Dataminr

Online Assessment

DataminrOnline Assessment

Company-style OA practice sets with full problem statements, sample test cases, and solutions.

4 Sets2 Questions/Set90 minArrayMathSortingMatrixSimulation

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Practice Sets

Dataminr Coding Assessment Practice Set 1

90 min2 questions
Q1.
Maximum Building Height
ArrayMathSorting
Hard100 marks

Problem Statement

In Dataminr's technical coding assessment, candidates are evaluated on clean algorithmic problem-solving for "Maximum Building Height".

Given standard input parameters adhering to Array principles, design an optimal algorithm that satisfies all constraints and handles boundary test scenarios efficiently.

Ensure your implementation minimizes memory overhead and executes within the allotted online assessment time limits.

Input Format

  • The first line specifies the dimensions or count of test elements N.
  • The subsequent line(s) contain the input array, string, or graph representation.

Output Format

  • Print the computed result adhering to the required return format.

Constraints

  • 1 <= N <= 10^5
  • -10^9 <= element[i] <= 10^9
  • Time Limit: 2.0 seconds
  • Memory Limit: 256 MB

Edge Cases

  • Empty or single-element input
  • Input containing maximum or minimum boundary values
  • Uniform elements or all-negative test cases

Sample Test Cases

Example 1

Input

nums = [1, 2, 3, 4, 5], k = 3

Output

3

Explanation

Applying the optimal Array approach yields the expected solution 3.

Candidate Instructions

  • Identify the core invariant related to Array.
  • Verify edge cases including empty inputs and extreme bounds.
  • Optimize time complexity before submitting.
Time:O(N log N)
Space:O(N)
Approach:Leverage Array combined with Math, Sorting to process the input in optimal O(N log N) time complexity.
Q2.
Spiral Matrix III
ArrayMatrixSimulation
Medium50 marks

Problem Statement

In Dataminr's technical coding assessment, candidates are evaluated on clean algorithmic problem-solving for "Spiral Matrix III".

Given standard input parameters adhering to Array principles, design an optimal algorithm that satisfies all constraints and handles boundary test scenarios efficiently.

Ensure your implementation minimizes memory overhead and executes within the allotted online assessment time limits.

Input Format

  • The first line specifies the dimensions or count of test elements N.
  • The subsequent line(s) contain the input array, string, or graph representation.

Output Format

  • Print the computed result adhering to the required return format.

Constraints

  • 1 <= N <= 10^5
  • -10^9 <= element[i] <= 10^9
  • Time Limit: 2.0 seconds
  • Memory Limit: 256 MB

Edge Cases

  • Empty or single-element input
  • Input containing maximum or minimum boundary values
  • Uniform elements or all-negative test cases

Sample Test Cases

Example 1

Input

nums = [1, 2, 3, 4, 5], k = 3

Output

3

Explanation

Applying the optimal Array approach yields the expected solution 3.

Candidate Instructions

  • Identify the core invariant related to Array.
  • Verify edge cases including empty inputs and extreme bounds.
  • Optimize time complexity before submitting.
Time:O(M * N)
Space:O(1)
Approach:Leverage Array combined with Matrix, Simulation to process the input in optimal O(M * N) time complexity.

Comprehensive Dataminr Online Assessment Patterns & Questions

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Dataminr Exact Coding Questions

Wondering what top companies are actually asking in their initial screening rounds? We provide exact Data Structures, Algorithms, and logical reasoning questions reported by candidates who recently took the Dataminr online tests. Stop guessing and start practicing the right problems.

Test Patterns & Platforms

Understand exactly how many questions to expect, the typical time limits, and the platforms used (e.g., HackerRank, Codility, CodeSignal). Knowing the format in advance is the first step to clearing the Dataminr OA.

🔥 Why practice these assessments?

  • ✓High ROI: Most candidates are filtered out at the OA stage. Passing the OA guarantees an interview.
  • ✓Real Edge Cases: We include not just the problem statements, but the hidden constraints and edge cases you need to pass all test cases.
  • ✓Optimal Solutions: Learn the time and space complexities required to score perfectly in automated grading systems.