BIG DATA AND ANALYTICS – ITECH1103

You are to design a scenario of your choosing. This scenario will be modelled initially as an ERD, and then implemented in SQL statements. As well as creating the requisite SQL.
Tables, you will need to manufacture data that is imported into these Tables. You will then be required to develop several SQL queries to provide key functionality for your database.

The purpose of this task is to provide students with practical experience in working in teams to write a data analytical report to provide useful insights, patterns and trends in the RETAILDEMO_2 dataset. This dataset is located in SAS viya archives of datasets. This activity will give students the opportunity to show innovation and creativity in applying SAS analytics, and designing useful visualisation and predictive solutions for various analytics problems.

    • Explorer techniques, tools and applications of Big Data.
    • Identify the Australian Computer Society`s (ACS) Core Body of Knowledge (CBOK) and where it is represented in industry practice.
    • Conduct critique research and industry practice to determine your place in the spectrum of career possibilities.
    • Utilise Analytical tools

    1. Group Task: Create a data dictionary for the data source for use by the group.
    2. How much is marketing and marketing budget allocated to each industry ?
    3. What are the top and bottom 5 cities with respect to the number of customers?
    4. What is the distribution of customers by department in each country?
    5. What is the distribution of customers by group chain in each country? Add animation of the Date.
    6. What is the trend of transactions over months for each brand?
    7. For each store chain, which is the most and least popular class?
    8. What are the top and bottom 10 products ID in terms of Sales?
    9. What are top and bottom 5 classes with respect to the number of transactions?
    10. What is the popular brand with respect to frequency in each department in different countries?

The purpose of the video presentation is to provide an opportunity for students to present the data analysis results to everyone and to share their knowledge while practising their verbal communication skills. Students should use PPT to present their findings and recommendations.

Learn the diverse types of contemporary Big Data (e.g. IoT, social data).
Communicate and present the results of the Data Analytics process.
Learn to apply Big Data Analytics technology to a real-world dataset.

The presentation must include:
An introduction of the topic and team members. The findings made from the analysis of the data including images to support these findings. The recommendations you will make in your report a conclusion