Data Analyst Training Program

( 7-Days of Live Session | 100% Free | No Hidden Charges )

7 Days Training
Live Sessions
(Hindi)
Starts:
August
Interview Preparation
Aditya Chandak,
Data Architect

Complete Syllabus

Data Definition Language (DDL):


CREATE: Creating database objects like tables, views, indexes, etc.
ALTER: Modifying the structure of existing database objects.
DROP: Deleting database objects.
TRUNCATE: Removing all records from a table without removing its structure.
RENAME: Renaming database objects.

Data Manipulation Language (DML):


SELECT: Retrieving data from one or more tables.
INSERT: Adding new records to a table.
UPDATE: Modifying existing records in a table.
DELETE: Removing records from a table.
MERGE: Combining INSERT, UPDATE, and DELETE operations into one statement.

Joins:


INNER JOIN: Retrieves records that have matching values in both tables.
LEFT JOIN (OUTER JOIN): Retrieves all records from the left table and matched records from the right table.
RIGHT JOIN (OUTER JOIN): Retrieves all records from the right table and matched records from the left table.
FULL JOIN (OUTER JOIN): Retrieves all records when there is a match in either the left or right table.
CROSS JOIN: Cartesian product of two tables (every combination of rows).

Aggregations:


COUNT: Counting the number of rows or non-null values in a column.
SUM: Calculating the sum of values in a column.
AVG: Calculating the average of values in a column.
MIN: Finding the minimum value in a column.
MAX: Finding the maximum value in a column.
GROUP BY: Grouping rows that have the same values into summary rows.
HAVING: Filtering groups based on a specified condition.

Window Functions:


ROW_NUMBER: Assigning a unique sequential integer to each row within a partition.
RANK: Assigning a rank to each row within a partition, with no gaps in the ranking values.
DENSE_RANK: Similar to RANK, but with no gaps in the ranking values, and ranking values are consecutive integers.
NTILE: Dividing an ordered set of rows into a specified number of equally sized groups.
LEAD and LAG: Accessing data from subsequent or preceding rows within the same result set.

Common Table Expressions (CTE):


WITH: Defining temporary result sets within a query block.
Recursive CTE: A CTE that references itself, useful for hierarchical data or recursive queries.

Filters:


Filtering rows based on a specified condition.
Supports comparison operators (e.g., =, <>, <, >, <=, >=), logical operators (e.g., AND, OR, NOT), and IN, BETWEEN, LIKE, IS NULL, and other operators.

Who is this Workshop for?

Data Scientist
Data Analyst
IT Professionals
Financial Analysts
Students
Marketing Professionals
Data Engineers
Business Professionals
Anyone who wants to learn SQL

Contact Us

Why us?

Nitya Cloudtech is your trusted partner in navigating the ever-evolving landscape of technology. We specialize in offering comprehensive training programs on cutting-edge technologies and cloud platforms like Azure and AWS. Our mission is to seamlessly bridge the gap between academic learning and real-world industry demands, ensuring that aspiring tech professionals are equipped with the skills and knowledge needed to thrive in their careers.