Convert DOC to SQL

Why Convert DOC to SQL?

Converting DOC documents to SQL format is essential when you need to import tabular data from Word documents directly into a database. SQL provides the standard language for inserting data into MySQL, PostgreSQL, SQLite, SQL Server, and all relational databases.

SQL (Structured Query Language) has been the standard for relational databases since the 1970s. It provides a universal way to create tables, insert data, and manage database structures that works across all major database systems.

When you convert DOC to SQL, tables from the Word document are transformed into CREATE TABLE and INSERT statements. This allows you to directly execute the SQL file in any database client to import the data.

Key Benefits of Converting DOC to SQL:

• Direct Database Import: Execute SQL file to populate tables
• Schema Generation: CREATE TABLE statements from headers
• Universal Compatibility: Works with all SQL databases
• Version Control: SQL files work with Git
• Data Migration: Move data between different systems
• Seed Data: Create test data for development
• Batch Processing: Import many records at once

Practical Examples

Example 1: Employee Data

Input DOC file (employees.doc) - Table content:

Employee Directory

| ID  | Name        | Department | Email              | Salary  |
|-----|-------------|------------|--------------------|---------|
| 1   | John Smith  | Sales      | [email protected]   | 55000   |
| 2   | Jane Doe    | Marketing  | [email protected]   | 62000   |
| 3   | Bob Wilson  | IT         | [email protected]    | 75000   |

Output SQL file (employees.sql):

-- Employee Directory
-- Generated from employees.doc

CREATE TABLE IF NOT EXISTS employees (
    id INT PRIMARY KEY,
    name VARCHAR(255),
    department VARCHAR(255),
    email VARCHAR(255),
    salary DECIMAL(10,2)
);

INSERT INTO employees (id, name, department, email, salary) VALUES
(1, 'John Smith', 'Sales', '[email protected]', 55000.00),
(2, 'Jane Doe', 'Marketing', '[email protected]', 62000.00),
(3, 'Bob Wilson', 'IT', '[email protected]', 75000.00);

Example 2: Product Catalog

Input DOC file (products.doc) - Table content:

Product Catalog

| SKU     | Name           | Category    | Price   | Stock |
|---------|----------------|-------------|---------|-------|
| SKU001  | Laptop Pro     | Electronics | 999.99  | 50    |
| SKU002  | Wireless Mouse | Accessories | 29.99   | 200   |
| SKU003  | USB Hub        | Accessories | 49.99   | 150   |

Output SQL file (products.sql):

-- Product Catalog
-- Generated from products.doc

CREATE TABLE IF NOT EXISTS products (
    sku VARCHAR(50) PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    category VARCHAR(100),
    price DECIMAL(10,2),
    stock INT DEFAULT 0
);

INSERT INTO products (sku, name, category, price, stock) VALUES
('SKU001', 'Laptop Pro', 'Electronics', 999.99, 50),
('SKU002', 'Wireless Mouse', 'Accessories', 29.99, 200),
('SKU003', 'USB Hub', 'Accessories', 49.99, 150);

Example 3: Customer Orders

Input DOC file (orders.doc) - Table content:

Order History

| Order ID | Customer     | Date       | Total   | Status    |
|----------|--------------|------------|---------|-----------|
| ORD-001  | Alice Brown  | 2024-01-15 | 150.00  | Completed |
| ORD-002  | Charlie Lee  | 2024-01-16 | 89.99   | Pending   |
| ORD-003  | Diana Ross   | 2024-01-17 | 275.50  | Shipped   |

Output SQL file (orders.sql):

-- Order History
-- Generated from orders.doc

CREATE TABLE IF NOT EXISTS orders (
    order_id VARCHAR(50) PRIMARY KEY,
    customer VARCHAR(255) NOT NULL,
    order_date DATE,
    total DECIMAL(10,2),
    status VARCHAR(50)
);

INSERT INTO orders (order_id, customer, order_date, total, status) VALUES
('ORD-001', 'Alice Brown', '2024-01-15', 150.00, 'Completed'),
('ORD-002', 'Charlie Lee', '2024-01-16', 89.99, 'Pending'),
('ORD-003', 'Diana Ross', '2024-01-17', 275.50, 'Shipped');

Frequently Asked Questions (FAQ)

Q: What is SQL?

A: SQL (Structured Query Language) is the standard language for relational database management. SQL files contain statements for creating tables, inserting data, updating records, and querying information. It's supported by all major databases including MySQL, PostgreSQL, SQLite, and SQL Server.

Q: What type of SQL statements are generated?

A: The conversion generates CREATE TABLE statements (defining table structure from column headers) and INSERT INTO statements (for each row of data). The output is compatible with standard SQL and works with most databases.

Q: Which databases can I import the SQL into?

A: The generated SQL is compatible with MySQL, MariaDB, PostgreSQL, SQLite, SQL Server, Oracle, and other SQL-compliant databases. Some syntax adjustments may be needed for specific database features.

Q: How are data types determined?

A: Data types are inferred from the column content. Numeric values become INT or DECIMAL, dates become DATE, and text becomes VARCHAR. You can modify the CREATE TABLE statement to use specific data types for your needs.

Q: What about special characters in data?

A: Special characters like quotes and backslashes are properly escaped in the SQL output. Single quotes become '', and other special characters are handled according to SQL standards to prevent syntax errors.

Q: Can I customize the table name?

A: The table name is derived from the document or table title. You can easily edit the SQL file to change the table name before importing. Just modify the CREATE TABLE and INSERT INTO statements.

Q: How do I import the SQL file?

A: Use your database client to execute the SQL file. For MySQL: mysql database < file.sql. For PostgreSQL: psql database < file.sql. Most database GUI tools (phpMyAdmin, pgAdmin, DBeaver) also have import options.

Q: Are foreign keys and indexes included?

A: The basic conversion creates primary keys from ID columns if detected. Foreign keys and indexes are not automatically generated as they require understanding of table relationships. You can add these manually to the SQL file.