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AI and machine learning techniques are being increasingly used in data analytics as a tool for planning, prediction and identifying hidden patterns. Effective use of these tools needs a large volume of data that is presented in a multiplicity of ways . Often, such data needs to be extracted from database that have defined structures and a simple SQL query wouldn’t suffice. A straightforward approach is to write an application, fetch the data from the database, manipulate it through a code to provide the desired output. Postgesql (9.6 and above) provides some excellent features using which the complex data can be retrieved through a query circumventing the need for a code manipulation. In particular Postgre’s CTE ( WITH function) along with the array_agg function proves very handy. This talk discusses the use of CTE and recursive CTE which can be advantageously used to extract several facets of information . A few examples are presented.