Skip to main content

Interview Questions

database, and Blending when combining data from different sources like a SQL database and an Excel file."

Q6: "What are Table Calculations? How are they different from Calculated Fields?"​

Answer: "Calculated Fields are computed at the data source level — they're like adding a new column to the table. Table Calculations are computed after the query result is returned — they operate on what's visible in the view. For example, Running Total and Percent of Total are table calculations because they depend on the arrangement of marks in the view."

Q7: "What are sets in Tableau?"​

Answer: "Sets are custom fields that define a subset of data based on conditions. Fixed Sets are manually selected; Computed Sets update dynamically. For example, I'd create a computed set for 'Top 20% Customers by Revenue' — it auto-updates as data changes. Sets are powerful for IN/OUT comparisons."

Q8: "How would you design a dashboard for a non-technical executive?"​

Answer: "I'd follow three principles: (1) Lead with KPI cards — show 3-4 big numbers at the top. (2) Use simple charts — bar, line, and maps — no scatter plots or histograms. (3) Add interactive filters so they can explore without overwhelming them. I'd also use clear titles, consistent colors, and tooltips that explain what they're seeing."

Q9: "Explain the difference between Live and Extract connections."​

Answer: "Live queries the database in real-time — always fresh but slower. Extract creates a local snapshot in a .hyper file — much faster but only as fresh as the last refresh. I'd use Extract for 90% of cases with scheduled refreshes. Live only when real-time data is absolutely critical, like for a fraud monitoring dashboard."

Q10: "What is a parameter and how would you use it?"​

Answer: "A parameter is a user-controllable dynamic value. I'd use parameters for: (1) Dynamic Top N — let users choose top 5, 10, or 20. (2) Metric switching — toggle between Revenue, Profit, Quantity on the same chart. (3) Date range selection. Parameters make dashboards interactive and reduce the number of pages needed."

Q11: "Explain addressing and partitioning in table calculations."​

Answer: "Partitioning defines the scope — which groups the calculation restarts for. Addressing defines the direction — which dimension the calculation moves along. For example, in a Percent of Total by Region and Month — if Month is addressing and Region is partitioning, the percentage is calculated across months within each region."

Q12: "How do you handle null values in Tableau?"​

Answer: "Three approaches: (1) Use ZN() function — converts NULL to zero for calculations. (2) Use IFNULL([Field], replacement_value) for custom defaults. (3) Use Data Source filters to exclude nulls before loading. The choice depends on context — for SUM, ZN is safe; for AVG, including zero for null could skew results."

11. Practice Scenarios​

Scenario 1: Sales Dashboard Design​

Task: A client wants a dashboard showing regional sales performance for the last 12 months.

Solution Approach:

Row 1: KPI Cards
  → Total Revenue  |  YoY Growth %  |  # Orders  |  Avg Order Value

Row 2: Main Charts
  → Line Chart: Monthly Revenue Trend (with last year comparison)
  → Bar Chart: Revenue by Region (sorted descending)

Row 3: Detail
  → Heatmap: Region × Month (intensity = revenue)
  → Table: Top 10 Products by Revenue

Interactivity:
  → Region filter (clicking bar chart filters all others)
  → Date range slicer at the top

Scenario 2: Context Filter Problem​

Task: "Show me the Top 3 products in the Technology category."

Without Context Filter:

Step 1: Top 3 from ALL categories → Maybe: Desk, Chair, Laptop
Step 2: Filter Technology → Only Laptop survives → 1 result ❌

With Context Filter on Category = 'Technology':

Step 1: Filter to Technology → Laptop, Monitor, Mouse, Keyboard...
Step 2: Top 3 from Technology → Laptop, Monitor, Mouse ✅

Scenario 3: LOD for Customer Analysis​

Task: Create a calculated field showing each customer's first purchase date, regardless of view granularity.

Calculated Field: Customer First Purchase
{FIXED [Customer_ID] : MIN([Order_Date])}

Use Case: Compare each order date to the customer's first 
purchase date to calculate "days since first purchase" — 
useful for cohort analysis and customer lifecycle tracking.