Good evening everyone. Was hoping i could get ideas, or maybe steer me in the right direction, on how to build the below (see screenshot).

I have a numeric field called AMOUNT and i need to be able to create a new field that spells out whatever is in the AMOUNT field.

Is there a tool that will do that? Asked Chatgpt and it told me i need to build a macro, but i'm not the best at building macros. Let me know if anyone has ideas. 

(oh i attached an example alteryx workflow if that helps)

Thanks so much.

Hi All, 

I'm looking to generate a list of workflow in each collection level. 

How to generate and what is the process to create a workflow?

Hi All.

I am trying to display a custom message on the Alteryx server after a certain condition is met.

Using Message tool is helpful on the Designer but it does not work on the Server.

I have tried using the Output Message option available at the Interface Designer Setting Option but it is not of much help as my message is not a fixed message.

Thank Your for the help in advance.

Thanks and regards
Gouravi Tandel 

Is there a way (i thought it would be though dynamic rename, but not sure if this is the right way now) of how you can take the data from the first row of data, and add it into the column heading?

So in the images, I want the first row of plant, to be added onto OpenSO Qty Balance as per the second shot.

To add context, I have 3 input feeds and if something changes I want them to pick up the relevant plant that is there to the output.

Thank you in advance.

I asked a question yesterday to learn how to split a datafile by AccountLead, the response I receive works well, thank you! However, I would like my output files to have formatted column headings with colors. I have tried a few different options, including using a template for my output but the issue when I do that is that the flow crating multiple files is not working. I tried the Table tool but same thing I have an issue with creating multiple output files.  Any ideas would be appreciated.

I have a large data set of ranges of a transport network.

I would like to find duplicates on the Start Miles/yards and End Miles/yards.  This is easy enough with a unique tool.  However, I also want to find duplicate entries that fit inside the widest range, for example.

Start mile 29 start yard 770 end mile 29 end yard 109, if there was an entry such as start mile 29, start yard 769 and end mile 29 and end yard 110 I would want to highlight this as a duplicate.

The key unique fields would be the "ELR", "TID", "Direction" fields that must match on each occassion to observe a duplicate.

I am stumped on this one and would really appreciate your help.

David.

I have 300 Records for 12 months of data, that is 25 rows per month Group By Month and value in Descending order. I want to put a record Id for all the records, for example for the 25 records in Jan i want to keep the record ID as 1 to 25 and it has to be the same 1 to 25 for all the other months for total 300 records. how to acheive this?

Hi 

I have the data as attached for 5 year. I need to calculate Each month average. for example for Jan 2025 - The average should calculated by Dec'24+Jan'25/2 and for Feb'25 it should be Jan'25+Feb'25/2 and for all the years data it should calculate in this way

How to Acheive this through Alteryx? Can someone help me out it this?

Hello All,

I need a formula to derive previous business date  from current date. Can anyone assist.

Example -

Input

Today's date - 08/21/2023

Output -

Previous business date - 08/18/2023

HI folks, I need some help summarizing some data.  In the attached file I'm trying to group all data at the ClaimNum level.  I'd like to have one record per claim which means that the LossAddress, Provider and Doctor fields will all represent multiple values in their respective fields.  The LossAddress field is simplest since it would only reflect a single value, but the Provider and Doctor fields should have multiple values each.  

Any guidance is appreciated!

Thanks, 

George

Hi Folks,

I have a list of values, about 25, that I want to match against a field in my master data set.  I'm creating a indicator field with a value (Y) that indicates a match.   I cannot find a function that allows me to add all the match values.  In other software packages it would be called, INLIST or MATCH....does Alteryx have such a tool?

Thanks,

George

Example:   MATCH([match_field], value1, value2, value3.......etc) 

I need to try and split 3 different fields from the same column, at the moment they are under one general category, but i need them into seperate sections. Anybody know a way I can only select one type of text data. So I need to get Global ECM seperated from the Global M&A.

Dear all, I have several excel formulas that I want to translate to Alteryx. I tried to adopt Multi-row formula to update the row, however, the dependency between each field would cause difference answer after I reapply the formula.

e.g. 

but Avg price and Amount c/f  are newly created from the original data set

Appreciate if anyone is willing to give a helping hand, thank you so much.

I am dealing with a misaligned table where column headers are spilt across multiple rows and shifted into the wrong positions. I need to dynamically move the header text to the correct columns and align them properly. (Each column will need to start with its correct title case header)

Hello - thanks for the help in advance. 

I have cells that follow this format:

qual RES1 'Restaurant' = 'Five Guys/Burger {US}'
qual GY1 'Gym' = 'Planet Fitness'
qual LOC1 'Location' = 'New York/{Bronx, Brooklyn}'
concept 'Example 1'

where 'School' = 'Syracuse University' 
  and RES1

  and 'Meal Type' = 'Dinner'

concept 'Example 2'
where GY1

  and 'Day' = 'Wednesday' 

  and LOC1


Above is just an example, but all my cells will follow a similar format. What i need done:

I want all of the qual values at the top to be replaced by their full values throughout the cell. So if in the cell, there is a reference to GY1, I want it to read 'Gym' = 'Planet Fitness'

So in the above, my desired output would look like:

qual RES1 'Restaurant' = 'Five Guys/Burger {US}'
qual GY1 'Gym' = 'Planet Fitness'
qual LOC1 'Location' = 'New York/{Bronx, Brooklyn}'
concept 'Example 1'

where 'School' = 'Syracuse University' 
  and  'Restaurant' = 'Five Guys/Burger {US}'

  and 'Meal Type' = 'Dinner'

concept 'Example 2'
where  'Gym' = 'Planet Fitness'

  and 'Day' = 'Wednesday' 

  and 'Location' = 'New York/{Bronx, Brooklyn}'

Please note the three quals above are examples and my quals will be different, however they will follow the same format and be at the top of the cell. they represent a key that is referenced throughout my cells. I want basically a find and replace done with the qual values throughout the cell. 

I have a data set that I am trying to apply logic to and I don't know the best way to go about it.

Attached is a screenshot of an example set of the data.

If a Test Cycle has both "A" and "C" as the Status for the same "Type", I want only the row with the 'A" to appear.  The workflow can disregard the rows with C.  So in the example, for Test Cycle 21 since the "Type" Apple has both an A and C row, I just want the row A to remain.

For test cycle 34, they have two types, Apples and Bananas.  Since Test Cycle 34 has an A and C for Apples, just the row with "A" should appear for Apples.  For Bananas

, since just Status C appears, I want Alteryx to give me one row with the "C" and the max Canc Dt for those three rows for Test Cycle 34.

Is this easily doable in Alteryx?

StreamIn (52) ERROR [HY000] [AmazonAthena][AthenaClientError]: ExceptionName: InvalidRequestException, ErrorType: 130, ExceptionMessage: Unable to verify/create output bucket aws-athena-query-results-0719165104-us-east-1¶OdbcException¶   at System.Data.Odbc.OdbcConnection.HandleError(OdbcHandle hrHandle, RetCode retcode) ¶   at System.Data.Odbc.OdbcCommand.ExecuteReaderObject(CommandBehavior behavior, String method, Boolean needReader, Object[] methodArguments, SQL_API odbcApiMethod) ¶   at System.Data.Odbc.OdbcCommand.ExecuteReaderObject(CommandBehavior behavior, String method, Boolean needReader) ¶   at System.Data.Odbc.OdbcCommand.ExecuteReader(CommandBehavior behavior) ¶   at org.ForeSight.Tools.Athena.ExecuteScalarQuery(String dsn, String query) ¶   at org.ForeSight.Tools.LakeFormation.GetStagingLocationUri(String odbcDsn, String prefix) ¶   at org.ForeSight.Alteryx.StreamInEngine.WriteData() ¶   at org.ForeSight.Alteryx.StreamInEngine.II_Close() ¶   at SRC.Alteryx.GenericIncomingConnectionHandler.II_Close(GenericIncomingConnectionHandler* )

I have tested every update since version 2024.2.1.41, and none of them have resolved the issues with the Calgary tool. Whether using the AMP engine or not, the Calgary tool is ten times slower than it was in the earlier version. This needs to be investigated seriously, as it represents a significant bug for any users relying on indexing. I have been installing the new versions and testing it, then uninstall it to use 2024.2.1.41.

Problem Statement

Today, many organisations face the same recurring challenge:

Data is engineered in one place, analysed in another, and the connection between the two is often manual, fragile, or inefficient.

• Data engineers work in Databricks, designing scalable pipelines and Lakehouse architectures.
• Business analysts work in Alteryx or BI tools, needing clean, trusted, up-to-date data to make decisions.
• IT teams struggle to provide governed, real-time access without duplicating data or adding operational overhead.
• And small teams or newcomers often believe that building a modern data pipeline requires heavy infrastructure or enterprise licences.

As a result, companies often end up with:

• Inconsistent datasets across teams,
• Delays between engineering and analytics,
• Repeated data extraction or replication,
• Difficulty operationalising insights,
• Frustration on both sides of the “tech vs business” gap.
  
  

This article addresses exactly that problem.

By using only Databricks Free Edition and Alteryx One, we demonstrate that anyone can:

• Build a structured Bronze / Silver / Gold pipeline using Delta Lake
• Expose an analytics-ready table through a Databricks Serverless SQL Warehouse
• Connect Alteryx Cloud via Live Query without moving or duplicating data
• Enrich the dataset with business logic in a no-code Alteryx workflow
• Publish a clean dataset within minutes
  
  

The value?

A fully modern, end-to-end, reproducible analytics pipeline, accessible to both data engineers and business users, without needing a full cloud environment or complex infrastructure.

If your goal is to understand how to connect the Lakehouse world (Databricks) with the no-code analytics world (Alteryx), this article shows the how and the why through a practical example you can reproduce today.

1. Introduction: Why Databricks and Alteryx?

In this article, I’ll walk through a simple yet powerful end-to-end workflow demonstrating how to combine Databricks for scalable data engineering with Alteryx One for intuitive, no-code analytics.

Even with only:

• Databricks Free Edition,
• a single CSV file,
• a small Excel reference table,

…it’s possible to build a pipeline inspired by modern Medallion Architecture, expose clean Delta tables, and make them instantly consumable through Live Query in Alteryx One.

The goal is not to replicate a full enterprise setup, but to show how both platforms complement each other and accelerate analytics for technical and business users alike.

2. End-to-End Architecture Overview

Here is the architecture we will build:

• Ingest a CSV file into Databricks
• Apply Bronze → Silver → Gold transformations
• Store the refined table as Delta Lake table
• Connect Alteryx Cloud Live Query to the Gold table
• Enrich the dataset with an Excel file (business targets and reference data)
• Perform no-code transformations in Alteryx
• Publish a Power BI dashboard for final insights
  
  

The key message is:
Databricks handles scalable data preparation, Alteryx unlocks business-ready analytics.

3. Databricks Pipeline: Simple, Reproducible, and Modern

Even with the Free Edition, Databricks provides everything needed to structure a clear data engineering workflow using Delta Lake and notebooks.

Onboarding for the Free Edition is very easy. You can sign up in just a few clicks by searching “Databricks Free Edition” and opening the official link.

You can sign up for the Free Edition here:

Once you complete the initial steps, you now have access to Databricks, congratulations!

3.1 Bronze – Raw Ingestion

We start by uploading a CSV file into DBFS (or directly from a cloud bucket if preferred).

By clicking “Upload Data,” you can directly add flat files into Databricks. For the purpose of this article, we keep things simple by adding raw data directly into DBFS.

The process is straightforward.

Databricks automatically converts the uploaded file into a Delta table, allowing us to preserve raw data in a single, unified environment.

Opening a notebook, we can now see that our table is available:

Databricks also provides Serverless clusters, meaning you don’t need to configure or manage any compute to start working with your data. It just works, Databricks handles all the compute in the background.

Our files are now fully available in Databricks.

To simulate a production environment, we now copy our data from Raw to Bronze. Databricks structures data into three layers: Bronze (raw), Silver (cleaned and standardized), and Gold (analytics-ready).

Tables are now created and ready for cleansing in the Silver layer.

We are now ready to move to the next stage.

3.2 Silver – Cleaning & Standardization

The Silver layer produces a clean, consistent dataset that enables value creation in the downstream Gold layer. Uncleaned data often contains inconsistent types, missing values, duplicate records, and other quality issues.

To do this, we stay in the same notebook and switch to Python, demonstrating Databricks’ flexibility by allowing users to choose the language they prefer. We start using PySpark SQL so we can easily manipulate the data directly in our notebook.

In a single step, we can now see clean data in our Silver layer after applying correct data types, recalculating amounts, and adding quality filters.

This step can be directly automated from the Notebook interface, allowing us to eliminate manual effort and reduce operational toil.

We are now ready in Databricks to build our Gold layer.

3.3 Gold – Analytics-Ready Table

We simply run a LEFT JOIN between our two Silver tables to produce the Gold table, which is now ready for downstream analytics.

We can now run our Alteryx workflow on this data.

We treat sales_silver as our transactional fact table (each row represents a transaction) and customers_silver as our cleaned customer dimension.

In the Gold layer, we bring both together into a single fact_sales_gold table, which is the one we expose to Alteryx via Live Query.

4. Connecting Alteryx One to Databricks with Live Query

Alteryx One now allows us to use all Alteryx products in a single, seamless experience, whether on the cloud or on a laptop. We first connect to our Databricks data using Alteryx One. To do this, we go to the Alteryx One homepage, click on our profile, and navigate to Workspace Admin.

Here we can see the Databricks menu, where we can provision our Databricks workspace:

This information can be found easily in Databricks.

The service URL is the portion of your Databricks workspace URL up to cloud.databricks.com.

We now return to Databricks to generate the Personal Access Token (PAT). Be mindful of the security implications: these keys should never be shared. Go to your profile, open Settings → Developer, and generate a new token as shown below. Paste this token into Alteryx.

Everything is now set. You just need to fill in the remaining information:

As a final step, in the Data tab, we simply need to add the connection — and we are all set:

Just add a connection name, all information has already been filled in:

Once connected, Alteryx queries the Delta table live, without moving or duplicating data, a perfect fit for Lakehouse patterns..

This allows data engineers to refine the pipeline in Databricks while analysts explore the same data instantly in Alteryx.

5. No-Code Business Enrichment in Alteryx

We can now select our Gold table and begin working with our data:

When loading our data in Alteryx, nothing is actually imported into the backend. Everything stays in Databricks, keeping costs low and minimizing data movement:

This is where Alteryx shines: turning a curated dataset into actionable business insights — without writing code.

We now create an Alteryx workflow in Designer Cloud. From the homepage, click Create New → Designer Cloud to begin:

We can now add an Input tool and start working with our Gold table from Databricks:

By default, LiveQuery is enabled, allowing us to use the entire dataset directly in our browser without any replication in the Alteryx infrastructure. This is a major advantage. It enables full pushdown processing and allows users to leverage no-code tools without copying data, relying instead on the powerful scaling capabilities of Databricks.

You can verify whether Live Query is enabled by clicking your profile icon (top right), navigating to Workspace Admin → Settings, and checking the Enable Live Query option.

We can now import our Excel file into Alteryx One:

We can now add the remaining tools and easily prep and blend the data, without writing a single line of code:

And the beauty of this approach is that all processing happens in Databricks.

7. Combined Benefits of Databricks + Alteryx

🟧 What Databricks brings

• scalable Spark compute
• strong data engineering foundations
• Delta Lake performance & reliability
• structured Medallion architecture (Bronze / Silver / Gold)
  
  

🟦 What Alteryx brings

• no-code transformation for business users
• governed access to Databricks tables
• fast iteration for analytics and enrichment
• seamless export to BI tools
  
  

🟪 Together

Together, they deliver a modern, efficient workflow that bridges engineering and business teams — without unnecessary complexity.

8. Conclusion

This project demonstrates that, even with minimal resources, Databricks Free Edition and an Alteryx One environment, it is entirely possible to build a modern Lakehouse-style pipeline and deliver business-ready insights.

Databricks provides the engine, Alteryx provides the experience, and together they accelerate analytics from raw data to actionable value.

...without tool containers (which I currently use).

The workflow is set up like this.

The Database (Output Tool) in container #1 is the same Database (Input Tool) in container #2. I always need to update it before running the Macro (container #2), which means Run #1, Disable #1, Enable #2, Run #2. I know it's just a few clicks but I do this a lot and would love a solution that means I just run the whole workflow once.

Hello - I am having an issue with Fuzzy Match. 

I have a data source that looks like:

And I have a list of Names that I want to Fuzzy Match for in NAME. For Example, my text looks like

I have the second table as a Text input in my Alteryx flow. I want to Fuzzy Match for the second table values in the first table. Please not my actual data set is much larger, I am just using this as an example. 

Thanks for the help!

Niche request here: does anyone have experience with the ETL of very wide SPSS-derived Excel data sets in Alteryx please?

We have questionnaire results in Excel files (derived from SPSS) which are over 16k columns wide, so in Alteryx just looking at a union tool, for example, can take minutes, and then there's the added complication of mapping the column header codes to their correct aliases... 

We have a very simple working solution, which just Unions the Excel files and then where we deselect all the unused columns via a Select tool, but I feel we could do better, maybe through transposing?  We have left the mapping to Tableau, where we've just assigned aliases.

Any advice would be much appreciated.  Thanks so much in advance.

Hi everyone,

I’m creating a workflow in Alteryx that will call a Macro on a scheduled basis. The Macro receives the following inputs via a Text Input tool:

• Source Oracle table name

• Filter / WHERE clause (if applicable)

• Destination database/schema name in Snowflake

Normally, the Macro processing is straightforward: I use Input Data (Oracle) and Output Data (Snowflake) to establish connections, and a few Control Parameters allow the Macro to sequentially move a set of tables from Oracle to Snowflake.

However, this time I’m encountering some CLOB and BLOB fields that require additional processing, and I need some guidance.

I have two main questions:

1. Dynamic routing based on data type
   a) How can I analyze or parse an incoming table dynamically to identify the data types of each column?
   b) Once the data types are identified, how can I route them to different pipelines for processing? For example:

   • Text, Date, Number → Default Snowflake datatypes

   • BLOB → Use the BLOB Convert tool

   • CLOB 

2. Handling CLOBs
   The sample table I tested on doesn’t have large CLOB values, but the workflow still times out at this step. I assume some additional processing is needed to move the CLOB. How should I handle this efficiently in Alteryx?

I’m relatively new to Alteryx and have only used a limited set of tools, so any tips, best practices, or example workflows for handling CLOBs and BLOBs in a scheduled Macro would be greatly appreciated.

Thank you in advance for your guidance!

i have the below data set. so what i want is to create rows anywhere NBD is NOT 1. for example, for 12/12, NBD = 3.  i want to "fill the gap" by creating 2 rows. one for 12/13 and one for 12/14 with all the data from 12/12. the numbers of rows i need created would be determined by the number in the NBD column - 1.  

start:

end state:

I have a flow with a Directory input to read in all files from a network folder, I use a batch macro to find all sheet names across all of the files & then another batch macro to bring the data into the flow from each of those files, sheets.

Ideally I'd like to create a unioned view of the data BUT I'm struggling with the variances in format. All submissions should be the same format but various customers don't / won't comply. I'm happy to reject a number of submissions but some are simple fixes such as, the data doesn't start on row 1 so I need to look for row headings OR row headings are slightly different. 

These are examples of some of the variances I'd like to fix. The batch macro which picks up all data from all sheets is failing when I bring it into my flow.  The actual headers should be Distributor Account Number, Distributor Name, Date of Purchase, Customer Name, Material Reference Number & Quantity Sold but if this appears on rows 1, or even on rows 6,7 etc I want to start my data collation from there and if the headers say something like Dist Acc No, I want to accept that. 

Recently, I installed the following datasets according to my organization's internal protocols:

• TomTom Geocoder and Reverse Geocoder Macro, Address Points
• Zip+4 Coder
• TomTom Drivetime, Alteryx Maps
• US Census 2010 SF1 Demographic Data
• DNB Analytical File
• Experian CAPE, ACS Demos (incl. PR) and Simmons Syndicated Survey
• Experian Household and Individual Analytica File
• Kalibrate Technologies Traffic Counts Sample

Now, when I attempt to use the dataset in the 'Distance' tool to output drive times between multiple locations, I get the following error: 'Error: Distance (6): The data set "TomTom_US_2019_Q4" is unlicensed.'

I was redirected to this forum by my organization to see how this issue may be resolved. Thank you very much for your assistance!

Hello,

I have a below data set in excel. Data is import from line 1. So Alteryx created the default field Name like Field1,Field2,Field3 etc.

My requirement is the selection of field in output file should be dynamic. If i passed the count 2 from text then it should select only first two columns i.e. F1 and F2 rest should be ignore. If i pass the count 4 then it should select first 4 columns i.e. F1,F2,F3 and F4 from above table.

Once the column selected, the number of columns i need to rename from F1,F2,F3 header with Column1, Column2, Column3 etc.

How can i achieve this? Could you please help!

Your help is really appreciated .

Thank you in advance.

Hello,

I building a GIS map with FELT using census data information. I am interested in using alteryx to clean and reorganized the data set, but I do not have time to figure out how to use the platform. Is there someone who can get on zoom with me and teach/show me how to do what I need to do? Potentially could pay for your time