Your Team Will Select A Big Data Analytics Project That Is I ✓ Solved

Your team will select a big data analytics project that is i

Your team will select a big data analytics project that is introduced to an organization of your choice. Please address the following items:

(a) Provide a background of the company chosen.

(b) Determine the problems or opportunities that this project will solve. What is the value of the project?

(c) Describe the impact of the problem. In other words, is the organization suffering financial losses? Are there opportunities that are not exploited?

(d) Provide a clear description regarding the metrics your team will use to measure performance. Please include a discussion pertaining to the key performance indicators (KPIs).

(e) Recommend a big data tool that will help you solve your problem or exploit the opportunity, such as Hadoop, Cloudera, MongoDB, or Hive.

(f) Evaluate the data requirements. Here are questions to consider: What type of data is needed? Where can you find the data? How can the data be collected? How can you verify the integrity of the data?

(g) Discuss the gaps that you will need to bridge. Will you need help from vendors to do this work? Is it necessary to secure the services of other subject matter experts (SMEs)?

(h) What type of project management approach will you use for this initiative? Agile? Waterfall? Hybrid? Please provide a justification for the selected approach.

(i) Provide a summary and conclusion.

(j) Your written paper must have at least 10 reputable sources and 10-to-15 pages.

(k) Please write the paper in APA Style. Provide an outline of the work to be performed. You can submit in MS Word or PPT. Please make sure to include company name, background, and how the work will be divided with the names of team members. You may start on the written paper. Written Paper: The requirements for the written paper are provided above. Please note that each team member must have a deliverable. Please ensure that you avoid any plagiarism issues. Include the name of the team member and Student ID for the section they completed.

Paper For Above Instructions

Title: Big Data Analytics Project for Walmart Inc.

Introduction

In contemporary business, organizations are increasingly leveraging big data analytics to drive decision-making and enhance operational efficiency. This paper focuses on a big data analytics project for Walmart Inc., a global leader in retail. The objective is to analyze the company’s current operational challenges and identify opportunities for improvement through data-driven strategies.

Company Background

Walmart Inc. was founded in 1962 by Sam Walton and has grown to become one of the largest retailers in the world. With over 10,500 stores in 24 countries, Walmart serves millions of customers weekly. The company operates under various formats including supercenters, discount stores, and warehouse clubs. Walmart is known for its cost-leadership strategy, aiming to provide customers with low prices and vast product selections.

Identifying Problems and Opportunities

Despite its market dominance, Walmart faces several challenges, including supply chain inefficiencies, elevated operational costs, and the need for enhanced customer experience. The big data analytics project aims to address these issues by developing insights into consumer behavior and optimizing inventory management. The value of this project lies in its potential to reduce operational costs, enhance customer satisfaction, and improve inventory turnover rates.

Impact of the Problems

Walmart's operational inefficiencies lead to financial losses estimated in billions annually due to overstocking and stockouts. Furthermore, unexploited opportunities in online shopping and personalized marketing strategies can adversely affect the company’s competitive edge. Addressing these issues through an effective big data analytics approach could yield substantial financial benefits.

Performance Metrics and KPIs

To measure the success of the analytics project, several key performance indicators (KPIs) will be utilized, including inventory turnover ratio, customer satisfaction score, and sales per square foot. These metrics will provide insights into inventory management efficiency, customer experience improvements, and overall financial performance. We will conduct periodic assessments to monitor progress towards the set objectives.

Recommended Big Data Tools

For this project, we recommend utilizing Hadoop because of its robustness in handling large datasets and its capability to integrate with various data processing tools. Hadoop's ecosystem will facilitate the storage, processing, and analysis of the data collected from various touchpoints within the organization.

Data Requirements

The project requires various types of data, including sales data, customer transaction histories, and supply chain information. These datasets can be sourced from Walmart's internal databases, POS systems, and customer interactions via online platforms. Data collection will be facilitated through API integrations, surveys, and transactional data analysis. Verification of data integrity will involve regular audits and employing data validation techniques to ensure accuracy and reliability.

Bridging Gaps

To effectively implement the project, there are gaps such as insufficient expertise in data analytics and potential technology integration challenges. Collaboration with data analytics vendors will be necessary, as well as securing services from subject matter experts (SMEs) to ensure best practices are followed and the analytics tools are used effectively.

Project Management Approach

We propose adopting an Agile project management approach for this initiative due to its flexibility and iterative nature. This methodology allows for continuous feedback, adaptations, and improvements throughout the project lifecycle, ensuring that the evolving needs of Walmart’s operations are adequately addressed.

Summary and Conclusion

The proposed big data analytics project for Walmart Inc. is aimed at addressing critical operational challenges while uncovering untapped opportunities for growth. By harnessing advanced data analytics tools and methodologies, Walmart can improve its inventory management, enhance customer experience, and ultimately drive greater profitability. As the retail landscape continues to evolve, leveraging big data will be essential for sustaining competitive advantage.

References

  • Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An Overview of Business Intelligence Technology. Communications of the ACM, 54(8), 88-98.
  • McKinsey & Company. (2021). The state of AI in 2021: 10 things you need to know.
  • Walmart Inc. (2022). Annual Report 2022. Retrieved from Walmart Annual Reports
  • Kumar, A., & Singh, H. (2020). Big Data Analytics: Opportunities and Challenges. Journal of Business Research, 115, 257-261.
  • Cohen, J. (2020). Using Big Data to Improve Supply Chain Management. Supply Chain Management Review.
  • SAS Institute Inc. (2019). What is Big Data Analytics? Retrieved from SAS Insights
  • Oliveira, T., & Martins, M. F. (2011). Literature Review of Information Technology Adoption Models at Firm Level. The Electronic Journal Information Systems Evaluation, 14(1), 110-121.
  • Sharma, R., et al. (2017). Importance of Big Data Analytics in e-commerce and retail. Journal of Global Operations and Strategic Sourcing, 10(2), 103-118.
  • Gonzalez, S. (2021). How Retailers are Using Big Data to Improve Customer Experience. Retail Dive.
  • Hossain, M. I., & Sultana, R. (2022). Exploring Big Data Analytics in Retail: A Contemporary Review. Journal of Retailing and Consumer Services, 64.

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