In this chapter, we looked at various options for combining data. We explored concatenating datasets, interleaving them, and merging them. We also looked at altering and updating datasets. All the methodologies were compared in terms of their pros and cons.
We also looked at mastering combining datasets. When our database numbers increase, combining datasets is one thing we must do to keep everything neat and tidy. With combining datasets comes the problem of faster and more efficient ways to access datasets and protecting the data. Hence, we also looked at indexing and encrypting data. You will end up working with multiple datasets in real-world scenarios, as seldom is data held in one table. Indexing may be required to boost performance, whereas encryption is becoming the norm due to concerns about data security.
In the next chapter, we will learn about transforming...
