Bucketing

Business-Daten mit SQL analysieren

Michel Semaan

Data Scientist

Histogramme – Wiederholung

WITH user_orders AS (
  SELECT
    user_id,
    COUNT(DISTINCT order_id) AS orders
  FROM meals
  JOIN orders ON meals.meal_id = orders.meal_id
  GROUP BY user_id)

SELECT
  orders,
  COUNT(DISTINCT user_id) AS users
FROM user_orders
GROUP BY orders
ORDER BY orders ASC
LIMIT 5;

CASE-Ausdruck

Abfrage

SELECT
  CASE
    WHEN meal_price < 4 THEN 'Günstiges Gericht'
    WHEN meal_price < 6 THEN 'Mittleres Gericht'
    ELSE 'Teures Gericht'
  END AS price_category,
  COUNT(DISTINCT meal_id)
FROM meals
GROUP BY price_category;

Bucketing – Abfrage

WITH user_revenues AS (
  SELECT
    user_id,
    SUM(meal_price * order_quantity) AS revenue
  FROM meals
  JOIN orders ON meals.meal_id = orders.meal_id
  GROUP BY user_id)


SELECT
  CASE
    WHEN revenue < 150 THEN 'Niedriger Umsatz'
    WHEN revenue < 300 THEN 'Mittlerer Umsatz'
    ELSE 'Hoher Umsatz'
  END AS revenue_group,
  COUNT(DISTINCT user_id) AS users
FROM user_revenues
GROUP BY revenue_group;

Bucketing – Ergebnis

revenue_group       users
------------------  -----
Niedriger Umsatz    473
Mittlerer Umsatz    606
Hoher Umsatz        225

Histogramme vs. Balkendiagramme

Histogramm der Bestellungen pro Nutzer

Nutzer pro Umsatzgruppe (Balkendiagramm)

Bucketing

Business-Daten mit SQL analysieren