Tableau: A BI Tool

While coming back from work a few days ago, my parents from Bangladesh called, and I was on the bus at that moment. They were tense and constantly warning me to be safe because of Covid — 19. I tried to solace them. However, it further provoked me to dig deeper into this topic to get a clear picture of the situation here in Australia. This analysis will help me to reassure my parents with an informed decision.
I opted for Tableau Desktop and Microsoft Power B.I. as my visualization tools for the blogs. Having prior experience in visualization projects helped me choose these tools for the blogs. In addition to that, these are powerful data visualization and analysis tools that allow users to create dashboards, draw insights, and tell a story with data. It effectively reduces the complexity of the raw data. Datasets can be large and challenging to comprehend. These tools can define problems and create individualized dashboards and stories to grasp the gist of a situation quickly.

For this post, I am using Tableau Desktop as the reviewing tool.

Dataset Selection: I acquired the data from Our world in data. I wanted to uncover some facts concerning the Covid-19 cases in Australia to support my statement. The website contains Covid-19 data from different points of view. I have taken two datasets regarding death and confirmed cases and merged them to find the answers I have been pursuing. Each data set has many attributes (>30). However, I narrowed it down to a few and merged afterwards to finalize the features I needed for the analysis.

The reasons for choosing data from Our World in Data are:

1. Data is collected from specialized institutes, research articles, international institutions, or statistical agencies.
2. Availability of a large variety of data.
3. Cited in numbers of scientific and health journals.
4. Provider of reliable source.
5. Data is structured and detailed.
6. The data time frame is significant.

Dataset Cleaning: While merging the data, I deleted the attributes which were not helpful for the analysis. I also needed a few more columns derived from the existing markers. Tableau has a feature named “Calculated Fields.” I added the columns with a few simple calculations using that.

Figure 1: Incorporating Calculated Fields in Tableau.

Also, it helps filter out the null values smoothly. In addition, I also dragged out a few records which were misplaced(mistakes during data entry).

Analysis: As I wanted to figure out the current circumstances of Covid-19 in Australia, I wanted to compare the total death and total cases in Oceania. On the other hand, I tried to visualize the impact of vaccination and booster doses in terms of confirmed new cases.

Figure 2: Vaccine Rate vs New Cases In Australia.

Firstly, This picture depicts the vaccination rate vs. new cases. The cases were significantly within control until January. Then again, it started to come down within a few days, with having almost 80% of the population fully vaccinated. The trendline shows vaccination rate is pretty higher than the cases.

Figure 3: Booster Dose Percenateg vs New Cases in Australia.

Secondly, Here I tried to display the impact of booster doses for new cases. After confirming booster to the 20% of the entire population, the recent confirms started to slow down.

Figure 4: Total Confirmed Case of Covid Considering the Continents (Oceania Having Significantly lower Count)

Figure 5: Death Counts in Terms of Continents (Oceania Having the Lowest Count)

Finally, these two graphs exhibit the number of total cases and deaths; both were remarkably lower in Oceania throughout the entire covid period.

Furthermore, the dashboard function allowed me to visualize the graphs altogether.

Figure 6: The Dashboard of All the Previous Reports.

Why Tableau Desktop is attractive: As a B.I. Tool, Tableau Desktop offers a wide range of functionality to obtain information. In this analysis, the functionalities I came across are:

1. Filtering
2. Dual Axis Graph.
3. Trendline.
4. Calculated Fields.
5. Dashboard.
6. Story
7. Measures and Dimensions.

It simply puts together all the functionalities that a person might need throughout the analysis. These all come preinstalled with Tableau.

Opportunities and Challenges: Tableau provides many opportunities that persuade people to use this tool.

1. Doesn’t require coding. Everyone can use it regardless of background.
2. Allows all sorts of data. I.E., Structure, Semi-Structured, Unstructured.
3. Provides visual cues for intuitiveness.
4. Monitor performance.
5. Analyzing, visualizing data, and presenting insights.
6. Competitive analysis.
7. Quick and robust prototyping.
8. Training videos suggestions.
9. Uploading and publishing visualizations.
10. Creating measure values from dimension data.
11. Grouping.
12. “Show me” option for the graph.

However, there are also some scopes to make the tool even better. Such as

1. Reports to be refreshed automatically.
2. Having a comprehensive platform for mobile.
3. Resolving the accidental deterioration of performance.
4. Integrating more data cleaning options.
5. Reduction of price.

To sum up, Tableau Desktop is a fantastic tool for data analysis because of its user-friendliness and simplicity. Being intuitive in nature, this tool helped me choose the colours and graphs. Tableau is easy to navigate and doesn’t require much prior knowledge to get started. It is super easy to learn with lots of resources on the internet, such as DataCamp (Links to an external site.), Youtube (Links to an external site.)

Thanks for bearing with me.

References:

Our World in Data, 2022, Coronavirus (COVID-19) Deaths, Online, viewed 16 March 2022, <https://ourworldindata.org/covid-deaths>.

Our World in Data, 2022, Coronavirus (COVID-19) Vaccinations, Online, viewed 16 March 2022, <https://ourworldindata.org/covid-vaccinations/>.