One of the uses for sparse columns will likely be replacing entity-attribute-value designs. In an EAV design, the "sparse attribute" values are represented by a separate table. The attribute value can either be declared as (n)varchar or sql_variant. An example I've always used is the hardware store that wants to keep track of its products in a "products" table, but each product has different attributes. If you use the minimum number of columns to simplify the example, the EAV design looks like this.

create table products — base table
 id int primary key,
 name varchar(max)
create table properties — sparse attribute (name-value pair) table
 id int,
 name varchar(50),
 value varchar(max),
 CONSTRAINT PK_properties PRIMARY KEY (id, name),
 FOREIGN KEY (id) REFERENCES products (id)

Here's a straightforward way to convert the table to use SQL Server 2008's sparse columns. It uses dynamic SQL, but in this case there's no user input (SQL injection worries).

declare @tab nvarchar(max),
        @sql nvarchar(max)

set @tab=N'create table products2 (id int primary key, name nvarchar(max) '
select  @tab=@tab+','+ name + ' varchar(max) sparse' from properties
group by name
set @tab += ' ,col_values xml column_set for all_sparse_columns);'
— select @tab

Populating it is also straghtforward using the pivot operator, introduced in SQL Server 2005. In the case where each item has only one of each sparse property (the table constraint enforces this), and our properties table has only three columns, there's no real aggregation with pivot. The aggregate is just required by the pivot operator syntax. This populates the table:

declare @col nvarchar(max),
        @sql nvarchar(max)

set @cols=N''
select  @cols=@cols+','+ name from properties
group by name
 select @cols
set @cols=substring(@cols,2,datalength(@cols)/2 – 1)
set @sql=N'insert into products2 (id, name,' + @cols + ') select,, '+@cols+
      N' from (
      select id, name, value
      from properties
      ) as q
      for name in ('+@cols+
      ) as PivotTable'
set @sql += ' join products p on ='
— select @sql
exec (@sql)

What remains to be done now is to choose better data types for the sparse columns, if the data isn't really a string. If you haven't enforced value type correctness in the application, this may require some data cleansing. Full example as an attachment. Remember that currently (in CTP6) you can only have 1024 total columns in a table; but the limit will be increased to 30000 sparse columns before RTM. (1.23 KB)