Free SQL Help for Devs, DBAs, and the Curious

SQL Server Reporting Services (SSRS) is a powerful tool that enables businesses to extract valuable insights from their data. However, creating effective paginated reports requires an understanding of best practices. This blog post will cover some of these best practices, using technologies such as SQL Server 2019, MySQL 8.0, DB2 11.5, Azure SQL, and Azure Synapse.

First and foremost, it's crucial to design your reports with the end user in mind. Tailor your reports to meet the specific needs of your audience. This includes using meaningful labels, providing useful descriptions, and arranging data in a logical manner. It's also important to optimize your queries to ensure that your reports load quickly.

For instance, in SQL Server 2019, you can use the PIVOT operator to transform your data into a more readable format. Here's an example:

-- SQL code goes here

SELECT Year, [Product 1], [Product 2], [Product 3]
FROM 
(
  SELECT Year, Product, Sales
  FROM SalesData
) AS SourceTable
PIVOT
(
  SUM(Sales)
  FOR Product IN ([Product 1], [Product 2], [Product 3])
) AS PivotTable;

In MySQL 8.0, you can use the JSON_TABLE() function to convert JSON data into a relational format that can be used in your reports. Here's an example:

-- MySQL code goes here

SELECT *
FROM JSON_TABLE('{"employees": [{"id": 1, "name": "John"}, {"id": 2, "name": "Jane"}]}', '$.employees[*]'
COLUMNS(
  id INT PATH '$.id',
  name VARCHAR(20) PATH '$.name'
)) as jt;

In DB2 11.5, you can use the LISTAGG() function to create a single string from multiple rows of data. This can be useful for creating summary reports. Here's an example:

-- DB2 code goes here

SELECT deptno,
       LISTAGG(surname, ',') WITHIN GROUP (ORDER BY surname) AS employees
FROM employees
GROUP BY deptno;

In Azure SQL and Azure Synapse, it's essential to monitor query performance and optimize your database for reporting. You can use tools like Query Performance Insight and Automatic Tuning to identify performance issues and implement improvements.

Lastly, test your reports thoroughly before deployment. This includes checking for accuracy, performance, and usability. It's also important to provide training and support to your users, as this will ensure that they can effectively use your reports to extract meaningful insights from the data.