Preparing for data analytics interviews can be a daunting task, especially when aiming for a coveted position at Persistent Systems. To help you navigate this journey with confidence, we’ve curated a comprehensive guide filled with key questions and expert answers tailored to Persistent Systems’ interview process. From technical inquiries to problem-solving scenarios and domain knowledge assessments, this blog equips you with the insights needed to ace your interview and secure your dream role. Dive in and discover valuable tips to stand out in your data analytics journey at Persistent Systems!
Table of Contents
Technical Questions
Question: What is Normalization in SQL?
Answer: Normalization in SQL refers to the process of organizing a database schema to reduce redundancy and dependency by dividing large tables into smaller, related tables and defining relationships between them. The primary goals of normalization are to minimize data redundancy, ensure data integrity, and improve database efficiency. There are several normal forms (1NF, 2NF, 3NF, BCNF, 4NF, 5NF) that define progressively stricter rules for organizing data in a relational database.
Here’s a brief overview of some of the normal forms:
- First Normal Form (1NF): This form requires that each table have a primary key and that each column contains atomic (indivisible) values. It eliminates repeating groups within a table.
- Second Normal Form (2NF): A table is in 2NF if it is in 1NF and every non-key attribute is fully functionally dependent on the primary key. This eliminates partial dependencies.
- Third Normal Form (3NF): A table is in 3NF if it is in 2NF and all attributes are functionally dependent only on the primary key, and not transitively on another attribute.
- Boyce-Codd Normal Form (BCNF): A stronger version of 3NF, where every determinant is a candidate key.
- Fourth Normal Form (4NF): A table is in 4NF if it is in BCNF and has no multi-valued dependencies.
- Fifth Normal Form (5NF): A table is in 5NF if it is in 4NF and all join dependencies are implied by the candidate keys.
Question: Types of Joins.
Answer: SQL offers several types of joins for combining rows from multiple tables based on related columns.
- INNER JOIN returns only the rows with matching values in both tables.
- LEFT JOIN returns all rows from the left table and matched rows from the right table, with NULL values for non-matching rows.
- RIGHT JOIN returns all rows from the right table and matched rows from the left table, with NULL values for non-matching rows.
- FULL JOIN returns all rows from both tables, combining matching rows and filling non-matching rows with NULL values.
- CROSS JOIN produces the Cartesian product of the two tables, combining every row of the first table with every row of the second table.
Each type of join serves specific purposes in data retrieval and manipulation tasks within SQL databases.
Question: What are Rank functions?
Answer: Rank functions in SQL are used to assign a rank to each row in a result set based on specified criteria. These functions allow you to assign a unique rank to each row or group of rows, often ordered by a particular column or set of columns. The most common rank functions are:
- RANK(): Assigns a unique rank to each row within the partition of a result set. Rows with the same values receive the same rank, and the next rank is assigned incrementally.
- DENSE_RANK(): Similar to RANK(), but it assigns consecutive ranks to rows without any gaps. If multiple rows have the same values, they receive the same rank, and the subsequent rank is incremented accordingly.
- ROW_NUMBER(): Assigns a unique sequential integer to each row in the result set, starting from 1. Unlike RANK() and DENSE_RANK(), ROW_NUMBER() does not account for ties; each row receives a distinct number.
Question: What is the difference between NoSQL and SQL Databases?
Answer: NoSQL (Not Only SQL) and SQL (Structured Query Language) databases are two different types of database management systems (DBMS) with distinct characteristics and use cases. Here are the key differences between them:
- SQL databases follow a structured data model with tables, rows, and columns, adhering to ACID properties, while NoSQL databases support various data models and are often schema-less.
- SQL databases scale vertically by adding resources to a single server, whereas NoSQL databases scale horizontally by adding nodes to a distributed cluster.
- SQL databases use the standardized SQL query language, while NoSQL databases may have their own query languages or support SQL-like syntax.
- SQL databases prioritize strong consistency and transactional integrity, whereas NoSQL databases often prioritize scalability and performance, sometimes at the expense of strong consistency.
- SQL databases are commonly used in traditional applications with structured data requirements, while NoSQL databases are favored for large-scale data storage and high-speed data ingestion applications.
The choice between SQL and NoSQL databases depends on factors like data structure, scalability needs, performance requirements, and application use cases.
Question: What is Cloud Computing?
Answer: Cloud computing refers to the delivery of computing services over the internet, providing access to resources such as servers, storage, databases, networking, software, and more on a pay-as-you-go basis. Users can access these resources remotely through web browsers or APIs without needing to invest in and maintain physical infrastructure. Cloud computing offers scalability, flexibility, and cost-effectiveness, allowing organizations to rapidly deploy and scale applications, store and analyze large volumes of data, and innovate without the constraints of traditional on-premises infrastructure. Major cloud providers include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
Question: What is Virtualization?
Answer: Virtualization involves creating virtual versions of computing resources like servers, storage, and networks.
It allows multiple virtual instances to run on a single physical hardware platform.
This enhances resource utilization, scalability, and flexibility in managing IT infrastructure.
Virtualization abstracts underlying hardware resources, making them independent of physical hardware.
It is widely used in cloud computing, server consolidation, disaster recovery, and testing and development environments.
Common virtualization technologies include hypervisors (e.g., VMware, Hyper-V, KVM), virtual machines (VMs), containers (e.g., Docker), and virtualized network and storage components.
Question: What are Horizontal Scaling and Vertical Scaling?
Answer: Horizontal Scaling (Scale Out) involves adding more instances of servers or nodes to distribute the workload across multiple machines.
Each instance operates independently, enhancing throughput and redundancy, often achieved through load balancing.
It offers improved scalability and fault tolerance, commonly seen in cloud computing and distributed systems.
Vertical Scaling (Scale Up) increases the capacity of a single server by adding more resources like CPU, memory, or storage.
While vertical scaling enhances single-machine performance, it may have limitations in scalability and cost-effectiveness.
The choice between the two depends on factors such as scalability needs, performance requirements, cost considerations, and workload characteristics.
Question: What is the role of a Hypervisor in Cloud Computing?
Answer: Hypervisors in cloud computing abstract physical hardware resources into virtual resources for VMs.
They ensure isolation between VMs, enhancing security and stability in multi-tenant environments.
Hypervisors manage VM creation, provisioning, and lifecycle, facilitating workload management.
They enable hardware independence, allowing VMs to run on different hardware platforms seamlessly.
Features like live migration, fault tolerance, and high availability ensure continuous operation of VMs.
Overall, hypervisors are foundational in cloud computing, enabling virtualization, resource allocation, and reliable service delivery.
Question: Name some renowned cloud service providers.
Answer: Some renowned cloud service providers include:
- Amazon Web Services (AWS)
- Microsoft Azure
- Google Cloud Platform (GCP)
- IBM Cloud
- Oracle Cloud
- Alibaba Cloud
- Salesforce Cloud
- VMware Cloud
- DigitalOcean
- Rackspace
These providers offer a wide range of cloud computing services, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS), catering to various business needs and requirements.
Question: Can you explain in brief about IaaS, SaaS, and PaaS?
Answer:
- Infrastructure as a Service (IaaS):
Provides virtualized computing resources like servers, storage, and networking over the internet.
Users have control over operating systems, applications, and middleware on rented virtual machines.
Examples include AWS EC2, Microsoft Azure Virtual Machines, and Google Compute Engine.
- Platform as a Service (PaaS):
Offers a platform and environment for developers to build, deploy, and manage applications without managing infrastructure.
Provides development tools, databases, middleware, and other services to streamline app development.
Examples include AWS Elastic Beanstalk, Microsoft Azure App Service, and Google App Engine.
- Software as a Service (SaaS):
Delivers software applications over the internet on a subscription basis.
Eliminates the need for local installation, maintenance, and management of software.
Examples include Salesforce, Microsoft Office 365, Google Workspace, and Dropbox.
Question: Explain why Python is an interpreted language.
Answer: Python is considered an interpreted language because it does not require compilation into machine code before execution. Instead, Python code is executed line by line by an interpreter at runtime. Here’s why Python is classified as an interpreted language:
- No Separate Compilation Step: Unlike languages like C or C++, where code needs to be compiled into machine code before execution, Python source code is directly executed by the interpreter.
- Read-Evaluate-Print Loop (REPL): Python supports an interactive mode where code can be entered and executed line by line, allowing for quick testing and prototyping without the need for compilation.
- Bytecode Compilation: Although Python code is executed by the interpreter, it undergoes a compilation step where it is translated into bytecode, which is then executed by the Python virtual machine (PVM).
- Dynamic Typing and Reflection: Python’s dynamic typing and support for features like introspection and reflection make it well-suited for interpretation at runtime, as it allows for flexibility and dynamic behavior.
- Portability: Since Python code is interpreted rather than compiled into platform-specific machine code, Python programs can be easily run on any platform with a compatible interpreter installed.
Question: What is Foreign Key ?
Answer: A foreign key in a relational database is a column or set of columns that establishes a relationship between two tables. It enforces referential integrity by ensuring that the values in the foreign key column(s) of one table correspond to the values in the primary key column(s) of another table. This relationship allows data to be linked across multiple tables, enabling the creation of logical connections between related data entities. Foreign keys are essential for maintaining data consistency and enforcing data integrity constraints in relational databases.
Question: What is Polymorphism and Inheritance?
Answer:
Polymorphism refers to the ability of objects to take on multiple forms or behaviors depending on their context. In object-oriented programming, polymorphism allows objects of different classes to be treated as objects of a common superclass, enabling methods to be called on these objects without knowing their specific types.
Inheritance, on the other hand, is a fundamental concept in object-oriented programming where a class (subclass) can inherit attributes and behaviors (methods) from another class (superclass). This allows for code reuse and promotes the creation of a hierarchical structure, where subclasses can extend and specialize the functionality of their superclass.
Question: What is cross-join?
Answer: A cross join, also known as a Cartesian join, is a type of join operation in SQL that produces the Cartesian product of two tables. It returns all possible combinations of rows from the two tables, where each row from the first table is combined with every row from the second table. In other words, the cross-join generates a result set that contains every possible pair of rows from the two tables, without any specific condition for matching rows. It’s important to use cross joins with caution, as they can result in a large number of rows, especially when working with tables containing a significant number of records.
General Questions
Question: Where do you see yourself in 10 years?
Question: Why Persistent?
Question: What do you know about our company?
Question: If you have multiple offers which is more attractive than Persistent, would you accept Persistent?
Question: What are your hobbies?
Question: How quickly do you adapt to new technology?
Question: Will you work under a bond of two years?
Conclusion
Preparing for data analytics interviews at Persistent Systems requires a blend of technical proficiency, problem-solving acumen, and domain knowledge. By familiarizing yourself with common interview questions and crafting thoughtful responses, you can showcase your expertise and stand out as a top candidate. Remember to approach each question with confidence, clarity, and a strategic mindset, demonstrating your ability to tackle complex data challenges with precision and creativity. Good luck in your interview journey with Persistent Systems!
