Articles

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Making Data Analytics Simpler: SQL Server and R

R an SQL Server are a match made in heaven. You don't need anything special to get started beyond the basic instructions. Once you have jumped the hurdle of reliably and quickly transferring data between R and SQL Server you are ready to discover the power of a relational database when when combined with statistical computing and graphics.

2015-05-11

9,421 reads

External Article

Alan Cooper: Geek of the Week

Alan Cooper helped to debug the most widely-used PC language of the late seventies and early eighties, BASIC-E, and, with Keith Parsons, developed C-BASIC. He then went on to create Tripod, which morphed eventually into Visual Basic in 1991. Alan remains enthusiastic and interested in development with strong views on Agile and Pair Programming.

2015-05-07

10,006 reads

External Article

Time Slots - An Essential Extension to Calendar Tables

After answering many forum entries from developers asking for help with dealing with SQL that involved time intervals and ranges, Dwain dreamed of a generalized tool that sets up time slots of various sorts without the need to experiment; that could do the heavy lifting, so that developers could do aggregations and reports based on time intervals without the hard graft. Here is Dwain's dream made reality.

2015-05-05

7,291 reads

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Question of the Day

The string_agg function

We create the following table and then insert some records in it:

create table t1 (
   id int primary key,
   category char(1) not null,
   product varchar(50)
);

insert into t1 values
(1, 'A', 'Product 1'),
(2, 'A', 'Product 2'),
(3, 'A', 'Product 3'),
(4, 'B', 'Product 4'),
(5, 'B', 'Product 5');
What happens if we execute the following query in both Sql Server and PostgreSQL?
select id, 
category, 
string_agg(product, ';')
                 over (partition by category order by id
                 rows between unbounded preceding and unbounded following) as stragg
from t1;

See possible answers