MIS771 – DESCRIPTIVE ANALYTICS AND VISUALISATION
Subject Code – MIS771
Subject Name – Descriptive Analytics and Visualisation
University Name – Deakin Business School, Australia
In today's data-driven world, making informed decisions is paramount. Data analysis plays a crucial role in extracting meaningful insights from raw information. In this blog, we'll unravel the concepts of data analysis and data visualization, and provide you with practical steps on how to effectively analyse your data.
Descriptive Analytics and Visualisation MIS771, This subject includes the following topics data analysis, Data visualisation, and evidence-based decision-making. The subject aims to help students understand how software is extensively used to develop data visualisation and analysis skills.
Data Analysis is a method to collect, understand, and analyse data to discover useful information for business decision-making.
Steps to analyse the data:
Define your goals
Decide how to measure goals
Collect data
Analyse data
Visualise and interpret results
Data visualisation is a graphical representation of data and information. It is generally used to discover unknown facts and trends.
Data Analysis: Data analysis involves examining, cleaning, transforming, and interpreting raw data to discover meaningful patterns, trends, and insights. It's the process of converting data into actionable information that can guide decision-making and problem-solving.
Data Visualization: Data visualisation is the art of presenting data in visual forms such as graphs, charts, and maps. It aims to convey complex information in a clear and understandable manner, enabling quick comprehension of trends and patterns.
Importance of Data Visualization: Data visualisation is a simple and effective approach to conveying information to a broad audience using visual data. The practise can also assist businesses in determining which factors influence customer behaviour, identifying areas that need to be improved or given more attention, making data more memorable for stakeholders, determining when and where specific products should be placed, and forecasting sales volumes.
Deakin Business School is located in Victoria, Australia. Deakin Business School is recognised as one of the top business schools in the world. The university offers a huge range of business courses at the undergraduate and postgraduate levels.
1.
Define Your Objective:
Clearly define what you want to achieve through data analysis. Whether it's uncovering sales trends, customer behaviour, or operational inefficiencies, a well-defined objective will guide your analysis.
2.
Collect and Organise Data
Gather relevant data from reliable sources. Organise the data into a structured format, ensuring that it's clean and complete.
3.
Exploratory Data Analysis (EDA)
Before diving into complex analyses, perform exploratory data analysis. This involves calculating summary statistics, identifying outliers, and creating basic visualisations to gain initial insights.
4.
Choose the Right Analysis Techniques
Depending on your objective, choose appropriate analysis techniques. Common techniques include descriptive statistics, inferential statistics, regression analysis, and clustering.
5.
Apply Statistical Tests
If applicable, use statistical tests to determine relationships between variables and to validate hypotheses. Examples include t-tests, ANOVA, and correlation analysis.
6.
Create Visualizations
Transform your data into insightful visuals. Choose suitable charts (bar graphs, line charts, scatter plots) to effectively communicate your findings.
7.
Interpret Patterns and Trends
Analyse your visualisations to identify patterns, trends, and anomalies. Are there correlations between variables? What insights can you draw from the data?
8.
Validate Results
Ensure that your findings are statistically valid and not due to chance. Always validate your conclusions through appropriate statistical measures.
9.
Draw Insights and Make Decisions
Based on your analysis, draw meaningful insights and make informed decisions. These insights should align with your initial objective.
10.
Communicate Results
Present your findings to stakeholders using clear, concise language. Use visualisations to support your narrative and help others understand your insights. Guidelines for the Report Your report consists of three sections: Introduction, Main Body, and Conclusion. The report should be around 1,200 words. The introduction begins by highlighting the primary purpose(s) of the analysis and concludes by explaining the report’s structure (i.e., subsequent sections).
The report’s main body summarises the key findings for each question, specifically addressing Edmond’s questions. Use proper headings in the report’s main body. Do not include any Excel output in the report, and avoid statistical jargon. Instead, use simple English to convey your findings and conclusions. The conclusion should highlight the key findings of the analyses and explain the main limitations (if any).
Learning Outcomes-
To solve complex problems, use quantitative reasoning skills.
As a data analyst, you must plan, monitor, and assess your own learning.
Deduce clear and unambiguous solutions in a format that is beneficial for decision-making, research, and public communication.
The first task is to report on how to plan and deliver the assessment task on time.
The second task is to analyse the given dataset and draw conclusions from the analysis. Finally, the third task is to convey the findings and conclusions in a written report to a person with very little or no knowledge of Business Analytics.
Questions related to the above-mentioned case study.
1. Do stores with an online sales channel have a better Sales record than stores without an online sales channel?
2. Is the proportion of Mall store managers with less than ten years of management experience smaller than the proportion of Strip store managers with less than ten years of management experience?
3. Does Gross Profit differ between the three levels of waste?
4. Does the proportion of country stores differ across NSW, Victoria, and Queensland?
5. We released additional funds to all stores to increase their weekly trading hours. Can you assess the effectiveness of the scheme?
6. I would like you to design and run an experiment to see the effect of the online channel and the level of waste on gross profits. The data for the experiment is in the “Experiment” worksheet.
This practical task aims to help you keep track of your progress with the assignment and submit it on time. To report how you plan your project and turn the plan into action, you must complete the tables provided in dot points as clearly as possible. Remember, effective planning, execution, and completing given tasks on time are essential self-management skills.
Read the case study and questions asked by Edmond carefully. Then spend some time reviewing the data to get a sense of the context. The analysis required for this assignment involves material covered in Module 1, with the corresponding tutorials being a helpful guide.
Start the analysis by translating the business problems into testable propositions. Before submitting your analysis, make sure it is logically organised and that any incorrect or unnecessary output has been removed. Marks will be penalised for poor presentation, disorganised or disorganized/incorrect results, or any unnecessary output.
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Data analysis and visualisation are essential tools in today's data-driven landscape. By effectively analysing data, you can transform raw information into actionable insights that guide decision-making.
Pairing analysis with visualisation not only enhances your understanding but also facilitates the communication of insights to others. Whether you're exploring business trends, scientific research, or societal data, mastering these skills empowers you to extract knowledge from data and make informed choices.
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