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Masking Data in Practice

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Phil Factor takes a strategic look at common SQL data masking techniques, and the challenges inherent in masking certain types of sensitive and personal data, while ensuring that it still looks like the real data, and retains its referential integrity, and distribution characteristics.

2021-01-11

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The Joy of Realistic Generated Fake Database Data

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Have you ever had to demonstrate a database-driven application, and longed to have the real data to do so? To do what, precisely? Well, so you can then scroll through the customers who have used the system, demonstrate the accounting and audit, browse through the products, maybe even demo the customer tracking system with comments, complaints and so on. All this is possible, using realistic, fake data.

2021-01-08

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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;

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