Informatica Interview Questions and Answers

Q1. Don't know what to say
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Q2. Still don't know just writing here to unlock credit
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Q3. I don't have anything to share
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Q1. My Profile summary for 5 to 10 mins
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Q2. Program to all paths in a binary matrix n*n
Ans. 
Program to find all paths in a binary matrix n*n
• Use backtracking algorithm to explore all possible paths

• Start from the top-left corner and explore all possible paths

• Mark visited cells to avoid revisiting them

• Terminate the search when all possible paths have been explored

• Return all the valid paths found
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Q3. Java collections like Set , Map, their performance
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Q4. Mango DB related questions, shading, partitioning
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Q5. Kafka architecture and why don't we persist data in permanently.
Ans. 
Kafka is a distributed streaming platform that allows for real-time data processing. Data is not persisted permanently to optimize performance.
• Kafka is designed for real-time data processing and streaming, not for long-term storage.

• Data is stored in Kafka for a configurable amount of time, after which it is automatically deleted.

• Persisting data permanently would require additional storage and slow down performance.

• Kafk...read more
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Q6. Difference between mango DB and Cassandra
Ans. 
MongoDB is a document-oriented database while Cassandra is a column-family database.
• MongoDB is better suited for complex queries and data modeling.

• Cassandra is better for write-heavy workloads and high availability.

• MongoDB has a flexible schema while Cassandra has a fixed schema.

• MongoDB supports ACID transactions while Cassandra supports eventual consistency.

• MongoDB is more popular for web applications while Cassandra
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How to sort a very large array of numbers ?
hint: merge sort

Q1. Find the longest increasing decreasing subsequence in an array. hint- DP question
Ans. 
Use dynamic programming to find the longest increasing decreasing subsequence in an array.
• Use dynamic programming to keep track of the length of the longest increasing subsequence ending at each index.

• Similarly, keep track of the length of the longest decreasing subsequence starting at each index.

• Combine the two to find the longest increasing decreasing subsequence.
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