What are data intensive applications?
Data intensive applications handle large quantities of data (multiple terabytes and petabytes) that can be complex and distributed across various locations. Data intensive applications process data in multistep analytical pipelines, including transformation and fusion stages.
Some examples of data intensive applications include stock trading applications, user behavior analysis, market simulations, and digital marketing. A stock trading application needs user account information access and also information about the market and portfolios. In digital marketing, there may be several campaigns running at one time, in addition to using demographic information to target specific ads to specific consumers.
When looking at data intensive applications, it’s important to consider the optimal methods of handling high volumes of different types of data, scalability, resilience and security.