Why advanced analytics uncovers hidden patterns in Tableau - Dashboard Impact

Dashboard Mode - Why advanced analytics uncovers hidden patterns

Business Question

How can advanced analytics help us find hidden patterns in sales data to improve business decisions?

Sample Data

Order ID	Region	Product Category	Sales	Profit	Order Date
1001	East	Furniture	500	50	2024-01-15
1002	West	Technology	1200	300	2024-01-20
1003	East	Office Supplies	300	30	2024-02-05
1004	South	Furniture	700	70	2024-02-10
1005	West	Technology	1500	400	2024-03-01
1006	East	Technology	800	120	2024-03-15
1007	South	Office Supplies	400	40	2024-03-20

Dashboard Components

• KPI Card: Total Sales
  Formula: SUM([Sales])
  Result: 5400
  Description: Shows total sales amount across all orders.
• KPI Card: Average Profit Margin
  Formula: AVG([Profit]/[Sales])
  Result: 0.15 (15%)
  Description: Average profit margin per sale.
• Bar Chart: Sales by Region
  Formula: SUM([Sales]) grouped by [Region]
  Data:
  • East: 1600
  • West: 2700
  • South: 1100
  
  Description: Visualizes sales distribution by region.
• Heat Map: Sales by Product Category and Month
  Formula: SUM([Sales]) grouped by [Product Category] and MONTH([Order Date])
  Data:
  • January: Furniture 500, Technology 1200, Office Supplies 0
  • February: Furniture 700, Technology 0, Office Supplies 300
  • March: Furniture 0, Technology 2300, Office Supplies 400
  
  Description: Highlights sales intensity by category and month to find seasonal patterns.
• Scatter Plot: Sales vs Profit
  Formula: Plot each order's [Sales] on X-axis and [Profit] on Y-axis
  Description: Shows relationship between sales and profit to detect outliers or trends.
• Cluster Analysis (Advanced Analytics)
  Formula: Tableau clustering on [Sales], [Profit], and [Region]
  Description: Groups similar orders to uncover hidden customer segments or sales patterns.

Dashboard Layout

+----------------------+----------------------+
| Total Sales (KPI)    | Average Profit Margin |
|       5400           |         15%           |
+----------------------+----------------------+
|      Sales by Region (Bar Chart)           |
|               [East, West, South]           |
+---------------------------------------------+
| Heat Map: Sales by Category and Month       |
| Furniture, Technology, Office Supplies      |
+---------------------------------------------+
| Scatter Plot: Sales vs Profit                |
| (Each dot is an order)                       |
+---------------------------------------------+
| Cluster Analysis: Customer Segments         |
| (Colored groups on scatter plot)             |
+---------------------------------------------+

Interactivity

Filters for Region and Product Category allow users to narrow down data. Selecting a region updates all charts and KPIs to show only that region's data. Clicking a cluster highlights related orders in the scatter plot. Date range filter adjusts heat map and other visuals to focus on specific months.

Self Check

If you add a filter for Region = East, which components update and how?

• Total Sales KPI updates to 1600.
• Average Profit Margin recalculates for East region orders.
• Sales by Region bar chart highlights East and dims others.
• Heat Map shows sales only for East region categories and months.
• Scatter Plot shows only East region orders.
• Cluster Analysis recalculates clusters based on East region data.

Key Result

Dashboard shows total sales, profit margin, sales distribution by region and category, and uncovers hidden customer segments using clustering.