big data product optimisation

big data product optimisation - i BIG DATA FOR PRODUCT AND...

Info icon This preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon
i BIG DATA FOR PRODUCT AND PROCESS OPTIMISATION
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
ii Abstract Big data analytics provides organisations with an opportunity for continuously improving the performance of their products to meet the demands of the customers. The aim of this research study is to investigate how big data analytics can be used by organisations in assessing and improving the performance of their products. Using secondary data obtained from secondary sources such as books, journals, peer reviewed journals, credible websites and articles, data was collected about big data analytical and its use by organisations in assessing and improving the performance of their products. From the research findings, this research found that global companies use big data analytics to adapt to new technologies, which provide a strong basis for them to assess and enhance the performance of their products. Also, the study establishes that organisations use big data analytics to conduct research on how to optimize product and processes. Further, the study established that organisations such as real estate forms use big data analytics to enhance the performance of their products through reducing the financial risks associated with their products. Further, the study establishes that some of the challenges that organisations face in deploying and using big data analytics include difficulties in maintaining consistent and reliable data and limited knowledge and lack of a sophisticated team of IT experts and data scientists endowed with extensive knowledge on how to predict business trends. Moreover, the research findings demonstrate that big data analytics creates value to organisations through improving their sales turnover, revenue margins and growth rates; enhancing their decision making abilities and customer satisfaction levels; and helping in minimising financial risk and reducing in time wastage.
Image of page 2
iii Table of Contents Abstract ......................................................................................................................................................... ii CHAPTER ONE: INTRODUCTION ........................................................................................................... 1 1.1 Background of the Study .................................................................................................................... 2 1.2 Problem Statement .............................................................................................................................. 4 1.3 Aim and Objectives of the Study ........................................................................................................ 5 1.4 Research Questions ............................................................................................................................. 6 1.5 Thesis Disposition ............................................................................................................................... 6 CHAPTER TWO: LITERATURE REVIEW ............................................................................................... 8 2.1 General Overview of Big Data Analytics ........................................................................................... 8 2.2 Big Data and Organisational Performance ........................................................................................ 10 2.3 Business Intelligence ........................................................................................................................ 13 2.4 Big Data and Competitive Advantage .............................................................................................. 15 2.5 Comparison of Big Data Analytic Tools ........................................................................................... 17 2.6. Advantages and Disadvantages of the Tools ................................................................................... 20 CHAPTER THREE: METHODOLOGY ................................................................................................... 22 3.1 Tableau Software .............................................................................................................................. 22 3.2 Visual Analysis ................................................................................................................................. 22 3.3 Achieving Maximum Output from Tableau ...................................................................................... 24 3.4 Product Process Optimization ........................................................................................................... 26 3.5 Phase 1: Discovery ............................................................................................................................ 27 3.6 Phase 2: Prototyping ......................................................................................................................... 27 3.7 Phase 3: Scaling Out ......................................................................................................................... 28 CHAPTER FOUR: RESULTS ................................................................................................................... 30
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
iv CHAPTER FIVE: DISCUSSION ............................................................................................................... 36 CHAPTER 6: CONCLUSION AND RECOMMENDATIONS ................................................................ 44 6.2 Conclusions ....................................................................................................................................... 44 6.3 Recommendations ............................................................................................................................. 49 6.4 Limitations of this research and future research suggestions ............................................................ 50 References ................................................................................................................................................... 51
Image of page 4
1 CHAPTER ONE: INTRODUCTION Big data analytics provides organisations with an opportunity for continuously improving the performance of their products to meet the demands of the customers. The global manufacturing
Image of page 5

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 6
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern