Welcome to module two.
In module one we focused on how to think about analytical problems.
And we presented a framework called the information action value chain,
which describes the overall analytical process.
In this module, we'll focus on analytical technologies, or
the tools that are used to store, manipulate, and analyze data.
We'll start by learning about the various ways in which data can be stored.
We'll then introduce a number of concepts related to data and
analytical environments, including big data, cloud computing.
Data virtualization and federation, in memory computing, and
in database analytics.
We'll spend some time understanding a very popular storage
mechanism called the relational database.
Which will prepare us for module three, which is entirely dedicated to learning
how to extract data from these type of databases.
Finally, we'll present a landscape that will help us understand
the spectrum of analytical tools available to us as data analysts.
And we'll provide an overview of some of the more common ways that these tools
are used in the analytical process.
By the end of this module,
you should have a good understanding of what types of analytical tools exist and
what types of activities are suited to each type of tool.
As a practical matter, you should be able to examine your own data environment and
understand how it works and how you can make the best use of it.
Together with module one,
our broader objective here is to ensure that you have a solid thought process and
a good foundation of knowledge about your data environment.
Because regardless of the tools you use, the most important tool of the data
analyst is the one right here between your ears.
Hope you enjoyed the module.