to 20 pages (4000 to 5000 words), excluding graphs, diagrams, and references. The paper at a minimum should include the following elements:

 

• Executive summary

 

• Problem statement

 

• Background/Literature review
  • Impacts of empirical entrepreneurship and economic development
  • Overview of analytics and big data sciences
  • Application of descriptive analytics in statistical modeling and visualization
  • Benefits and challenges of descriptive analytics in business intelligence and data warehousing
  • Predictive analytics used in the data mining process and algorithms
  • Benefits and challenges of predictive analytics in text, web, and social media analytics
  • Advantages and challenges of prescriptive analytics as related to optimizations and simulations

 

• Solutions/recommendations
  • Benefits of utilizing cloud computing and location-based analytics
  • Different big data concepts, vendors, and tools to be used to implement this technology
  • Privacy, ethical concerns, and organizational considerations
  • Recommendations on implementing the technologies—why and how the technology will help to solve the inventory shortages, logistical problems, revenue maximization, and cross selling

 

• References