Sky Industries Data Analyst Interview Questions and Answers

Cas study on books library data

Q1. Basics of spark Discussion on case study approach SQL question on windows function
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Q1. Why our firm ?
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Q2. Why in office , why not work from home ?
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Q1. Basic Questions
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Q2. Personal information
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Q1. What is supervised learning
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Supervised learning is a type of machine learning where the model is trained on labeled data to make predictions or decisions.
• Uses labeled training data to learn the mapping between input and output variables

• The model is trained on a dataset where the correct output is known

• Examples include classification and regression tasks
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Q2. What is overfitting
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Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor generalization on new, unseen data.

• Techniques to prevent overfitting include cross-validation, regularization, and early stopping.

• Example: A decision tree with too many branches that perfectly fits the training d
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Case study is shared two days before the interview process

Q1. General spark optimization techniques
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Spark optimization techniques improve performance and efficiency of data processing.
• Partitioning data to distribute workload evenly

• Caching frequently accessed data to avoid recomputation

• Using appropriate data formats like Parquet for efficient storage and retrieval

• Optimizing shuffle operations by tuning parameters like shuffle partitions

• Avoiding unnecessary data shuffling by using broadcast joins
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Q1. Optimizations in Databricks
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Optimizations in Databricks involve tuning cluster configurations, optimizing code, and utilizing caching.
• Tune cluster configurations to allocate resources efficiently

• Optimize code by using efficient algorithms and data structures

• Utilize caching to store intermediate results and avoid recomputation
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Q2. Where broadcast join is used and why
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Broadcast join is used when one of the tables is small enough to fit in memory of all the nodes in the cluster, reducing shuffle and improving performance.
• Broadcast join is used to optimize join operations by broadcasting the smaller table to all nodes in the cluster.

• It is beneficial when one of the tables is small enough to fit in memory of all nodes, reducing the need for shuffling data across the network.

• Broadcast j...read more
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Q1. Tell me about yourself, Why we hire you, your current profile at last company
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Process of purchase, roles and responsibilities of purchaser