Query performance tuning in Tableau - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an extract for faster query performance.

Tableau

CREATE EXTRACT [1]

Drag options to blanks, or click blank then click option'

ADATA

BVIEW

CDATABASE

DTABLE

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'DATA' or 'DATABASE' instead of 'TABLE' causes syntax errors.

Trying to extract a VIEW instead of a TABLE may not improve performance as expected.

In Tableau, creating an extract of the TABLE improves query speed by storing data locally.

2fill in blank

medium

Complete the Tableau calculation to optimize query by filtering only recent data.

Tableau

IF [Order Date] >= DATEADD('year', -1, TODAY()) THEN [1] ELSE NULL END

Drag options to blanks, or click blank then click option'

A[Sales]

B[Profit]

C[Quantity]

D[Discount]

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing non-revenue fields like Discount or Quantity may not optimize the main query.

Leaving the blank empty causes calculation errors.

Filtering [Sales] for the last year reduces data scanned, improving query speed.

3fill in blank

hard

Fix the error in the Tableau LOD expression to calculate average sales per customer.

Tableau

{ FIXED [Customer ID] : AVG([1]) }

Drag options to blanks, or click blank then click option'

A[Profit]

B[Quantity]

C[Sales]

D[Discount]

Attempts:

3 left

💡 Hint

Common Mistakes

Using Profit or Quantity changes the meaning of the calculation.

Using Discount does not represent sales amount.

The correct measure to average per customer for sales analysis is [Sales].

4fill in blank

hard

Fill both blanks to optimize query by limiting data and aggregating sales.

Tableau

SUM(IF [Region] = [1] THEN [Sales] ELSE 0 END) / COUNTD([2])

Drag options to blanks, or click blank then click option'

A'West'

B[Customer ID]

C'East'

D[Order ID]

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong region name causes incorrect filtering.

Counting Order ID instead of Customer ID changes the aggregation meaning.

Filtering sales for the 'West' region and counting distinct [Customer ID] optimizes aggregation.

5fill in blank

hard

Fill all three blanks to create a calculated field that improves query speed by filtering and aggregating profit.

Tableau

SUM(IF [Category] = [1] AND [Order Date] > [2] THEN [3] ELSE 0 END)

Drag options to blanks, or click blank then click option'

A'Furniture'

BDATE('2023-01-01')

C[Profit]

D'Technology'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong category or date reduces filter effectiveness.

Summing Sales instead of Profit changes the metric focus.

Filtering for 'Furniture' category and orders after 2023-01-01, then summing [Profit] helps focus queries and improve speed.