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Alteryx Knowledge Base

Definitive answers from Designer experts.
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The Publish to Power BI Tool has been deprecated and replaced with the Power BI Output Tool. See here for more information about the Power BI Output Tool: https://help.alteryx.com/current/MicrosoftPowerBIOutput.htm The rest of this article refers to the deprecated Publish to Power BI Tool. By combining Alteryx and Microsoft Power BI, organizations can streamline and accelerate the process of preparing and analyzing data. This provides a faster way to deliver an end-to-end experience for data access, preparation, analysis, visualization and consumption — delivering deeper business insight faster with a more complete set of data.   With the new macro connecting to Power BI within Alteryx is even easier!   Depending upon your intentions with the Power BI tool you may need to sign up for Power BI and Microsoft Azure or just Power BI.  If you are only using Power BI independently then Option 1 will be fine, however if you have corporate deployment of Microsoft Azure then Option 2 would be best.   Option 1: This option is ideal if you would like to manipulate your data in Alteryx and then use the visualization methods inside Power BI. This set up is perfect if you are not looking to manage users or connect to local or network directories.   Create a Power BI Account using the 'Get Started Free' Link Follow the steps below Option 2: This option if for a cooperate deployment who utilize the Microsoft Azure. To use the Alteryx application it needs to be registered by your Azure administrator and a Client ID obtained from them. When using an account you setup yourself, you'll need to perform the following Azure Active Directory administration tasks to obtain the Client ID. It is recommended to get help from someone familiar with Azure Active Directory management, however the links below give good step by steps guides on how to set this up.   Create a Power BI Account using the 'Get Started Free' Link Create an Azure Active Directory Tenant Register a Client App Obtain a Client ID If you are unsure if you would need integration between Power BI and Azure here is a useful video explaining the integration.  Follow the steps below Once you have selected your option let's move over to the Designer!   Step 1: Let's move to Alteryx   The Power BI tool can be found in the connectors category once installed from the Macro District on the Alteryx Gallery or the The Alteryx Starter Kit for Microsoft     You can now drag the macro onto the canvas and use it to upload your modified data to Power BI. Step 2: Configuration – Dataset Name   Enter the dataset name as you want it to appear in Power BI   Step 3: Configuration – Table Name   Enter that table name as you want it appear in Power BI   Step 4: Operation   Create New: This will create a new dataset/table. If the dataset already appears it will append ‘_2” to the dataset name. Append: This will append records to the existing table. (Dataset name has to be exact) Replace: This will overwrite the existing table. (Dataset name has to be exact)   Step 5: Advanced Tab   Interactive authorization: This option will prompt the user for their username and password for Power BI. If you are looking to schedule this workflow or upload to the Gallery please choose ‘Hard-coded credentials’ because the interactive authentication will not be able to retrieve the client ID. Refresh token: This option caches a ‘refresh token’ which allows the user to re-run the workflow without the needs to re-authenticate until the refresh token expires. (Check with Microsoft for expiration policies). Uncheck this box if attempting to publish to a different Power BI account so that the user will be prompted for a different username. Unchecking this box and running the workflow will delete the cached refresh token which could be useful if the token becomes corrupted. Hard-coded credentials: Please enter your Power BI Username; Password; and client ID. To obtain. This is the ideal choice if you are looking to schedule or run this workflow on the gallery.   Step 6: Run the workflow!   You can now run the workflow and Publish to Power BI.   Tips and Tricks   Our best practice is to select ‘Work or school account’ Power BI has about a 2GB limit in the cloud, so clean it up now and then.   Common Errors   Publish to Power BI (2) Tool #2: The external program "PBIGetAccessToken.exe" returned an error code: -532462766.     This error is related to write permissions when writing out the access token. This error should be fixed in the latest release on the Macro District As the Tips and Tricks mentioned please select ‘Work or school account’ and enter your credentials. This will prompt a new permissions window. Please hit ‘Accept’ and you should be able to write out the access token correctly.   If you continue to get this error please run Alteryx as Administrator.     Error: Publish to Power BI (48): Tool #4: The type initializer for 'Microsoft.IdentityModel.Clients.ActiveDirectory.AuthenticationContext' threw an exception.   Please check your .NET Framework (the easiest way to find out is probably to navigate to your installed programs via control panel), this tool requires a .NET 4.5 framework.     [Publish to Power BI (1) Tool #4: Loading an assembly required for interactive user authentication failed. Make sure assembly 'Microsoft.IdentityModel.Clients.ActiveDirectory.WindowsForms, Version=2.12.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' exists]   This issue occurs when one of the dependent files (Microsoft.IdentityModel.Clients.ActiveDirectory.WindowsForms.dll) is missing or corrupt. Re-installing the tool should resolve this issue.     Power BI API error….HTTP/1.1 400 (‘error”(code…….     Open PBIX from Power BI webapp, then try to use macro to append/replace dataset of same name as PBIX results in error. The solution is to use a different dataset name. This is a bug in our JSON Build tool please do not have fields containing a period     The browser based authentication dialog failed to complete. Reason: The download has failed (the connection was interrupted)     Please enable TLS in IE advanced settings within internet options.       Authentication failed: Refresh Token is malformed or invalid     The refresh token is corrupted, please delete the refresh token in the same folder of the macro or uncheck refresh token in macro interface.       An Array can’t be at the top level     This is a bug with our JSON build tool please do not start with a number   If you continue to have problems with the Power BI Macro please contact Alteryx Support.   Best,   Jordan Barker Professional Services  
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Quick navigation for the Tool Mastery Series!
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With the release of 2018.3 comes the long-awaited and highly anticipated Python Tool! This article is a general introduction to using the tool.
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Alteryx provides product technical support for a period of eighteen (18) months after the Release Date of each Release Version, as outlined in the tables below.   NOTE: You can find product 'Release Version' details for all Alteryx Analytics Platform products by following the steps here.   Alteryx Designer & Server Release Version Release Date End of Support (EOS) 2018.3.4.51585 8/27/18 2/27/2020 2018.2.6 8/16/2018 2/16/2020 2018.1.6 7/17/2018 1/17/2020 2018.2.5.48994 7/5/18 1/5/2020 2018.2.4.47804 5/31/2018 12/1/2019 2018.1.4.44311 4/2/2018 10/2/2019 2018.1.3.42973 3/6/2018 9/6/2019 11.8.3.40692 1/19/2018 7/19/2019 11.7.4.37815 11/28/2017 5/28/2019 11.5.1.31573 8/15/2017 2/15/2019 11.3.3.30523 7/14/2017 1/14/2019 11.3.2.29874 6/27/2017 12/27/2018 11.0.5.26351 3/21/2017 9/21/2018 11.0.3.25674 2/15/2017 8/15/2018 10.6.8.17850 7/12/2016 6/28/2018 10.6.6.17413 6/28/2016 12/28/2017 10.5.9.15014 5/5/2016 11/5/2017 10.1.7.12188 2/18/2016 8/18/2017 10.1.7.11834 2/4/2016 8/4/2017 10.1.6.11313 1/14/2016 7/14/2017 10.1.6.60263 11/30/2015 5/30/2017 Predictive Analytics 10/24/2015 4/24/2017 10.0.9.58949 9/26/2015 3/26/2017 10.0.9.58645 9/9/2015 3/9/2017 10.0.9.58529 9/3/2015 3/3/2017   Alteryx Connect Release Version Version Information Displayed in Product Release Date End of Support (EOS) 2018.3.0  v18-3-7-20180814.115808-git.ae708379 8/27/18 2/27/2020 2018.2.4.47804 v18-2-6-20180418.134811-git.67cf65dd 5/31/2018 12/1/2019 3.0.0_0c4cae69 v17-4-7-20180212.164240-git.0c4cae69 3/6/2018 9/6/2019 2.0.0_05b4e5c2 N/A 11/28/2017 5/28/2019 1.0.1.31573 N/A 9/12/2017 3/12/2019 1.0.0.31573 N/A 8/15/2017 2/15/2019   Alteryx Promote Release Version Version Information Displayed in Product Release Date End of Support (EOS) 2018.3.4.51585 v2018.3.0 - Build c14dfc7 8/27/18 2/27/2020 2018.2.4.47804 v2018.2.0 - Build 593b5b29 5/31/2018 12/1/2019 2018.1.3.42973 v2018.1.0 - Build 2bfb396 3/6/2018 9/6/2019   Alteryx Analytics Product Compatibility Policy Alteryx is committed to ensuring that workflows created in legacy versions of Alteryx Designer will continue to work as expected with newer versions of Alteryx Designer. Alteryx will identify any known workflow compatibility issues. With the release of 11.7, a user may convert workflows created in a newer version of Alteryx Designer for use in an older version of Alteryx Designer. In this 'downgrade' scenario, a dialog appears asking the user to confirm or cancel the conversion process. Conversions performed in this manner are not fully tested for compatibility. For Alteryx Designer users who also use Alteryx Server, Alteryx is also committed to ensuring that in an upgrade scenario, legacy versions of Alteryx Designer are able to successfully connect to and use the newest Alteryx Server version. Therefore, it is always recommended that Alteryx Server first and the Alteryx Designer installations are upgraded thereafter. Alteryx will identify any known upgrade compatibility issues. If you experience any issues with an upgrade, please visit alteryx.com/support.   Alteryx Designer Predictive Tools Compatibility Policy Alteryx Designer users can install predictive tools for use with open source R, or Microsoft R. This table details the versions compatible with each release of Alteryx Designer.   Alteryx Designer Version Standard R Version RRE - Revolution R Enterprise (renamed as Microsoft R Server in 2016) Microsoft R Client (MRC) Microsoft R Server (renamed as Microsoft Machine Learning Server in 2018) Microsoft Machine Learning Server (MMLS) 2018.3 3.4.4   Deprecated by vendor - Not supported   3.4.3   Deprecated by vendor - Not supported  9.3 2018.2 3.4.4 Deprecated by vendor - Not supported 3.4.3 Deprecated by vendor - Not supported 9.3 2018.1 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 11.8 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 11.7 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 11.5 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 11.3 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 11.0 3.3.2 Deprecated by vendor - Not supported 3.3.2 9.0/ 9.1 NA 10.6 3.2.3 8.0 Not supported NA NA     Supported Browsers for Alteryx Analytics Platform   Alteryx Analytics is supported on the following versions of Chrome, Safari, Firefox, Internet Explorer and Edge web-browsers*:       Chrome - Windows Safari - MacOS Firefox Standard Release Internet Explorer Edge Alteryx Analytics Platform latest 11 and above latest (60 and above for Firefox ESR) 11 and above latest         *Note: from time to time, the vendor may provide an update to its web-browser that results in compatibility issues with the browser version used by Alteryx in the development and pre-release testing of the Alteryx platform. Alteryx will use reasonable efforts to mitigate against this risk but we also encourage you to be mindful of browser versions used within your organization and to manage your deployment of the Alteryx platform accordingly.
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With the Python Tool, Alteryx can manipulate your data using everyone’s favorite programming language - Python! Included with the tool are a few of pre-built libraries that extend past even the native Python download. This allows you to extend your data manipulation even further than one could ever imagine. The libraries installed are listed here - and below I’ll go into a bit more detail on what and why these libraries are so useful.   Each library is well documented, and there’s usually an introduction or examples on their sites to get you started on how a basic function in their library works.     ayx – Alteryx API – simply enough, we’re using Alteryx, sooo yea, kind of a requirement for the translation between Alteryx and Python.   jupyter – Jupyter metapackage – If you’ve used a Jupyter notebook in the past, you’ll notice the interface for the Python Tool is similar. This interface allows you to run sections of code outside of actually running the workflow, which makes understanding and testing your data that much easier. http://jupyter.org/index.html   matplotlib – Python plotting package – Any charting, plotting, or graphical needs you would want will be in this package. This provides a great deal of flexibility for whatever you want to visualize. https://matplotlib.org/   numPy – NumPy, array processing for numbers, strings, records, and objects – Native Python processes data in what some would call a cumbersome way. For instance, if you wanted to make a matrix, a.k.a. a 4x4 table, you would need to create a list within a list, which can slow processing a bit. However, NumPy has its own “array” type that fits the data in this matrix pattern that allows for faster processing. Additionally, it has a bunch of methods of handling numbers, strings, and objects that make processing a whole lot easier and a whole lot faster. http://www.numpy.org/   pandas – Powerful data structures for data analysis, time series, and statistics – This is your staple for handling data within Alteryx. Those who have used Python, but never pandas, will enter a whole new beautiful world of data handling and structure. Data manipulation within Python is faster, cleaner, and easier to code with. The best part about it is that the Python Tool will read in your Alteryx data as a pandas data frame! Understanding this library should be one of the first things to know when tackling the Python code. https://pandas.pydata.org/   requests – Python HTTP for Humans – for all the connector/Download Tool fans out there. If any of you are familiar with making HTTP requests (API calls and the like), then you should introduce yourselves to this package and explore how Python performs these requests. http://docs.python-requests.org/en/master/   scikit-learn – a set of Python modules for machine learning and data mining – Welcome to the world of machine learning in Python! This library is your go-to for statistical and predictive modeling and evaluation. Any crazy and wild methods you’ve learned for machine learning will most likely be found here and can really push the boundaries of data science. http://scikit-learn.org/stable/   scipy – Scientific Library for Python – all your scientific and technical computing can be found here. This library builds off the packages already installed here, like numPy, pandas, and matplotlib. Dealing with mathematical models and formulae are usually located within this library and can help provide that higher level analysis of your data. https://www.scipy.org/   six – Python 2 and 3 compatibility utilities – For those who are unfamiliar, Python versions come in 2 forms, version 2.x and 3.x (with 3.x being the most recent). Now, even though Python 3 is supposed to be the latest and greatest, there are still many users out there who prefer using Python 2. Therefore, integration between the two is a bit tricky with syntax differences, etc. The six module provides functions that are usable between the two so everyone can remain calm and happy! Their documentation is usually coupled with which version the functions most closely align to, so a user can get a better idea to its functionality. https://pypi.org/project/six/   SQLAlchemy – Database Abstraction Library – SQL in Python! Covers all your database needs from connecting to and extracting data, allowing it to interact with your Python code and thus, Alteryx itself. https://www.sqlalchemy.org/   statsmodels – statistical computations and models for Python – This library builds off sci-kit learn but focuses more on statistical tests and data exploration. Additionally, it utilizes R-style formulae with pandas data frames to fit models! https://www.statsmodels.org/stable/index.html   These are the libraries installed with the Python Tool, which can do almost any data function imaginable. Of course, if you’re looking to do something that these libraries don’t provide, there are myriad other Python libraries that I’m sure will help you with your use case. Most of these are also well documented in how to use so search away and let your mind float away in the beautiful cosmos created by Python.
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What’s changing with Alteryx licensing in 2018? Find out in our FAQ!
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Looking for more premium connector and tool content to better equip your Alteryx platform for success? Check out what our partners have been up to!
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As most of us can agree, predictive models can be extremely useful. Predictive models can help companies allocate their limited marketing budget on the most profitable group of   customers,  help non-profit organizations to find the most willing donors to donate to their cause, or even determine the probability a student will be admitted into a given school. A well-designed predictive model can help us make smart and cost-effective business decisions.
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Don’t know the area of your polygon? Need the length of your line? Do you want your spatial object’s X and Y coordinates? Don’t Panic! The Spatial Info tool can translate all that information and more!
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The  Dynamic Replace Tool   is an under-utilized tool in the   Developer Toolset  that is very powerful. It allows for dynamic formulas or conditions to be used in your workflow.  It was first introduced in Alteryx 6.1 . It’s one of the few tools that is currently multi-threaded which makes is fast.
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Set yourself up for success with excerpts from the 2017 Tips and Tricks Book for bringing data into your workflows!
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Set yourself up for success with  excerpts from the 2017 Tips and Tricks Book for workflow design!
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Amazon offers many different services that can be accessed from the AWS Command Line Interface (aka the AWS CLI). Alteryx workflows can take advantage of these services using the AWS CLI from the Run Command tool.   Some of the common uses of the Amazon CLI within Alteryx include: Using S3 with IAM roles Uploading/Downloading file types not currently supported by the S3 Upload / Download tools Interacting with Athena As an example of using the AWS CLI, let’s build a process that can take a local file and copy to S3, using an AWS IAM profile. Here are the steps involved: Review the documentation for the service. In this example, we're using the "S3" service, but Amazon has many different AWS services. Install the AWS CLI on any machines that will need to execute the AWS functions From Windows Command Line, create a working command (Optional step to make calling the CLI easier in the future) – Add reference to the AWS CLI executable to Window Environment variables via My Computer > Right Click > Properties > Advanced System Settings > Environment Variables > System Variables > Select “Path” > Edit > (Add the path to the directory of your installed “aws.exe” file, separated by a semicolon. Do not delete/modify any pre-existing values in the Path variable.) > OK > OK Per the AWS documentation, create a local profile using your IAM role. The local profile references your credentials so that you don't have to pass the credentials in every command. Test the following command in your Windows command prompt, making sure to use a valid local file to copy, and a valid destination location on your S3, and a valid profile name: s3 cp "C:\temp\mylocalfile.csv" "s3://mylocation/mydestinationfilename.csv" --profile MyIAMUser   Once you've validated your command in the command prompt, transfer it to an Alteryx workflow In a new workflow, pull in a “Run Command” tool from the “Developer” category Configure the Run Command tool using the working command:   Test the above As an optional step, we can wrap this functionality into a macro to make it easy to update, and to support batch uploads Add a Control Parameter for “Local File Path” and configure its action to update the specific string value “C:\temp\myfile.csv” Add a Control Parameter for “Destination File Path” and configure its action to update the specific string value “s3://mybucket/myfiletest1.csv” Add a Text Box and configure its action to update the command value “aws” in case the user hasn’t placed the CLI exe in their PATH variables The example above is attached in the 11.3 workflow, SaveToS3_usage.yxzp.
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Have you ever wanted to restrict the fields that flow through your workflow based on their data type? What about only allowing fields that begin with the same word or are in a specific position? The  Dynamic Select  tool is just what you’re looking for!
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A must-have for any app or macro, the  Error Message Tool  displays a prompt to the user based on input from  Interface Tools . Using any expression that evaluates to true, along with any number of user inputs from question  anchor connected Interface Tools, the Error Message Tool can layer even the most involved applications with failsafes that ease a user’s experience through more robust interactions.
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Thanks to the brilliance of  @RobertB  during last year’s Alteryx Innovation Days, we now have  a command line tool in beta  that generates visual markup in the Designer to compare two workflows!
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The  ConsumerView Matching macro  enables users to match their customer file to the Experian ConsumerView data. Starting with customer information such as name and address you can leverage the ConsumerView macro in Alteryx to append a variety of information about your customers such as household segmentation, home purchase price, presence of children in a home, estimated education and income levels, length of residence, and many more!
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The  Append Fields  tool adds  every  row of the source input to   every  row of the target input as new columns. This is also known as a Cartesian or cross join!
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The  Multi-Row Formula Tool  functions much like the normal  Formula Tool  but adds the ability to reference multiple rows of data within one  expression . Say, for example, someone was on the ground floor of a house and had a Formula Tool. They would only be able to talk to the people also on the ground floor. If they had a Multi-Row Formula Tool, though, they would also be able to talk to the people upstairs, in the attic, and in the basement as well.
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Binary Large OBject (BLOB) data types are often used to store images, audio, and other multimedia files/objects in a single, standardized, format for simplified database management - making them a frequent filetype in the Alteryx Designer. Fortunately, with the  Blob Convert Tool , along with the  Blob Input  and  Blob Output   Developer Tools , working with BLOB objects is no more difficult than the file types they represent!
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