1500 Questions | Data Practitioner Certification 2026

Data Preparation and Manipulation (27%): Connecting to various sources, filtering, sorting, and summarizing complex datasets.

Data Analysis and Modelling (19%): Applying DAX calculations, analysis functions, and industry-standard modelling practices.

Data Storytelling and Insights (23%): Translating raw data into actionable recommendations and compelling visual narratives.

B) One-to-many (1:*)

C) Many-to-one (*:1)

D) Many-to-many (:)

E) Single Directional

F) Bi-directional

Correct Answer: B

Explanation:

A (Incorrect): One-to-one would imply each product is only ever sold once, which is not typical for sales data,

C (Incorrect): While logically similar, the direction from Products to Sales is defined as One-to-many,

D (Incorrect): Many-to-many creates complexity and ambiguity that should be avoided in basic star schemas if a unique key exists,

E (Incorrect): This refers to cross-filter direction, not the cardinality of the relationship,

F (Incorrect): Bi-directional filtering is a property of the relationship, not the relationship type itself,

Question 2: While performing data preparation in Power Query, you notice that a 'Region' column has inconsistent casing (e.g., 'north', 'North', 'NORTH'), which transformation step is most efficient to ensure all values are identical for grouping?

B) Capitalize Each Word

C) Split Column by Delimiter

D) Format -> Uppercase

E) Group By

F) Remove Duplicates

Correct Answer: D

Explanation:

A (Incorrect): Replace Values would require multiple manual entries for every variation of the word,

B (Incorrect): While it works, Uppercase is often safer for data keys to avoid trailing space issues or specific regional casing rules,

C (Incorrect): Splitting by delimiter does not address the casing of the text within the column,

E (Incorrect): Grouping before standardizing would result in separate rows for 'north' and 'North',

F (Incorrect): This would delete data rows rather than fixing the formatting of existing data,

Question 3: You need to calculate the total sales for the previous year using DAX, which function is specifically designed to shift a set of dates back by exactly one year?

B) CALCULATE()

C) SAMEPERIODLASTYEAR()

D) FILTER()

E) ALL()

F) RELATED()

Correct Answer: C

Explanation:

A (Incorrect): SUM only aggregates values and cannot handle date shifting on its own,

B (Incorrect): CALCULATE is the engine used, but it requires a function like SAMEPERIODLASTYEAR to perform the specific time shift,

D (Incorrect): FILTER returns a table based on a condition but does not inherently understand "one year ago" without complex logic,

E (Incorrect): ALL removes filters; it does not shift them to a previous period,

F (Incorrect): RELATED is used to fetch values from another table in a relationship, not for time calculations,

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