In cases like this, we generally use a broader set of API and ODBC connections as

our analytical tool of choice to connect to several sources concurrently.

And use additional functionality in the tool to integrate the data

construct analytical data sets.

We then proceed, as we would, using the other methods.

Of course, there are a number of other approaches that we might take when

working with data to get the results we're looking for,

including hybrids of the ones we've discussed here.

For example, I might perform certain manipulations in Excel,

and then import the results into a more sophisticated analysis tool.

I can also do the opposite, using an advanced tool to

isolate some set of data that I want to incorporate into Excel.

Perhaps into a business or financial model.

The approach you take in any situation will depend on what it is

you're trying to do.

But one thing we haven't really discussed is when you'd want to use

one tool versus another.

This is a really complicated question and the answer depends not only on

the capabilities of the tool itself but on the skills of the analysts, the nature of

the data environment and even the organization in which an analyst works.

In our video on data and analysis tools we broadly discussed what functions

each type of tool is designed to perform, but we also saw that there's

quite a bit of overlap in the capabilities of different tools.

What one analyst finds really easy to do in one application

another analyst might find more intuitive in a different application.

That having been said, here are a few ideas that you can start with

that I've drawn from my own experience in leading analytical teams.

But you'll have to discover what works best in your environment.

Let's start with Excel.

Excel is really great for quick and dirty analyses.

Basic charts and graphs are for when you want to share your analysis with business

partners who don't have access to more sophisticated tools.

Excel also makes certain types of manipulations really easy,

like calculations that depend on multiple rows of data.

And it's a great environment for trial and error around really

complicated calculations since you can see every formula in every cell.