The simple CASE expression returns the first result whose compareX value is equal to the input_expression.
The searched CASE expression returns the first result whose conditionX is true.
The searched CASE returns results when a boolean expression is TRUE.
(This differs from the simple case, which can only check for equivalency with an input.)
SELECT Id, ItemId, Price,
  CASE WHEN Price < 10 THEN 'CHEAP'
       WHEN Price < 20 THEN 'AFFORDABLE'
       ELSE 'EXPENSIVE'
  END AS PriceRating
FROM ItemSales
| Id | ItemId | Price | PriceRating | 
|---|---|---|---|
| 1 | 100 | 34.5 | EXPENSIVE | 
| 2 | 145 | 2.3 | CHEAP | 
| 3 | 100 | 34.5 | EXPENSIVE | 
| 4 | 100 | 34.5 | EXPENSIVE | 
| 5 | 145 | 10 | AFFORDABLE | 
Use Case
CASE can be used in conjunction with SUM to return a count of only those items matching a pre-defined condition. (This is similar to COUNTIF in Excel.)
The trick is to return binary results indicating matches, so the "1"s returned for matching entries can be summed for a count of the total number of matches.
Given this table ItemSales, let's say you want to learn the total number of items that have been categorized as "Expensive":
| Id | ItemId | Price | PriceRating | 
|---|---|---|---|
| 1 | 100 | 34.5 | EXPENSIVE | 
| 2 | 145 | 2.3 | CHEAP | 
| 3 | 100 | 34.5 | EXPENSIVE | 
| 4 | 100 | 34.5 | EXPENSIVE | 
| 5 | 145 | 10 | AFFORDABLE | 
Query
SELECT 
    COUNT(Id) AS ItemsCount,
    SUM ( CASE 
            WHEN PriceRating = 'Expensive' THEN 1
            ELSE 0
          END
        ) AS ExpensiveItemsCount
FROM ItemSales 
Results:
| ItemsCount | ExpensiveItemsCount | 
|---|---|
| 5 | 3 | 
Alternative:
SELECT 
    COUNT(Id) as ItemsCount,
    SUM (
        CASE PriceRating 
            WHEN 'Expensive' THEN 1
            ELSE 0
        END
       ) AS ExpensiveItemsCount
FROM ItemSales 
CASE's shorthand variant evaluates an expression (usually a column) against a series of values. This variant is a bit shorter, and saves repeating the evaluated expression over and over again. The ELSE clause can still be used, though:
SELECT Id, ItemId, Price,
  CASE Price WHEN 5  THEN 'CHEAP'
             WHEN 15 THEN 'AFFORDABLE'
             ELSE         'EXPENSIVE'
  END as PriceRating
FROM ItemSales
A word of caution. It's important to realize that when using the short variant the entire statement is evaluated at each WHEN. Therefore the following statement:
SELECT 
    CASE ABS(CHECKSUM(NEWID())) % 4
        WHEN 0 THEN 'Dr'
        WHEN 1 THEN 'Master'
        WHEN 2 THEN 'Mr'
        WHEN 3 THEN 'Mrs'
    END
may produce a NULL result. That is because at each WHEN NEWID() is being called again with a new result. Equivalent to:
SELECT 
    CASE 
        WHEN ABS(CHECKSUM(NEWID())) % 4 = 0 THEN 'Dr'
        WHEN ABS(CHECKSUM(NEWID())) % 4 = 1 THEN 'Master'
        WHEN ABS(CHECKSUM(NEWID())) % 4 = 2 THEN 'Mr'
        WHEN ABS(CHECKSUM(NEWID())) % 4 = 3 THEN 'Mrs'
    END
Therefore it can miss all the WHEN cases and result as NULL.
We can use 1,2,3.. to determine the type of order:
SELECT * FROM DEPT
ORDER BY
CASE DEPARTMENT
      WHEN 'MARKETING' THEN  1
      WHEN 'SALES' THEN 2
      WHEN 'RESEARCH' THEN 3
      WHEN 'INNOVATION' THEN 4
      ELSE        5
      END,
      CITY
| ID | REGION | CITY | DEPARTMENT | EMPLOYEES_NUMBER | 
|---|---|---|---|---|
| 12 | New England | Boston | MARKETING | 9 | 
| 15 | West | San Francisco | MARKETING | 12 | 
| 9 | Midwest | Chicago | SALES | 8 | 
| 14 | Mid-Atlantic | New York | SALES | 12 | 
| 5 | West | Los Angeles | RESEARCH | 11 | 
| 10 | Mid-Atlantic | Philadelphia | RESEARCH | 13 | 
| 4 | Midwest | Chicago | INNOVATION | 11 | 
| 2 | Midwest | Detroit | HUMAN RESOURCES | 9 | 
sample on price increases:
UPDATE ItemPrice
SET Price = Price *
  CASE ItemId
    WHEN 1 THEN 1.05
    WHEN 2 THEN 1.10
    WHEN 3 THEN 1.15
    ELSE 1.00
  END
in this way '0' representing the known values are ranked first, '1' representing the NULL values are sorted by the last:
SELECT ID
      ,REGION
      ,CITY
      ,DEPARTMENT
      ,EMPLOYEES_NUMBER
  FROM DEPT
  ORDER BY 
  CASE WHEN REGION IS NULL THEN 1 
  ELSE 0
  END, 
  REGION
| ID | REGION | CITY | DEPARTMENT | EMPLOYEES_NUMBER | 
|---|---|---|---|---|
| 10 | Mid-Atlantic | Philadelphia | RESEARCH | 13 | 
| 14 | Mid-Atlantic | New York | SALES | 12 | 
| 9 | Midwest | Chicago | SALES | 8 | 
| 12 | New England | Boston | MARKETING | 9 | 
| 5 | West | Los Angeles | RESEARCH | 11 | 
| 15 | NULL | San Francisco | MARKETING | 12 | 
| 4 | NULL | Chicago | INNOVATION | 11 | 
| 2 | NULL | Detroit | HUMAN RESOURCES | 9 | 
Imagine that you need sort records by lowest value of either one of two columns.
Some databases could use a non-aggregated MIN() or LEAST() function for this (... ORDER BY MIN(Date1, Date2)), but in standard SQL, you have to use a CASE expression.
The CASE expression in the query below looks at the Date1 and Date2 columns, checks which column has the lower value, and sorts the records depending on this value.
| Id | Date1 | Date2 | 
|---|---|---|
| 1 | 2017-01-01 | 2017-01-31 | 
| 2 | 2017-01-31 | 2017-01-03 | 
| 3 | 2017-01-31 | 2017-01-02 | 
| 4 | 2017-01-06 | 2017-01-31 | 
| 5 | 2017-01-31 | 2017-01-05 | 
| 6 | 2017-01-04 | 2017-01-31 | 
SELECT Id, Date1, Date2
FROM YourTable
ORDER BY CASE 
           WHEN COALESCE(Date1, '1753-01-01') < COALESCE(Date2, '1753-01-01') THEN Date1 
           ELSE Date2 
         END
| Id | Date1 | Date2 | 
|---|---|---|
| 1 | 2017-01-01 | 2017-01-31 | 
| 3 | 2017-01-31 | 2017-01-02 | 
| 2 | 2017-01-31 | 2017-01-03 | 
| 6 | 2017-01-04 | 2017-01-31 | 
| 5 | 2017-01-31 | 2017-01-05 | 
| 4 | 2017-01-06 | 2017-01-31 | 
As you see row with Id = 1 is first, that because Date1 have lowest record from entire table 2017-01-01, row where Id = 3 is second that because Date2 equals to 2017-01-02 that is second lowest value from table and so on.
So we have sorted records from 2017-01-01 to 2017-01-06 ascending and no care on which one column Date1 or Date2 are those values.