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Alteryx Designer Knowledge Base

Definitive answers from Designer experts.
Date/Time data can appear in your data in string formats (text fields) or date formats.  The DateTime Tool standardizes and formats such data so that it can be used in expressions and functions from the Formula or Filter  Tools (e.g. calculating the number of days that have elapsed since a start date). It can also be used to convert dates in datetime format to strings to use for reporting purposes.
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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.
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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:
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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.
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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.
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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:
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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. 
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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.
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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.
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Fact: workflows are the best. Look it up. They’re all about getting things done and, with hundreds of tools and the ability to integrate external processes , there’s no shortage of things you can get done. We know that there are some areas of analytics that require a little extra firepower, however, and that’s why you can leverage your workflows in apps and macros for added functionality.
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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. 
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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 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:   Stacking records 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 community@alteryx.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.
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Data blending, transformation and cleansing..oh my! Whether you're looking to apply a mathematical formula to your numeric data, perform string operations on your text fields (like removing unwanted characters), or aggregate your spatial data (among many other things!), the Formula Tool is the place to start.  With the examples provided below, you should be on your way to harnessing the many functions of the Formula Tool:
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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.
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If you haven’t used the Run Command Tool just yet, that’s great. It means that whatever your analyses required, we had it covered with basic Designer functionality. But in spite of how great the Designer is, it just can’t do everything. There is a utility on your computer that can do just about anything, however, and it’s the command line . The Run Command Tool pairs the two into a dynamic tag-team duo that can wrestle all the computation you could need into one, integrated, Designer workflow:
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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.  
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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. 
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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.
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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.
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The Neural Network Tool in Alteryx implements functions from the nnet package in R to generate a type of neural networks called multilayer perceptrons. By definition, neural network models generated by this tool are feed-forward (meaning data only flows in one direction through the network) and include a single Hidden Layer. In this Tool Mastery, we will review the configuration of the tool, as well as what is included in the Object and Report outputs.
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