There is a data visibility limitation regarding caching, meaning it does not create any context for your data. This is because caches are essentially storage units from which you can retrieve data, so they are perfect for spitting out the raw data that you stored within them, but not for giving you any background for that data. Chances are, your data is spread out across separate backend systems, so you will need something that can create context for the diverse forms of data should you need supporting information to understand it beyond what is already stored in the cache.
Furthermore, while caches do offer speedy access to data, they do not enable you to derive insights from the cached data in real-time, almost simultaneously, as events occur (this is where stream processing comes in). Your data loses value to you as time passes, since the time lag involved in collecting the data, combining it all, then analyzing it—perhaps using multiple different applications aside from the cache—consumes valuable seconds that could be used in more productive ways. Unfortunately, caches are not intelligent enough to manipulate, organize, calculate, or analyze data, since their only function is regurgitating stored data. What this means for your company is a slew of missed revenue opportunities that continue to slip through the cracks of your technology infrastructure. Your delayed reaction time, due to the processing time involved with retrieving a certain amount of data from the cache and pushing it through many different backend pipelines, causes you to relinquish a massive amount of actionable information.
A company’s sole reliance on simple cache ushers in the issue of a lack of streamlined and unified presentation of data. This is due to the tedious practice of accessing data, which could be stored in different formats and processing languages, from scattered, heterogeneous backend systems. Caches offer no standardization of how data is delivered to end users and applications. The result: seemingly disconnected and hard-to-use data. When your company possesses many unique sources and databases of data, establishing connections between siloed data sets is crucial for advanced information analysis.