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Accenture SQL Interview
About Accenture
Accenture is known for offering consulting and technology services globally. Founded in 1989, it is based in Dublin, Ireland. Operations are conducted in over 120 countries with more than 500,000 employees. Many industries like finance, healthcare, and telecommunications are served. Strategy, digital, technology, and operations are provided to businesses by Accenture.
Innovation is emphasized for Accenture’s success. Investments are made in research and partnerships with top technology providers. Industry knowledge is combined with advanced analytics to assist clients. Business processes are improved and cloud services are facilitated. Value creation and performance improvement are aimed for clients by Accenture.
Corporate social responsibility is a key focus. Sustainability and ethical practices are prioritized. Social initiatives and education in underserved areas are supported by Accenture. Inclusion and diversity are promoted in the workplace. A positive impact is aimed for through Accenture’s values and actions.
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Why Join in Accenture?
Joining Accenture offers many benefits for career growth. The company works on exciting, high-tech projects. Employees get to work across different industries and countries. Accenture values innovation and provides a challenging work environment. There are opportunities for learning and career advancement. Good pay and work-life balance are also provided. The company supports inclusion and social responsibility.
Accenture SQL Interview Preparation Tips
1: Which of the following is a JavaScript framework/library?
What is a UNIQUE constraint?
- Definition: A constraint that ensures all values in a column or a set of columns are unique.
- Purpose: Prevents duplicate entries in the specified column(s).
- Example: ALTER TABLE table_name ADD CONSTRAINT unique_constraint UNIQUE (column_name);
What is a Query?
- Definition: A request for data or information from a database.
- Types:
- SELECT: Retrieves data from a database.
- INSERT: Adds new data.
- UPDATE: Modifies existing data.
- DELETE: Removes data.
What is Data Integrity?
- Definition: The accuracy and consistency of data within a database.
- Types:
- Entity Integrity: Ensures each row is uniquely identifiable.
- Referential Integrity: Ensures relationships between tables remain consistent.
- Domain Integrity: Ensures data values are within a specific range or format.
What is the difference between Clustered and Non-clustered index?
- Clustered Index:
- Definition: Sorts and stores data rows in the table based on the index key.
- Characteristics: Only one clustered index per table; affects physical order of rows.
- Non-clustered Index:
- Definition: Creates a separate structure from the data rows to store index keys and pointers.
- Characteristics: Multiple non-clustered indexes can exist on a table; does not affect physical order of rows.
What is an Index? Explain its different types.
- Definition: A database object that improves query performance by allowing faster data retrieval.
- Types:
- Clustered Index: Defines the physical order of data in a table.
- Non-clustered Index: Creates a logical order of data without changing the physical order.
- Unique Index: Ensures all values in the index are unique.
- Composite Index: Indexes multiple columns to improve performance on queries involving those columns.
What is a Cross-Join?
- Definition: A type of join that returns the Cartesian product of two tables.
- Characteristics: Combines every row from the first table with every row from the second table.
- Example: SELECT * FROM table1 CROSS JOIN table2;
What is a Self-Join?
- Definition: A join where a table is joined with itself.
- Purpose: Useful for comparing rows within the same table.
- Example: SELECT A.*, B.* FROM employees A JOIN employees B ON A.manager_id = B.employee_id;
What is a Join? List its different types.
- Definition: A SQL operation that combines rows from two or more tables based on a related column.
- Types:
- INNER JOIN: Returns rows with matching values in both tables.
- LEFT JOIN (or LEFT OUTER JOIN): Returns all rows from the left table and matched rows from the right table.
- RIGHT JOIN (or RIGHT OUTER JOIN): Returns all rows from the right table and matched rows from the left table.
- FULL JOIN (or FULL OUTER JOIN): Returns rows with a match in one of the tables.
What is Pattern Matching in SQL?
- Definition: Pattern matching is used to search for specific patterns within column data.
- Key Operators:
- LIKE: Searches for a specified pattern in a column.
- %: Represents zero or more characters in a pattern.
- _: Represents a single character in a pattern.
How to create empty tables with the same structure as another table?
- Using CREATE TABLE AS SELECT
CREATE TABLE new_table AS SELECT * FROM existing_table WHERE 1=0;
- Using CREATE TABLE with LIKE:
CREATE TABLE new_table LIKE existing_table;
What is a Recursive Stored Procedure?
- Definition: A stored procedure that calls itself to perform repetitive tasks.
- Usage: Useful for tasks like traversing hierarchical data (e.g., organizational charts).
What is a Stored Procedure?
- Definition: A precompiled SQL statement or set of statements stored in the database.
- Benefits: Can be executed repeatedly, improves performance, and provides modular code.
What is Collation? What are the different types of Collation Sensitivity?
- Definition: Collation determines how data is sorted and compared in SQL.
- Types of Sensitivity:
- Case Sensitivity: Differentiates between uppercase and lowercase letters (e.g.,COLLATE SQL_Latin1_General_CP1_CI_AS).
- Accent Sensitivity: Differentiates between accented and unaccented characters (e.g., COLLATE SQL_Latin1_General_CP1_CS_AS).
- Kana Sensitivity: Differentiates between Hiragana and Katakana characters.
- Width Sensitivity: Differentiates between single-byte and double-byte characters.
What are the differences between OLTP and OLAP?
- OLTP (Online Transaction Processing):
- Purpose: Handles day-to-day operations and transactions.
- Characteristics: Fast query processing, high transaction volume, normalized data.
- OLAP (Online Analytical Processing):
- Purpose: Used for complex queries and data analysis.
- Characteristics: Optimized for read-heavy operations, supports multidimensional analysis, denormalized data.
What is OLTP?
- Definition: OLTP stands for Online Transaction Processing.
- Purpose: Manages and processes transaction-oriented applications.
- Characteristics: High performance, quick query processing, and supports large numbers of simultaneous transactions.
What is a User-defined Function? What are its various types?
- Definition: A function created by users to perform operations and return values.
- Types:
- Scalar Functions: Return a single value (e.g., RETURN).
- Table-Valued Functions: Return a table (e.g., RETURN TABLE).
- Inline Table-Valued Functions: Return a table from a single SELECT statement.
What is a Foreign Key?
- Definition: A column or a set of columns in one table that uniquely identifies a row in another table.
- Purpose: Ensures referential integrity by linking related data across tables.
- Example: FOREIGN KEY (column_name) REFERENCES other_table(column_name);
What is a Subquery? What are its types?
- Definition: A query nested inside another query used to perform operations that require data from multiple queries.
- Types:
- Scalar Subquery: Returns a single value (e.g., used in SELECT, WHERE clauses).
- Column Subquery: Returns a single column of values (e.g., used in IN clause).
- Row Subquery: Returns a single row of values (e.g., used in comparison with a row).
- Table Subquery: Returns a set of rows and columns (e.g., used in the FROM clause).
What is a Primary Key?
- Definition: A unique identifier for each record in a table.
- Characteristics: Must be unique and not null; ensures each row can be uniquely identified.
- Example: PRIMARY KEY (column_name);
What are Constraints in SQL?
- Definition: Rules applied to columns in a table to ensure data accuracy and integrity.
- Types:
- NOT NULL: Ensures that a column cannot have NULL values.
- UNIQUE: Ensures all values in a column are unique.
- PRIMARY KEY: Uniquely identifies each record in a table.
- FOREIGN KEY: Ensures referential integrity between tables.
- CHECK: Ensures that all values in a column satisfy a specific condition.
- DEFAULT: Provides a default value for a column when none is specified.
What are Tables and Fields?
- Tables: Structures in a database that store data in rows and columns.
- Fields: Columns within a table that store specific pieces of data.
What is the difference between SQL and MySQL?
- SQL: Structured Query Language used to manage and manipulate relational databases.
- MySQL: An open-source relational database management system that uses SQL to interact with the database.
What is SQL?
- Definition: Structured Query Language, used for querying and managing relational databases.
- Purpose: Allows users to create, read, update, and delete data within a database.
What is RDBMS? How is it different from DBMS?
- RDBMS (Relational Database Management System):
- Definition: A type of DBMS that stores data in structured tables with relationships between them.
- Examples: MySQL, PostgreSQL, Oracle.
- DBMS (Database Management System):
- Definition: A software system for managing databases, which can be relational or non-relational.
- Examples: MongoDB (NoSQL), SQLite (lightweight SQL).
What is DBMS?
- Definition: Database Management System, software used to manage and interact with databases.
- Purpose: Provides tools for storing, retrieving, and manipulating data.
What is a Database?
- Definition: A structured collection of data stored and managed electronically.
- Purpose: Organizes and allows efficient access, management, and manipulation of data.
What is the SELECT statement?
- Definition: A SQL command used to query and retrieve data from a database.
- Example
SELECT column1, column2
FROM table_name
WHERE condition;
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Accenture SQL Interview Questions – Download PDF
Accenture SQL Interview Questions: Conclusion
In order to get selected as an SQL developer in Accenture one must crack through the Accenture SQL interview. In this blog we have discussed some sample interview questions. Candidates can use these questions in order to prepare themselves for the interview.
If you’re preparing for an Accenture SQL interview, enhancing your skills with a Full stack developer course can be a game-changer. Not only will you master SQL, but you’ll also gain comprehensive knowledge of both front-end and back-end technologies, making you a versatile candidate. Full stack development courses provide hands-on experience with databases, servers, and client-facing applications, which will help you stand out in a competitive job market and ace technical interviews like those at Accenture.
Frequently Asked Questions
What are the common types of SQL queries you should be familiar with for an Accenture interview?
- SELECT Queries: Retrieve data from tables.
- JOIN Queries: Combine rows from two or more tables.
- GROUP BY Queries: Aggregate data into summary rows.
- HAVING Clauses: Filter groups based on aggregate functions.
- Subqueries: Nested queries to fetch data from other queries.
What SQL functions and operators should you be familiar with for an Accenture SQL interview?
- Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX().
- String Functions: CONCAT(), SUBSTRING(), LENGTH(), TRIM().
- Date Functions: GETDATE(), DATEADD(), DATEDIFF(), FORMAT().
- Mathematical Functions: ROUND(), CEILING(), FLOOR().
- Logical Operators: AND, OR, NOT.
How does Accenture assess your understanding of SQL joins during the interview?
- INNER JOIN: Retrieve matching rows from both tables.
- LEFT JOIN (LEFT OUTER JOIN): Retrieve all rows from the left table and matching rows from the right table.
- RIGHT JOIN (RIGHT OUTER JOIN): Retrieve all rows from the right table and matching rows from the left table.
- FULL JOIN (FULL OUTER JOIN): Retrieve all rows when there is a match in either left or right table.
- CROSS JOIN: Retrieve the Cartesian product of two tables.
What are some common mistakes to avoid when writing SQL queries for an Accenture interview?
- Ignoring Indexes: Not utilizing indexes can lead to slower queries.
- Overusing SELECT: Fetching more data than necessary can affect performance.
- Improper Use of JOINs: Incorrect joins can lead to inaccurate results or performance issues.
- Not Handling NULLs: Failing to account for NULL values in conditions and aggregations.
- Inefficient Subqueries: Using subqueries inappropriately can lead to performance degradation.