Matrix Questions at Zomato: What to Expect

Matrix questions appear in roughly 14% of Zomato's technical interviews (4 out of 29 total problems). For a company managing real-time data on restaurants, delivery logistics, and geospatial mapping, matrices are a natural structure for representing grids, maps, and tabular data. Success here demonstrates your ability to handle multi-dimensional data traversal and transformation—core skills for optimizing delivery routes, analyzing zone-based data, or processing image grids for menu scans.

What to Expect — Types of Problems

Zomato's matrix problems typically focus on practical applications rather than abstract puzzles. Expect these categories:

• Grid Traversal & Pathfinding: Problems involving moving through a grid (representing a map or delivery area) to find a path, often with constraints. Examples include counting paths from a delivery hub to a location, or navigating around obstacles ("closed restaurants").
• Matrix Transformation: Modifying a matrix in-place, such as rotating an image of a food item or menu, or updating values based on neighboring cells. These test your understanding of index manipulation and space complexity.
• Search in Sorted Matrix: Searching for a target (like a specific restaurant ID or price point) in a matrix where rows and columns are sorted—a common pattern for efficient data lookup.
• Connected Components: Using Depth-First Search (DFS) or Breadth-First Search (BFS) on a matrix to find connected regions, akin to identifying contiguous delivery zones or clusters of restaurants.

The emphasis is on clean, efficient code that handles edge cases, as real-world data is often imperfect.

How to Prepare — Study Tips with One Code Example

Master a few fundamental patterns rather than memorizing problems. Practice writing bug-free traversal code and performing in-place operations. Always clarify problem constraints (e.g., can the matrix be modified?) and walk through edge cases like empty matrices or 1x1 grids.

A critical pattern is Depth-First Search (DFS) on a matrix for problems involving connected cells, such as "counting islands" of deliverable areas. The core idea is to mark visited cells to avoid re-processing.

def dfs(matrix, i, j, visited):
    # Check boundaries and if cell is valid/not visited
    if (i < 0 or i >= len(matrix) or
        j < 0 or j >= len(matrix[0]) or
        matrix[i][j] == 0 or visited[i][j]):
        return
    visited[i][j] = True
    # Explore 4-directionally
    dfs(matrix, i+1, j, visited)
    dfs(matrix, i-1, j, visited)
    dfs(matrix, i, j+1, visited)
    dfs(matrix, i, j-1, visited)

def count_areas(matrix):
    if not matrix:
        return 0
    rows, cols = len(matrix), len(matrix[0])
    visited = [[False] * cols for _ in range(rows)]
    count = 0
    for i in range(rows):
        for j in range(cols):
            if matrix[i][j] == 1 and not visited[i][j]:
                dfs(matrix, i, j, visited)
                count += 1
    return count

Recommended Practice Order

Build competency in this sequence:

1. Basic Traversal: Start with problems that require simple row/column iteration.
2. In-place Operations: Practice rotating and transposing matrices without extra space.
3. Pathfinding: Tackle BFS/DFS for shortest path or path count problems.
4. Search in Sorted Matrix: Implement efficient binary-search inspired approaches.
5. Complex DFS/BFS: Solve connected components and more advanced flood-fill variations.

Focus on writing correct, compilable code on your first try during practice to simulate interview conditions.

Practice Matrix at Zomato