Week 21 - SQL Chips and Chunks Newsletter

1. SQL Chip: The WHERE clause is your filter. It lets you sift through all the rows in a table to pull out only the ones that meet a specific condition. Think of it as a gatekeeper, letting only the relevant data pass through to your results.

2. SQL Chunk: Let's use the = operator to find specific information. Imagine you need to find a customer by a precise identifier, like a customer ID.

SELECT
    customer_name,
    email,
    join_date
FROM
    customers
WHERE
    customer_id = 12345; -- The '=' operator finds an exact match

3. SQL Challenge: Sometimes, you need to find data that falls within a range. The BETWEEN operator is perfect for this, as it allows you to filter data between two values, including the endpoints.

SELECT
    order_id,
    order_date,
    total_amount
FROM
    orders
WHERE
    order_date BETWEEN '2025-01-01' AND '2025-01-31'; -- BETWEEN finds data in a specific date range

4. SQL Mistake: A common mistake is using the equals operator (=) when working with partial text matches. The correct operator for this is LIKE. Using = will only return an exact match, which isn't what you want when you're looking for a name that contains a specific word.

-- SQL Mistake Example
SELECT
    product_name
FROM
    products
WHERE
    product_name = 'USB'; -- This only finds 'USB', not 'USB Cable' or 'USB Hub'

-- The FIX: Use the LIKE operator with a wildcard (%)
SELECT
    product_name
FROM
    products
WHERE
    product_name LIKE '%USB%'; -- This finds 'USB Cable', 'USB Hub', and 'Wireless USB Adapter'

5. SQL in Practice: In finance, analysts frequently need to identify fraudulent transactions. A common pattern is to look for transactions that exceed a certain dollar amount. The > operator is an essential tool for this kind of filter.

SELECT
    transaction_id,
    transaction_amount,
    transaction_date
FROM
    transactions
WHERE
    transaction_amount > 5000; -- The '>' operator finds all transactions over $5,000

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