Although DataManager can handle very large datasets or files, it is comparable to most tools of its type, in that, when it comes to big data, it has essentially constrained your machine resources--processor speed, memory, and storage space. However, that is not to say it is not a very useable and effective tool for addressing big data quality (as well as accomplishing other objectives as well).
As with most big data scenarios, some of the big data challenges can be addressed outside of the tool but you can also be successful through leveraging features and functionalities within DataManager. In addition, using the appropriate strategies, you can overcome any limitations a machine may apply.
The examples in the upcoming sections of this chapter aim to properly illustrate some of those big data strategies as well as addressing the outlined data quality categories.
