Even though we didn't look at any code in this chapter, we still managed to accomplish a lot. We started the chapter by identifying two very realistic needs (a simple high scores table and then a location/venues database), and worked through the thought process behind how you would choose an appropriate storage method.

We saw that for something as simple as a high scores table, a localized SQLite database was both effective and simple to implement. The only real con to this approach was not being able to show global high scores tables, but for most games, this is but a minor feature. However, for our cafe/coffee shop application, we saw that a localized SQLite database was much less effective than having a centralized external database, with the only con for the external database solution being that performance would suffer if repeated, unnecessary network calls were frequently made.

To address this issue, we turned to caching as a solution—using both external and local databases and trying to leverage the pros of each method. However, to build an effective cache requires making several design decisions in order to optimize the cache hit frequency, while minimizing memory consumption and stale data.

Lastly, we ended the chapter by taking not just a step away from the code, but a step away from the Android application itself, and tried to look at our application from a more holistic view. We looked at what a typical data-centric application would look like, and broke the circulation of data down into four parts. Up to this point, we've already covered enough to be able to implement part four of the design (the local cache), and we'll now devote a chapter to each of the remaining three parts. By the end of this book, the goal is for you to be able to confidently design and implement a full-scaled data-centric application.