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Anblicks Interview Questions and Answers
21 Interview questions
Multicollinearity can distort regression coefficients; handling it is crucial for accurate model interpretation.
1. Remove Highly Correlated Features: Use correlation matrix to identify and drop one of the correlated features.
2. Principal Component Analysis (PCA): Transform correlated features into a set of uncorrelated components.
3. Regularization Techniques: Apply Lasso or Ridge regression to penalize large coeff...
The bias-variance tradeoff is a fundamental concept in machine learning that balances model complexity and prediction accuracy.
Bias refers to the error due to overly simplistic assumptions in the learning algorithm, leading to underfitting.
Variance refers to the error due to excessive complexity in the model, leading to overfitting.
A high-bias model (e.g., linear regression on non-linear data) may miss relevant re...
Analyzed customer data to identify trends, leading to a targeted marketing campaign that increased sales by 25%.
Conducted a thorough analysis of customer purchase patterns over the last year.
Identified a significant trend where younger demographics preferred eco-friendly products.
Presented findings to the marketing team, suggesting a targeted campaign focusing on sustainability.
The campaign resulted in a 25% incre...
I systematically clean and prepare large datasets by identifying issues, transforming data, and ensuring quality for analysis.
Identify missing values: Use techniques like imputation or removal based on the context. For example, replace missing age values with the median age.
Handle duplicates: Check for and remove duplicate records to avoid skewed analysis. For instance, if multiple entries exist for the same patie...
I prioritize security by implementing best practices, regular audits, and data encryption to protect sensitive information.
Implement data encryption both at rest and in transit to safeguard sensitive information.
Conduct regular security audits and vulnerability assessments to identify and mitigate risks.
Utilize access controls and authentication mechanisms to restrict data access to authorized users only.
Adopt sec...
I have extensive experience in data cleaning and preprocessing, ensuring data quality for analysis.
Identified and handled missing values using techniques like imputation or removal, e.g., replacing missing age values with the median.
Standardized data formats, such as converting date formats to a consistent 'YYYY-MM-DD' for easier analysis.
Removed duplicates to ensure data integrity, e.g., eliminating repeated pati...
Building a real-time data pipeline involves data ingestion, processing, storage, and visualization for timely insights.
Identify data sources: Use APIs, streaming data, or databases (e.g., Kafka for streaming data).
Data ingestion: Implement tools like Apache Kafka or AWS Kinesis for real-time data collection.
Data processing: Use stream processing frameworks like Apache Flink or Spark Streaming to transform data on-...
Designing a real-time chat application involves architecture, protocols, and user experience considerations.
Choose a suitable architecture: Client-server or peer-to-peer.
Use WebSockets for real-time communication, allowing full-duplex communication.
Implement a scalable backend using Node.js or similar frameworks.
Utilize a database like MongoDB for storing messages and user data.
Incorporate authentication mechanism...
I have extensive experience with AWS, Azure, and GCP, focusing on data engineering and cloud architecture.
Proficient in AWS services like S3 for storage, Redshift for data warehousing, and Lambda for serverless computing.
Utilized Azure Data Factory for ETL processes and Azure SQL Database for relational data storage.
Implemented GCP BigQuery for large-scale data analytics and used Cloud Storage for data lake soluti...
Designing a data pipeline involves defining requirements, selecting tools, and implementing ETL processes for data flow.
Define the data sources: Identify where the data will come from, e.g., databases, APIs, or flat files.
Choose the right tools: Select ETL tools like Apache Airflow, Talend, or custom scripts in Python.
Design the architecture: Create a flow diagram showing how data moves from source to destination.
...
Anblicks Interview Experiences
19 interviews found
Anonymous
I applied via Company Website and was interviewed in Oct 2024. There was 1 interview round.
(4 Questions)
- Q1. How do you do bulk report migration ?
- Ans.
Bulk report migration can be done using Power BI REST API or PowerShell scripts.
Use Power BI REST API to automate the migration process
Create PowerShell scripts to handle bulk report migration
Leverage tools like Power BI Management cmdlets for bulk operations
- Q2. How will you handle errors on pg
- Ans.
I will handle errors on pg by implementing error handling techniques and logging mechanisms.
Implement try-catch blocks to catch and handle errors
Use logging frameworks to log errors for troubleshooting
Display user-friendly error messages to guide users on how to resolve issues
- Q3. Difference between distinct and null, parallel period and same period last year
- Ans.
Distinct vs Null: unique values vs absence of value. Parallel period vs Same period last year: comparing current vs previous time periods.
Distinct values are unique values in a dataset, while null represents the absence of a value.
Parallel period compares data from the same time period in different years, while Same period last year compares data from the previous year.
For example, if we are comparing sales data for Ja...
- Q4. How do you refresh dimensions using api
- Ans.
You can refresh dimensions using Power BI REST API by sending a POST request to the appropriate endpoint.
Use the POST method to send a request to the refresh endpoint
Include the dataset ID and table name in the request body
Authenticate the request using an access token or API key
Skills evaluated in this interview
Selected
I appeared for an interview in Mar 2025, where I was asked the following questions.
- Q1. How do you approach cleaning and preparing data for analysis in large datasets?
- Ans.
I systematically clean and prepare large datasets by identifying issues, transforming data, and ensuring quality for analysis.
Identify missing values: Use techniques like imputation or removal based on the context. For example, replace missing age values with the median age.
Handle duplicates: Check for and remove duplicate records to avoid skewed analysis. For instance, if multiple entries exist for the same patient, k...
- Q2. Can you describe a time when your data insights led to a business decision?
- Ans.
Analyzed customer data to identify trends, leading to a targeted marketing campaign that increased sales by 25%.
Conducted a thorough analysis of customer purchase patterns over the last year.
Identified a significant trend where younger demographics preferred eco-friendly products.
Presented findings to the marketing team, suggesting a targeted campaign focusing on sustainability.
The campaign resulted in a 25% increase i...
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
(2 Questions)
- Q1. SQL Query to get Salary greater than manager salary
- Ans.
SQL query to retrieve salaries greater than manager salary
Use a SELECT statement to retrieve the salaries
Join the employee table with the manager table to compare salaries
Add a WHERE clause to filter salaries greater than manager's salary
- Q2. Count of alphabets in a string
- Ans.
Count the number of alphabets in a given string.
Iterate through each character in the string and check if it is an alphabet using isalpha() function.
Increment a counter for each alphabet found.
Return the final count of alphabets.
Example: Input - 'Hello123', Output - 5 (alphabets: H, e, l, l, o)
Interview Preparation Tips
- Python
- SQL
Skills evaluated in this interview
Maulik Shah
Selected
I appeared for an interview in Mar 2025, where I was asked the following questions.
- Q1. System design/Architecture related question
- Q2. SQL+Data modeling related questions
- Q3. Scenario based problem solving
Selected
I appeared for an interview in Mar 2025, where I was asked the following questions.
- Q1. What is the bias-variance tradeoff?
- Q2. How do you handle multicollinearity in a dataset?
- Ans.
Multicollinearity can distort regression coefficients; handling it is crucial for accurate model interpretation.
1. Remove Highly Correlated Features: Use correlation matrix to identify and drop one of the correlated features.
2. Principal Component Analysis (PCA): Transform correlated features into a set of uncorrelated components.
3. Regularization Techniques: Apply Lasso or Ridge regression to penalize large coefficien...
Selected
I applied via LinkedIn and was interviewed in Jul 2024. There were 2 interview rounds.
Coding questions and aptitude questions will be asked
(2 Questions)
- Q1. Explain spark architecture
- Ans.
Spark architecture is a distributed computing framework that consists of a driver program, cluster manager, and worker nodes.
Spark architecture includes a driver program that manages the execution of tasks and interacts with the cluster manager.
Cluster manager allocates resources and schedules tasks on worker nodes.
Worker nodes execute the tasks and return the results to the driver program.
Spark architecture supports f...
- Q2. Explain broadcast joun
- Ans.
Broadcast join is a method used in distributed computing to combine data from multiple sources by broadcasting smaller tables to all nodes.
Broadcast join is commonly used in distributed systems like Apache Spark to improve performance by reducing data shuffling.
It involves broadcasting the smaller table to all nodes in the cluster, so that each node can perform the join operation locally.
This method is efficient when o...
Skills evaluated in this interview
Selected
I applied via Naukri.com and was interviewed in Apr 2024. There were 2 interview rounds.
(2 Questions)
- Q1. Data pipelines architecture of your work
- Ans.
My data pipelines architecture involves a combination of batch and real-time processing using tools like Apache Spark and Kafka.
Utilize Apache Spark for batch processing of large datasets
Implement Kafka for real-time data streaming
Use Airflow for scheduling and monitoring pipeline tasks
- Q2. Python data structures
(1 Question)
- Q1. AWS skills & python
Skills evaluated in this interview
- Q1. How do you manage your time when faced with multiple project deadlines within a short timeframe?
- Q2. What has been your experience with using container technology?
- Q1. How is accuracy measured in document classification?
- Q2. What is the concept of Maximum Likelihood Estimation (MLE) in logistic regression?
Selected
I applied via Recruitment Consulltant and was interviewed in May 2023. There were 4 interview rounds.
(1 Question)
- Q1. Spark architecture and scenario based
(1 Question)
- Q1. SQL and programming on any of the language
(1 Question)
- Q1. Just a brief about there company and salary negosation
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The duration of Anblicks interview process can vary, but typically it takes about 2-4 weeks to complete.
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