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This article is part of the Tool Mastery Series, a compilation of Knowledge Base contributions to introduce diverse working examples for Designer Tools. Here we’ll delve into uses of the Image Tool on our way to mastering the Alteryx Designer:
A picture is worth a thousand words, right? Save your breath and snap a picture to supplement your analyses and reports with the Image Tool, the camera icon tool residing next to all your other reporting needs in the Reporting Tool Category. Whether you’re looking to build a presentation, report, or email from scratch, or simply add graphics to accentuate your raw data – this tool will make it a breeze to access image files from disk, store image files in physical workflows, or dynamically access image files (even in Blob format!) to pair with any Alteryx output. Use the Image Tool to:
Add visual assets to reports and presentations (attached in Image.yxmd):
Perform dynamic image substitutions (attached in Image.yxmd):
Supplement reporting tables with graphics to make raw data more readable
By now, you should have expert-level proficiency with the Image Tool! If you can think of a use case we left out, feel free to use the comments section below! Consider yourself a Tool Master already? Let us know at firstname.lastname@example.org if you’d like your creative tool uses to be featured in the Tool Mastery Series.
Stay tuned with our latest posts every #ToolTuesday by following @alteryx on Twitter! If you want to master all the Designer tools, consider subscribing for email notifications.
The Find Replace Tool is one of those tools that goes relatively unused and uncelebrated until you stumble into a data blending technique that would be extremely difficult without it – at which point, it becomes your favorite tool in the Designer. You can find it in the Join Category and it’ll make easy string substitutions in your data that would otherwise require herculean effort to work around. Today, we celebrate Find Replace as a hero.
When it comes to spatial analyses, few tools come up more than the Trade Area Tool . Whether you’re looking to pad polygons around your spatial objects in distance or drive time, you won’t need to make a trade-off - just the Trade Area Tool.
This tool provides a number of different univariate time series plots that are useful in both better understanding the time series data and determining how to proceed in developing a forecasting model.
The Association Analysis Tool allows you to choose any numerical fields and assesses the level of correlation between those fields. You can either use the Pearson product-moment correlation, Spearmen rank-order correlation, or Hoeffding's D statistics to perform your analysis. You can also have the option of doing an in-depth analysis of your target variable in relation to the other numerical fields. After you’ve run through the tool, you will have two outputs:
The Multi-Field Formula Tool offers the same functionality as the Formula Tool, but offers the added benefit of applying a function across multiple fields of data all at once. Gone are the days of writing the same function for multiple fields.
Say there are four fields with dollar signs ($) that need to be removed. It could be done with a Formula Tool and a function written for each field:
The Drop Down Tool is part of the Interface Tool Category and can be used when creating Apps. This tool has many great configurations from loading data from within the workflow to using outside sources to update tools. Hopefully, after reading this article and looking at the samples you will feel more comfortable using this tool in your app user interface.
We’ve said it before, and we’ll say it again. The Documentation Tool Category is underrated. Good comments and shareability are always a plus and to help spread the good word, we’re excited to unearth the last gem of the bunch - the Explorer Box Tool . How good could it really be? Well, if the Designer was the 1975 Notre Dame football team, the Explorer Box would be a shoo-in for Rudy. Be it web pages, files, or file explorer windows, the Explorer Box will let you embed and interact with all the above right in your workflows:
The Create Points Tool is the ‘Bonnie’ to your Clyde of any spatial analyses. The Create Points Tool allows you to take your latitude and longitude, often the spatial fields included in datasets, and convert them to a format that can play with Alteryx Spatial toolset. If your dataset lacks the latitude and longitude fields needed there are numerous free websites, geocoders, or geocoding APIs where this information is available.
The Message Tool within the Alteryx Designer is your own personal car alarm. This tool can provide you warnings or errors when your data doesn't meet a user-specified criteria or it can set up to tell you when data does not match.
The Message Tool can be set up to pick up records before, during and after the records have passed through the tool itself. This makes it useful for evaluating your dataset at different parts of your workflow.
Easily the most used tool in the parsing category , the Text To Columns Tool makes for an extremely quick dicing of delimited fields. To use it you only need to specify a delimited field, delimiter(s), whether you’re parsing to rows or columns (you’ll need to specify a number of columns to parse into with this selection) and you’re off. Any way you slice it, this tool has you covered:
The Contingency Table tool is a part of the Data Investigation category in Alteryx Designer, which comes as a part of the predictive tools installation. Intuitively, you can use the Contingency Table tool to create a contingency table.
There’s a lot going on in the world of analytics. Endless data stores and insight are at the other end of an internet connection and, as analysts, we’re always in on the action. Being in the thick of the fray with data whizzing by at lightning speeds, being equipped with the right tools is a must. Like you, Alteryx also likes to live dangerously, and we’re always ready for action.
Linear regression is a statistical approach that seeks to model the relationship between a dependent (target) variable and one or more predictor variables. It is one of the oldest forms of regression and its applications throughout history have been endless for modeling all kinds of phenomena. In linear regression, a line of best fit is calculated using the least squares method . This linear equation is then used to calculate projected values for the target variable given a set of new values for the predictor variables.
The Block Until Done Tool is one of those tools that may not be commonly used when starting out in Alteryx. But as users start building out more complex workflows, if errors start appearing out of seemingly nowhere this tool can come quite in handy. The best way to describe this tool is it is like a traffic controller for your workflow. Alteryx normally processes individual records at a time as it is going through the tools. Meaning if you had, let’s say, a total of three tools in your workflow. All three of those tools are simultaneously working through the dataset. As one record finishes being processed by one tool it starts getting processed immediately by another. When you introduce the Block Until Done Tool anywhere in between these three tools, it will wait until all processes upstream are done before sending records out through each of the three outputs - all of which are optional.
This article is part of the Tool Mastery Series, a compilation of Knowledge Base contributions to introduce diverse working examples for Designer Tools. Here we’ll delve into uses of the Union Tool on our way to mastering the Alteryx Designer:
The Union Tool, the aptly named join category tool with DNA on it, accepts multiple input streams of data and combines them into one, unified, data stream. Whereas the Join Tool combines datasets horizontally (either by a record ID or record position), the Union Tool combines datasets vertically. Not unlike how two nucleic acid strands are unified to form the double helical DNA.
We know, great puns are in our DNA.
The Union Tool has a handful of great applications besides side-stitching punchlines, too. Check them out below:
Have common fields in multiple datasets? Stack them into a single stream with the Union Tool by field name, position, or with manual arrangement:
Don't worry - your datasets don't have to have identical. Any uncommon fields will be at the end of the table, with any fields that are not in a given dataset being populated with null values.
Creating different joins
The Alteryx Join Tool has 3 outputs:
These look like:
If you’re used to SQL joins, these are the left, inner, and right joins, respectively. The Union Tool allows you to effortlessly combine these Join outputs (shaded areas above) to create other, more complex, SQL join configurations like the ones below:
Combining reporting elements vertically
Simply take your reporting elements and specify an Output Order in the Union Tool to stack them vertically - without creating a single reporting element from the combination like the Layout Tool does:
Detouring in apps/macros with help from Tool Containers
See the attached workflow, Union.yxmd, for the stack, join, and reporting examples shown above!
By now, you should have expert-level proficiency with the Union Tool! If you can think of a use case we left out, feel free to use the comments section below! Consider yourself a Tool Master already? Let us know at email@example.com if you’d like your creative tool uses to be featured in the Tool Mastery Series.
Stay tuned with our latest posts every Tool Tuesday by following Alteryx on Twitter! If you want to master all the Designer tools, consider subscribing for email notifications.
You've gotten your long dataset and you want to combine it with another dataset for additional information. Your dataset is nice and clean. Everything is formatted the same, no null values... The whole package. You open up the data to join to and right away you see a ton of clean up that needs to happen: nulls to replace, strings to format appropriately, extra characters, white space, the list goes on. You launch the Designer, and while fast and accurate, you have to set up a new Multi-Field Formula Tool for each situation you need to fix. If only there was a single tool that did it all.
The Generate Rows Tool, which is part of the Preparation tool category, creates new rows of data based on a user defined loop expression. It is especially useful when creating sequences of numbers or dates.
For example, l et's say you have a dataset with products that aren't sold very often (not every month) but you would like to create records for every month and fill in quantity and amount as zero for reporting purposes. You can use the Generate Rows Tool to take the earliest month on the dataset, increment that by one month (generating a new row each time) until it has reached the latest month or the month you are in.
The Alteryx Forest Tool implements a random forest model using functions in the randomForest R package. Random forest models are an ensemble learning method that leverages the individual predictive power of decision trees into a more robust model by creating a large number of decision trees (i.e., a "forest") and combining all of the individual estimates of the trees into a single model estimate. In this Tool Mastery, we will be reviewing the configuration of the Forest Model Tool, as well as its outputs.
Typically the first step of Cluster Analysis in Alteryx Designer, the K-Centroids Diagnostics Tool assists you to in determining an appropriate number of clusters to specify for a clustering solution in the K-Centroids Cluster Analysis Tool, given your data and specified clustering algorithm. Cluster analysis is an unsupervised learning algorithm, which means that there are no provided labels or targets for the algorithm to base its solution on. In some cases, you may know how many groups your data ought to be split into, but when this is not the case, you can use this tool to guide the number of target clusters your data most naturally divides into.
Clustering analysis has a wide variety of use cases, including harnessing spatial data for grouping stores by location, performing customer segmentation or even insurance fraud detection. Clustering analysis groups individual observations in a way that each group (cluster) contains data that are more similar to one another than the data in other groups. Included with the Predictive Tools installation, the K-Centroids Cluster Analysis Tool allows you to perform cluster analysis on a data set with the option of using three different algorithms; K-Means , K-Medians , and Neural Gas . In this Tool Mastery, we will go through the configuration and outputs of the tool.