Today, we are going to do some basic data analysis on Tableau. We are exploring how visualizations could be mapped out using the Lazada data-set, and subsequently do some analysis on it. The Lazada data shown below is the listing of all products on the website.
Next, what we would like to do is to add the Lazada database as a new connection in Tableau. In this case, you can choose a live connection if you wish to update Tableau whenever the database is updated, or an extract if you wish to just extract the data once.
Now that we have our data in Tableau, let us map out the data based on the sum of the price of products group by country, category level 1, 2 and 3.
Display of data in text
Next, we are going to create a new calculated field, label it as ‘Number of Listing’, and add it to the chart to find out how many listings are there for each item in level 3 category.
Adding new calculated field ‘Number of Listing’
Adding number of listing in level 3 category
We can now select treemaps on the right under the ‘Show Me’ tab and populate the data in a graphical image.
Level 3 Category Treemaps
From the diagram above we have a quick visualization on which type of items have the highest weightage based on the number of listing that category has. In the diagram above, we can see the top 5 listings for level 3 category:
- Phone Cases – 4,084
- Women Clothing – 1,626
- Women Jewellery – 1,506
- Miscellaneous Electronic Accessories – 1,195
- Men Watches – 1,070
For the next chart, we are going to focus on the level 2 category instead, by removing the level 3 category details.
Level 2 Category Treemaps
Once again, we can map out the top 5 listing for level 2 category:
- Mobiles and Tablet Accessories – 6,903
- Women Fashion – 3,944
- Watches – 2,063
- Jewellery – 1,708
- Men Fashion – 1,609
Next, we are going to focus on the level 1 category, similarly by removing the level 2 category details.
Level 1 Category Treemaps
Once again, we can map out the top 5 listing for level 1 category:
- Mobiles and Tablets – 7,277
- Home and Living – 6,048
- Fashion – 5,729
- Watches, Sunglasses, and Jewellery – 4,216
- Health and Beauty – 4,040
What we have done is some basic analysis on the Lazada data set and come up with a visualization on the number of listings based on the product category. With treemaps, we can have a quick glance at the top 5 listings on each category and see which markets are in high demand and are perhaps oversaturated.
In the next article, we will discuss more on how to use dashboards, filters, and conditions in Tableau using the same dataset.