Learn these SQL codes before the interview and perform with 100% confidence – Freshers

March 21, 2024 | by dp

Are you looking for a fresher data analytics job role?
Perform your interviews with 100% confidence. It’s simple and easy to remember

Distinct Values:

SQL Code: SELECT DISTINCT column_name FROM table_name;

Note: Fetches unique values from a specified column.

Understanding JOINs:

SQL Code:

INNER JOIN: SELECT * FROM table1 INNER JOIN table2 ON table1.id = table2.id;

LEFT JOIN: SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id;

RIGHT JOIN: SELECT * FROM table1 RIGHT JOIN table2 ON table1.id = table2.id;

Note: This is essential for combining data from multiple tables.

Aggregate Functions:

SQL Code:

COUNT: SELECT COUNT(*) FROM table_name;

SUM: SELECT SUM(column_name) FROM table_name;

AVG: SELECT AVG(column_name) FROM table_name;

MAX: SELECT MAX(column_name) FROM table_name;

Note: Key for deriving insights from datasets.

Data Filtering with WHERE:

SQL Code: SELECT * FROM table_name WHERE column_name = ‘value’;

Note: Filters records based on specified conditions.

Unveiling Subqueries:

SQL Code: SELECT column_name FROM table_name WHERE column_name IN (SELECT column_name FROM another_table);

Note: Fetches data based on results from another table.

Sorting Data with ORDER BY:

SQL Code: SELECT * FROM table_name ORDER BY column_name ASC|DESC;

Note: Sorts the query result by specified column in ascending (ASC) or descending (DESC) order.

Limiting Results with LIMIT:

SQL Code: SELECT * FROM table_name LIMIT number_of_rows;

Note: This limits the number of rows returned by the query.

Grouping Data with GROUP BY:

SQL Code: SELECT column_name, COUNT(*) FROM table_name GROUP BY column_name;

Note: Group rows that have the same values into summary rows.

Filtering data with WHERE and OR:

SQL Code: SELECT * FROM table_name WHERE condition1 OR condition2;

Note: Filters records based on multiple conditions using logical OR.

Updating Data with UPDATE:

SQL Code: UPDATE table_name SET column_name = ‘new_value’ WHERE condition;

Note: This modifies existing records in a table.

Performing well in SQL interviews is crucial for landing entry-level positions. Master these basic codes and ace your next interview!
Don’t forget to share this article with your friends to help them succeed too.

Getting 100% success in a data analytics interview as a fresher can be daunting, but mastering the essential SQL codes discussed above will significantly boost your chances. SQL (Structured Query Language) is the foundation of data analysis, and knowing these basic codes is crucial for landing entry-level positions in the field.

Benefits and Job Roles:

Learning the above SQL codes will not only help you succeed in data analytics interviews but also prepare you for various job roles in the field. These roles include Data Scientist, Business Analyst, Data Analyst, Database Administrator, and more. Mastering SQL is fundamental to effectively analyzing and interpreting data, making it a valuable skill across a range of industries and job functions.

Comparison with Paid Courses:

While paid courses can offer comprehensive training and in-depth knowledge, learning basic SQL codes through free resources or self-study can also be highly beneficial for job seekers in data analytics. Free resources provide accessible and practical learning opportunities, allowing you to grasp essential concepts quickly and at your own pace. Additionally, demonstrating initiative and self-learning skills can impress potential employers during interviews, showcasing your dedication and enthusiasm for the field. Therefore, combining free resources with practical experience and continuous learning is a cost-effective and efficient way to kickstart your career in data analytics.

Final Words

As a fresher aiming for 100% success in a data analytics interview, mastering basic SQL codes is just the beginning of your journey. Remember, practice makes perfect, so keep honing your skills and seeking opportunities to apply what you’ve learned. With dedication and perseverance, you’ll be well-equipped to excel in your data analytics career.

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