Q6. Can every View be updated?

No. Whether a View is updatable depends on its definition and the database system.

Q7. Does creating a View automatically improve performance?

No. A normal View is primarily used for abstraction, reuse, and centralized logic.

Q8. What is a Materialized View?

A Materialized View stores the result of a query physically and can be refreshed according to the database's configuration.

Q9. Why are Views useful in BI?

They can provide a clean, reusable reporting layer while centralizing SQL transformations and business logic.

Q10. What is one security benefit of Views?

A View can expose only selected columns or rows instead of giving users direct access to the entire underlying table, when combined with appropriate permissions.

🧠 Practice Questions

Practice 1

Create a View containing active customers.

CREATE VIEW active_customers AS
SELECT
    customer_id,
    customer_name,
    country
FROM customers
WHERE status = 'Active';

Practice 2

Query only customers from India:

SELECT *
FROM active_customers
WHERE country = 'India';

Practice 3

Create a View showing total sales by region.

CREATE VIEW regional_sales AS
SELECT
    region,
    SUM(order_amount) AS total_sales
FROM orders
GROUP BY region;

Practice 4

Find regions with sales above 500,000.

SELECT *
FROM regional_sales
WHERE total_sales > 500000;

Practice 5

Create a View combining customers and their orders.

CREATE VIEW customer_orders AS
SELECT
    c.customer_id,
    c.customer_name,
    o.order_id,
    o.order_date,
    o.order_amount
FROM customers c
JOIN orders o
    ON c.customer_id = o.customer_id;

🔥 Mini Challenge

You have:

customers

orders

The customers table contains:

customer_id

customer_name

region

status

The orders table contains:

order_id

customer_id

order_date

order_amount

Create a View called customer_sales_summary containing:

• Customer ID

• Customer name

• Region

• Number of orders

• Total sales

• Average order value

Solution

CREATE VIEW customer_sales_summary AS
SELECT
    c.customer_id,
    c.customer_name,
    c.region,
    COUNT(o.order_id) AS order_count,
    SUM(o.order_amount) AS total_sales,
    AVG(o.order_amount) AS average_order_value
FROM customers c
LEFT JOIN orders o
    ON c.customer_id = o.customer_id
GROUP BY
    c.customer_id,
    c.customer_name,
    c.region;

Now you can easily analyze high-value customers:

SELECT *
FROM customer_sales_summary
WHERE total_sales > 100000
ORDER BY total_sales DESC;

🎯 Key Takeaway

TABLE → Stores data

VIEW → Stores a reusable query definition

MATERIALIZED VIEW → Stores the query result

A strong Data Analyst doesn't just know how to write SQL queries.

They also know how to create reusable, maintainable, and consistent data logic.

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