"You should be able to easily identify this as a Measure Success question. These kinds of questions are used to test your analytical skills, as well as your ability to track project progress post-launch.
Recall the strategy for tackling them methodically and thoroughly:
Ask clarifying questions
State the goal of the feature / product
Behavior Mapping / UX Flow Mapping
Provide criteria to prioritize metrics
Prioritize metrics
Summarize
Let's begin!
"
Exponent - "You should be able to easily identify this as a Measure Success question. These kinds of questions are used to test your analytical skills, as well as your ability to track project progress post-launch.
Recall the strategy for tackling them methodically and thoroughly:
Ask clarifying questions
State the goal of the feature / product
Behavior Mapping / UX Flow Mapping
Provide criteria to prioritize metrics
Prioritize metrics
Summarize
Let's begin!
"See full answer
"SQL databases are relational, NoSQL databases are non-relational. SQL databases use structured query language and have a predefined schema. NoSQL databases have dynamic schemas for unstructured data. SQL databases are vertically scalable, while NoSQL databases are horizontally scalable."
Ali H. - "SQL databases are relational, NoSQL databases are non-relational. SQL databases use structured query language and have a predefined schema. NoSQL databases have dynamic schemas for unstructured data. SQL databases are vertically scalable, while NoSQL databases are horizontally scalable."See full answer
"Imagine you have a friend from France that speaks French, and you only speak English. You and your friend want to play a talking game. So, for your friend to understand you and for you to understand what your friend is saying you would need an API between the two of you. The api has its own language called api language. You and your friend will both get a small book that tells you how to speak api language. The api in between you and your friend would allow both of you to speak API language to"
Musonda C. - "Imagine you have a friend from France that speaks French, and you only speak English. You and your friend want to play a talking game. So, for your friend to understand you and for you to understand what your friend is saying you would need an API between the two of you. The api has its own language called api language. You and your friend will both get a small book that tells you how to speak api language. The api in between you and your friend would allow both of you to speak API language to"See full answer
"Minimum viable product is a product with a minimum set of features that are sufficient to gather information if customers are going to use it or are sufficient to answer the questions for the problems that are we are specifically trying to solve. In order to prioritize features it is critical to consider following points.
What is the problem we are trying to solve?
Understand the context.
Identify the features that you need to solve the problem while ensuring that features are in sync with"
Abhilash K. - "Minimum viable product is a product with a minimum set of features that are sufficient to gather information if customers are going to use it or are sufficient to answer the questions for the problems that are we are specifically trying to solve. In order to prioritize features it is critical to consider following points.
What is the problem we are trying to solve?
Understand the context.
Identify the features that you need to solve the problem while ensuring that features are in sync with"See full answer
"A red-black tree is a self-balancing binary search tree. The motivation for this is that the benefits of O(logN) search, insertion, and deletion that a binary tree provides us will disappear if we let the tree get too "imbalanced" (e.g. there are too many nodes on one side of the tree or some branches have a depth that is way out of proportion to the average branch depth). This imbalance will occur if we don't adjust the tree after inserting or deleting nodes, hence our need for self-balancing c"
Alex M. - "A red-black tree is a self-balancing binary search tree. The motivation for this is that the benefits of O(logN) search, insertion, and deletion that a binary tree provides us will disappear if we let the tree get too "imbalanced" (e.g. there are too many nodes on one side of the tree or some branches have a depth that is way out of proportion to the average branch depth). This imbalance will occur if we don't adjust the tree after inserting or deleting nodes, hence our need for self-balancing c"See full answer
"This could be done using two-pointer approach assuming array is sorted: left and right pointers. We need track two sums (left and right) as we move pointers. For moving pointers we will move left to right by 1 (increment) when right sum is greater. We will move right pointer to left by 1 (decrement) when left sum is greater. at some point we will either get the sum same and that's when we exit from the loop. 0-left will be one array and right-(n-1) will be another array.
We are not going to mo"
Bhaskar B. - "This could be done using two-pointer approach assuming array is sorted: left and right pointers. We need track two sums (left and right) as we move pointers. For moving pointers we will move left to right by 1 (increment) when right sum is greater. We will move right pointer to left by 1 (decrement) when left sum is greater. at some point we will either get the sum same and that's when we exit from the loop. 0-left will be one array and right-(n-1) will be another array.
We are not going to mo"See full answer
"
O(n) time, O(1) space
from typing import List
def maxsubarraysum(nums: List[int]) -> int:
if len(nums) == 0:
return 0
maxsum = currsum = nums[0]
for i in range(1, len(nums)):
currsum = max(currsum + nums[i], nums[i])
maxsum = max(currsum, max_sum)
return max_sum
debug your code below
print(maxsubarraysum([-1, 2, -3, 4]))
`"
Rick E. - "
O(n) time, O(1) space
from typing import List
def maxsubarraysum(nums: List[int]) -> int:
if len(nums) == 0:
return 0
maxsum = currsum = nums[0]
for i in range(1, len(nums)):
currsum = max(currsum + nums[i], nums[i])
maxsum = max(currsum, max_sum)
return max_sum
debug your code below
print(maxsubarraysum([-1, 2, -3, 4]))
`"See full answer
"The first clarification question which I will ask that if there is any goal. Specific objective? Is there any key result here targeting for? Let's assume the answer is no. Then will look for creating the overall vision of apple music.
I will ask to understand if there is any geographic area considered for this improvement and if there is any customer segment this improvement is targetted for. So we do not have such parameters.
Now let's talk to the customers and see what we hear from them.
"
Indranil G. - "The first clarification question which I will ask that if there is any goal. Specific objective? Is there any key result here targeting for? Let's assume the answer is no. Then will look for creating the overall vision of apple music.
I will ask to understand if there is any geographic area considered for this improvement and if there is any customer segment this improvement is targetted for. So we do not have such parameters.
Now let's talk to the customers and see what we hear from them.
"See full answer