Fractal Analytics Interview Questions, Process, and Tips

Q1. What are the types of transformation?
Ans. 
Types of transformations include filtering, sorting, aggregating, joining, and pivoting.
• Filtering: Selecting a subset of rows based on certain criteria.

• Sorting: Arranging rows in a specific order based on one or more columns.

• Aggregating: Combining multiple rows into a single result, such as summing or averaging values.

• Joining: Combining data from multiple sources based on a common key.

• Pivoting: Restructuring data from
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Q2. Why is spark a lazy execution
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Spark is lazy execution to optimize performance by delaying computation until necessary.
• Spark delays execution until an action is called to optimize performance.

• This allows Spark to optimize the execution plan and minimize unnecessary computations.

• Lazy evaluation helps in reducing unnecessary data shuffling and processing.

• Example: Transformations like map, filter, and reduce are not executed until an action like collec
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Q3. What is SCD and there types?
Ans. 
SCD stands for Slowly Changing Dimension. There are three types: Type 1, Type 2, and Type 3.
• SCD is used in data warehousing to track changes in dimension data over time.

• Type 1 SCD overwrites old data with new data, losing historical information.

• Type 2 SCD creates new records for each change, preserving historical data.

• Type 3 SCD keeps both old and new data in the same record, with separate columns for each version.
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Q4. What is linked service
Ans. 
A linked service is a connection to an external data source or destination in Azure Data Factory.
• Linked services define the connection information needed to connect to external data sources or destinations.

• They can be used in pipelines to read from or write to the linked data source.

• Examples of linked services include Azure Blob Storage, Azure SQL Database, and Salesforce.

• Linked services can store connection strings, a...read more
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Q5. What is dataset
Ans. 
A dataset is a collection of data that is organized in a structured format for easy access and analysis.
• A dataset can consist of tables, files, or other types of data sources.

• It is used for storing and managing data for analysis and reporting purposes.

• Examples of datasets include customer information, sales data, and sensor readings.

• Datasets can be structured, semi-structured, or unstructured depending on the type of d
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Q1. Main pillars of Project management
Ans. 
Main pillars of Project management include scope, time, cost, quality, communication, risk, and procurement.
• Scope management involves defining and controlling what is included in the project.

• Time management focuses on creating and maintaining a project schedule.

• Cost management involves budgeting and controlling project costs.

• Quality management ensures that the project meets the required standards.

• Communication manageme...read more
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Q2. Project Management Scenario based questions you can clear if you have hands-on experience
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Q1. Project Management+Technical discussion
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Q1. Informal HR discussion salary expectations,asked to submit documents for verification
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Q1. Project Management experience and challenges faced for a project
Ans. 
I have 5 years of project management experience, including leading a team to successfully complete a software development project.
• Managed cross-functional teams to ensure project milestones were met

• Identified and resolved conflicts within the team to maintain productivity

• Implemented Agile methodologies to improve project efficiency

• Communicated project updates to stakeholders regularly

• Managed project budget and resource
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Q2. More technical describe ado.net,boxing unboxing
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Basic Pyspark/python question with some mcqs

Q1. Project overview
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Q2. Pyspark, python , sql related questions.
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Q1. Basic technical question on spark and one python Dasa question and one sql
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Q2. Sql + python + spark + Adf + Databricks
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Q1. Why you want to join even though you have offers from good mnc
Ans. 
I am passionate about data engineering and believe this company offers unique opportunities for growth and learning.
• Exciting projects and challenges at this company

• Opportunities for growth and learning in data engineering

• Alignment with company values and culture

• Potential for career advancement and development

• Interest in the industry or specific technologies used by the company
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Q2. Salary expectations and work culture
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Q1. What kind of data modelling you worked with GenAI project?
Ans. 
I have experience working with data modelling in the GenAI project to optimize algorithms and improve performance.
• Utilized various data modelling techniques to analyze and interpret data

• Developed predictive models to enhance decision-making processes

• Collaborated with data scientists to refine and validate models

• Implemented machine learning algorithms to improve accuracy and efficiency
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Q2. What was the challenge in end-to-end product delivery and implementation of solution roadmap?
Ans. 
The challenge in end-to-end product delivery and implementation of solution roadmap involved coordinating multiple teams, managing dependencies, and ensuring alignment with business goals.
• Coordinating cross-functional teams to ensure timely delivery of each component of the product

• Managing dependencies between different teams and components to avoid delays

• Ensuring alignment of the solution roadmap with the overall busi...read more
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Q1. Why Informatica cloud is better than Azure Cloud solution?
Ans. 
Informatica Cloud offers more comprehensive data integration capabilities compared to Azure Cloud.
• Informatica Cloud provides a wide range of data integration tools and services for various data sources and formats.

• Informatica Cloud offers advanced data quality and data governance features that are not available in Azure Cloud.

• Informatica Cloud has a strong focus on data security and compliance, with built-in encryption...read more
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Q2. Why do you prefer Azure cloud solution as recommendations for Data Engineering pipelines? Explain data pipelines scenario you managed in the project?
Ans. 
I prefer Azure cloud solution for Data Engineering pipelines due to its scalability, reliability, and integration with other Microsoft services.
• Azure provides a wide range of tools and services specifically designed for data engineering tasks, such as Azure Data Factory, Azure Databricks, and Azure HDInsight.

• Azure offers seamless integration with other Microsoft services like Power BI, SQL Server, and Azure Machine Lea...read more
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Q1. How do you manage client obligations?
Ans. 
I manage client obligations by setting clear expectations, communicating regularly, and prioritizing tasks based on deadlines and importance.
• Set clear expectations with clients regarding deliverables and timelines

• Communicate regularly to provide updates on progress and address any concerns

• Prioritize tasks based on deadlines and importance to ensure all client obligations are met

• Proactively identify potential issues and...read more
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Q2. How do you manange conflicts in the project?
Ans. 
I manage conflicts in the project by promoting open communication, addressing issues promptly, seeking compromise, and involving stakeholders in resolution.
• Promote open communication among team members to address conflicts early on

• Address issues promptly and directly to prevent escalation

• Seek compromise and find win-win solutions to resolve conflicts

• Involve stakeholders in conflict resolution to ensure all perspectives
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