Interview Questions Answers in Linux Commands, Database Management

Question { 1646 }

What is the purpose of the "top" command?

Answer

The "top" command is used to monitor system processes and resource usage in real-time.

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Question { 1897 }

How do you check the disk usage in Linux?

Answer

The "df" command is used to display disk space usage of file systems.

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Question { 2038 }

What is a Database Schema and Why is It Important?

Answer

The architecture or blueprint for how data is arranged in a database is called a database schema. It outlines the tables, each table's fields, and the connections between the tables and fields.

Because it gives the data a clear structure and guarantees consistency, clarity, and integrity, a schema is crucial. It aids database managers and developers in comprehending the connections between data and the effective retrieval and manipulation of said data.

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Question { 1801 }

Explain the Difference Between a Primary Key and a Foreign Key.

Answer

Each record in a table is uniquely identified by its primary key, which also guarantees data integrity. There can only be one primary key per table, which guarantees that every record is distinct.
Conversely, a foreign key refers to the primary key in the associated table to establish a connection between two tables. By guaranteeing the validity of the link between the tables and the consistency of the data, this relationship aids in preserving referential integrity between them.

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Question { 1756 }

What is CRUD Operations?

Answer

The four core database management operations are Create, Read, Update, and Delete, or CRUD for short.

Create: To add new records to a table, use the INSERT INTO statement.
Read: To extract data from a table, use the SELECT statement.

Update: To make changes to already-existing records, use the UPDATE statement.
Delete: To eliminate records, use the DELETE FROM statement.

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Question { 1878 }

What are the Different Types of Joins and How do They Work?

Answer

Using an inner join, records from both tables with matching values are retrieved.
All records from the left table and matched records from the right table are retrieved using a left join, also known as a left outer join. Records from the right table that don't match will be NULL.
All records from the right table and matched records from the left table are retrieved using a right join, also known as a right outer join. Records from the left table that don't match will be NULL.

When there is a match in either the left or right table, records are retrieved using a full join (full outer join). Records from both tables that don't match will be NULL.

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Question { 2087 }

Explain the Difference Between OLTP and OLAP Databases.

Answer

Databases made for handling transaction-oriented applications are known as OLTP (Online Transaction Processing) databases. They are designed to handle a lot of brief online transactions (update, remove, insert). Retail sales systems are one example.
Databases created for querying and reporting are known as OLAP (Online Analytical Processing) databases, and they are frequently used for corporate intelligence and data analysis. They are best suited for processes involving a lot of reading on big data sets. Data warehousing is one example.

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Question { 2076 }

What are the ACID Properties in a Database and Why are They Important?

Answer

Reliable transaction processing and database data integrity and dependability are guaranteed by ACID characteristics.

Atomicity: Guarantees that every step in a transaction is carried out successfully; if not, the transaction is terminated.
Consistency: Guarantees that a transaction moves the database between legitimate states.

Isolation: Guarantees that transactions are carried out autonomously and without intervention.
Durability: Guarantees that, even in the event of a system failure, a transaction's outcomes are kept in the database indefinitely.

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Question { 1959 }

Describe the Process of ETL (Extract, Transform, Load).

Answer

The process of moving data into a data warehouse from multiple sources is called ETL:

Extract: Gathering information from many source systems.
Transforming the extracted data into a structure or format that is appropriate for analysis and querying is known as transformation. This could entail making sure the data is consistent, eliminating duplicates, and cleansing the data.

Loading: Putting the converted data into the database or data warehouse of choice.

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Question { 1942 }

What is a Data Warehouse and How is it Different from a Traditional Database?

Answer

A data warehouse is a central repository for storing large volumes of data from multiple sources, designed for query and analysis rather than transaction processing. It supports complex queries, data mining, and business intelligence. Unlike traditional databases optimized for day-to-day operations and transaction processing (OLTP), data warehouses are optimized for read-heavy operations, historical data analysis, and large-scale data aggregation (OLAP).

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Question { 2101 }

10 How to Handle Data Migration Between Different Databases?

Answer

Steps for Data Migration:
• Planning: Assess the source and target databases, and create a detailed migration plan.
• Mapping: Define how data from the source will map to the target database, including any transformations needed.
• Extracting: Extract data from the source database.
• Transforming: Convert the data to match the target schema, clean, and validate it.
• Loading: Load the transformed data into the target database.
• Testing: Verify the migration to ensure data integrity and consistency.
• Monitoring: Monitor the new system to ensure it is functioning correctly.

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Question { 2641 }

What is a Relational Database and How does it Differ from a NoSQL Database?

Answer

Relational databases, which often employ SQL, store data in structured tables with established schemas and relationships. It is appropriate for intricate queries and transactions and guarantees data integrity through ACID characteristics.

Contrarily, a NoSQL database is made to handle unstructured or semi-structured data and can hold information in a variety of formats, including documents, graphs, and key-value pairs. NoSQL databases may not offer the same degree of ACID compliance as relational databases, but they are frequently more adaptable and scalable, making them ideal for big data and real-time online applications.

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Question { 911 }

Explain the Importance of Data Normalization.

Answer

The practice of structuring data to reduce redundancy and enhance data integrity is known as data normalization. It entails creating associations between the smaller tables in a database. The significance of normalization is that it

minimizes the duplication of data.
guarantees the consistency of the data.

simplifies the structure, which facilitates updating and maintenance.
removes unneeded data to improve query performance.

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Question { 2674 }

How to Perform Data Cleaning and Preprocessing?

Answer

Several steps may be involved in SQL data cleaning and preprocessing:

Use the ROW_NUMBER() window function or the DISTINCT keyword to eliminate duplicates.
Managing missing values: To replace NULL values, use functions such as COALESCE.
Use the CAST or CONVERT functions to fix data types.
Utilize string functions like as LOWER, UPPER, TRIM, and others to standardize formats.

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Question { 2532 }

What are the Common SQL Functions Used for Data Aggregation?

Answer

SUM(): Determines a numeric column's total sum.
AVG(): Determines a numeric column's average value.
COUNT(): Determines how many rows satisfy a certain criterion.
MIN(): Determines a column's lowest value.
MAX(): Determines a column's maximum value.

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