1๏ธโฃ What is the role of a data analyst?
A data analyst collects, processes, and analyzes data to help businesses make data-driven decisions. They use tools like SQL, Excel, and visualization software (Power BI, Tableau) to identify trends, patterns, and insights.
2๏ธโฃ Difference between data analyst and data scientist
โข Data Analyst: Focuses on descriptive analysis, reporting, and visualization using structured data.
โข Data Scientist: Works on predictive modeling, machine learning, and advanced statistics using both structured and unstructured data.
3๏ธโฃ What are the steps in the data analysis process?
1. Define the problem
2. Collect data
3. Clean and preprocess data
4. Analyze data
5. Visualize and interpret results
6. Communicate insights to stakeholders
4๏ธโฃ What is data cleaning and why is it important?
Data cleaning is the process of fixing or removing incorrect, incomplete, or duplicate data. Clean data ensures accurate analysis, improves model performance, and reduces misleading insights.
5๏ธโฃ Explain types of data: structured vs unstructured
โข Structured: Organized data (e.g., tables in SQL, Excel).
โข Unstructured: Text, images, audio, video โ data that doesnโt fit neatly into tables.
6๏ธโฃ What are primary and foreign keys in databases?
โข Primary key: Unique identifier for a table row (e.g., Employee_ID).
โข Foreign key: A reference to the primary key in another table to establish a relationship.
7๏ธโฃ Explain normalization and denormalization
โข Normalization: Organizing data to reduce redundancy and improve integrity (usually via multiple related tables).
โข Denormalization: Combining tables for performance gains, often in reporting or analytics.
8๏ธโฃ What is a JOIN in SQL? Types of joins?
A JOIN combines rows from two or more tables based on related columns.
Types:
โข INNER JOIN
โข LEFT JOIN
โข RIGHT JOIN
โข FULL OUTER JOIN
โข CROSS JOIN
9๏ธโฃ Difference between INNER JOIN and LEFT JOIN
โข INNER JOIN: Returns only matching rows in both tables.
โข LEFT JOIN: Returns all rows from the left table and matching rows from the right; unmatched right-side values become NULL.
๐ Write a SQL query to find duplicate rows
SELECT column_name, COUNT(*)
FROM table_name
GROUP BY column_name
HAVING COUNT(*) > 1;
This identifies values that appear more than once in the specified column.
๐ฌ Double Tap โฅ๏ธ For Part-2