Methods and systems for providing database development recommendations based on multi-modal correlations detected through artificial intelligence

A method for providing database development recommendations based on multi-modal correlations detected through artificial intelligence, the method comprising:

• receiving a first user action, at a user interface, requesting a first database development recommendation based on first user selected criteria, wherein the first user selected criteria comprise known static data and expected dynamic data for a first database on a network of disparate computing devices;
• determining, based on the first user selected criteria, a first parameter for the first database development recommendation;
• determining, based on the first parameter, a first subset of static and dynamic training data for generating a first feature input, wherein the first subset comprises data streamed in real time from databases accessible to the network;
• inputting the first feature input into a first machine learning model to generate a first output from the first machine learning model;
• selecting a first database design element from a plurality of database design elements based on the first output;
• and
• generating, at the user interface, the first database development recommendation based on the first database design element.

A non-transitory, computer-readable medium comprising instructions that when executed by one or more processors cause operations comprising:

• receiving a first user action, at a user interface, requesting a first database development recommendation based on first user selected criteria, wherein the first user selected criteria comprise known static data and expected dynamic data for a first database on a network of disparate computing devices;
• determining, based on the first user selected criteria, a first parameter for the first database development recommendation;
• determining, based on the first parameter, a first subset of static and dynamic training data for generating a first feature input, wherein the first subset comprises data streamed in real time from databases accessible to the network;
• inputting the first feature input into a first machine learning model to generate a first output from the first machine learning model;
• selecting a first database design element from a plurality of database design elements based on the first output;
• and
• generating, at the user interface, the first database development recommendation based on the first database design element.