A USA based client approached Brainvire to develop a financial database search and query tool that generates real-time financial reports based on the requested parameters. The client was working as an investment banker in a reputed financial company and dealt with heavy unstructured data about merger and acquisitions happening around the globe.
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Fabricating real-time reports based on user- selected filter parameters and presenting the entire data in form of precise tabular report was quite complex and challenging as it involves in-depth processing and filtrations over huge bundle of data storage.
In order to overcome such challenge, developers needed to incorporate swift, scalable and modern technology that processes data within fractions of seconds. With the help of AngularJS, our developers appended requested URL, decode URL parameter fields and form real-time query. This is how they process real-time query and generate dynamic reports based on requested parameters.
Whenever a user select the parameters to fetch financial details, a query is generated back in the database and is executed in order to generate user-requested report. Execution of a real-time query on a huge database was quite complex and time-consuming.
Through database normalization along with accurate database indexing through methods like B-tree, hash and partition indexing, our developers optimized database server execution in an effective manner.
Generating dynamic reports based on selected filter options adjoined with various customization options like attributes, aggregation and time breakdown was quite complex and challenging.
By application of various joints like inner-join, outer-join, left-join and right-join dynamically as per user requested parameters, our developers managed this scenario in an efficient manner.
There are times when a user selects the same parameters and process same queries over multiple times on the server. It will not only increase server overhead but will also results in degradation of data processing efficiency.
In order to boost server performance, our developers came up with mem-cache mechanism that will store all the processed query in cache memory. So, the next time if the user performs the same query, it will retrieve results from cache memory instead of server and thus reduce server overhead and boost its performance.
Implementation of caching mechanism resulted in faster data processing which ultimately results in enhanced website performance.
Leveraging options like “Custom Filters” and “Advanced Query Builder” helped generate scalable and customized financial reports.
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