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3. How to Import and View Data
In this lesson, we learn how to connect raw data to Alteryx and previewing it in the Alteryx environment.
To explore more Kubicle data literacy subjects, please refer to our full library.
- A visual map of how data is manipulated in Alteryx
- Users can import data to Alteryx through the Input Data tool
- Users can also drag and drop files onto the canvas
- For more information on the Options available through the Input Data tool, follow this link
- The Browse tool allows users to view all data, even in large data sets
- The Browse tool also offers quick access to statistics about the dataset
Previously, we took a quick look at the different versions of Alteryx and the basic elements of the programs interface.
In the next series of lessons, we'll take much deeper look at individual functions in tools, how they work and help users understand the basic terminology used by the program.
Before jumping into any specific tools, we should define the workflow.
The workflow can be thought of as a visual map of how users can manipulate data in Alteryx.
It comprises of icons that represent one or more inputs along with the tools that are used to manipulate those inputs.
Lines connect those icons to give users a visual understanding of the order in which data is manipulated by the selected tools.
Before we can get into how one can manipulate data, we need to have a dataset.
In this lesson, we'll give users a clear understanding of how to import and view data.
We'll start with importing data into the large blank workspace also known as the canvas.
Alteryx support the variety of data and database file types, however regardless of the type of value of importing or connecting, the process is pretty much the same.
To import our data, we'll first need to navigate to the in out tab on the tools palette and drag the input data icon onto the canvas.
You may notice that the input data icon is also on my favourites tab.
This tab is initially populated with some of the most heavily used tools.
In order to change the contents of this tab, users can toggle the star icon above any of the tools.
For our purposes, I will always ignore the favourites tab so you can see where the tool icons normally live.
At the top of the configuration window on the left, there's an option to connect your data.
Simply click on the down arrow and then either navigate to the file or enter the appropriate database information to find the data that you require.
If we need to import multiple files, we can either repeat this process for each individual file, or simply highlight the selected files and drag them from the PC navigation window directly onto the canvas.
Similar to attaching files to an email.
As we can see, Alteryx will automatically put each of these files into it's own input data icon on the canvas.
I'm now going to leave all the one of these inputs so we're only working with one dataset.
Once we have connected our data, the configuration window expands into three sections.
The tab contains details of the connected file or database.
Below is an options window with various changeable fields.
These options differ depending on the file types that we're importing.
However, there are details in the show notes on options available for CSV files.
Right now, we'll focus on the field length option which appears from many common file types.
Field length is important as unstructured data can have fields of indeterminate length.
The default setting is 254 characters which is nearly two tweets in length may seem generous.
However, if your data contains text heavy fields, you may need to adjust this number.
This will make sure that all your text comes through and is not get truncated or chopped off.
The third section is the preview window which gives us a look at the contents of the dataset.
However, we can use the results window to take a more detailed view of our data.
Or press CTRL+R to run the workflow which will bring our data into Alteryx.
As we can see, the results window can display thousands of rows of data.
However, there is a role in it, and large datasets will not be displayed in their entirety.
To view all data for such datasets we'll need to add the browse tool.
We'll navigate to the in out tab in the tools palette, connect the browse tool to the workflow and run the workflow again.
Any truncated rows would not be displayed in the results window below.
In addition, the browse tool will show us some highlights about the data set in the configuration window.
Also, the results window for the browse tool offers 3 icons on the right side.
Copy results to clipboard, export results to file and open results in new window.
As we can see, the import process is relatively straightforward and can easily handle multiple files.
As a reminder, the workflow is the visualisation of how users manipulate data through Alteryx.
The input data icon represents the basic unit of that workflow; any data that we import to Alteryx.
This data can easily be imported through the normal file navigation system, or users can drag and drop files onto the canvas.
Also remember that it's important to preview datasets as we can easily capture any items that may cause problems down the road.
The best practice for previewing data is through the browse tool as it will show the entire dataset along with some quick statistics.
In the next lesson, we'll look at how Alteryx can help users prepare a data set for analysis.