Alteryx Data Types

As organisations generate large volumes of business data, they must analyse it to identify trends, track performance, and discover new opportunities. According to Market Research Future, the data analytics market is expected to reach $1,309.6 billion by 2035, with a 27.6% CAGR (2025–2035).

Alteryx is a data analytics and process automation platform that enables users to build repeatable workflows for data preparation, blending, spatial analytics, and advanced analytics. Alteryx supports several data types, including string, numeric, date/time, Boolean, spatial object, and binary/blob types.

This blog discusses Alteryx data types in detail to help you use them effectively.

Table of Contents

• Alteryx - An Introduction
• Data Types
• Key Tools
• FAQs
• Conclusion

Alteryx - An Introduction

Alteryx is a powerful tool that combines data preparation, geospatial analytics, and data science capabilities. It enables users to transform and analyse data through visual workflows.

Alteryx One combines Designer, Server, Analytics Cloud, and Connect in a single platform. Alteryx One is an AI platform that connects data, analyses it, and helps users make quick decisions.

You can configure steps to connect to data sources, transform and analyze data, and then run or schedule workflows as required.

Alteryx provides visual, low-code, and no-code tools; however, it uses code-based extensions for specialised use cases. Alteryx provides several key products, including:

Alteryx Data Types

Data types and their behaviour can vary across tools and data sources. Incorrect data types lead to calculation errors, slower workflows, and failed joins. Therefore, you should use the appropriate data type for every Alteryx workflow that you create.

1. String Data

A string represents text data containing letters, numbers, spaces, and other characters. Even when a string contains only digits, the digits are considered text. Although a string may contain a value that appears to be a number, it must first be converted to a numeric data type before performing computations.

Alteryx offers fixed-length and variable-length string types. Choose the right type and size based on the expected data, workflow requirements, and destination system.

Choose a field size large enough to accommodate the expected values without truncation. Also, avoid making the field definitions larger than necessary.

 

2. Numeric Data

Numeric data types include integers, fixed decimals, floating-point numbers, and doubles. Numeric data types, except Fixed Decimal, do not have adjustable field sizes.

Type	Description	Example
Byte	A byte is an 8-bit numeric type that stores whole numbers from 0 to 255.	0,1,2,3....253,254,255
Int16	Int16 is a two-byte numeric value without a decimal point.	–32,768 to 32,767
Int32	Int32 is a four-byte numeric value without a decimal point.	–2,147,483,648 to 2,147,483,647
Int64	Int64 is an 8-byte integer with a range of -263 to 263-1.	–9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
Fixed Decimal	Fixed decimal is a numeric type that stores values with a defined precision and scale. Precision indicates the total number of significant digits, and scale indicates how many digits are to the right of the decimal point.  The default Fixed Decimal precision and scale are 19.6, with a maximum precision of 50. Fixed Decimal is the only numeric type whose precision and scale you can change.	A value of 1234.567 becomes 1234.57 when the length is 7.2. A value of 1234.567 with a length of 6.1 results in 1234.6. A value of 1234.567 with a length of 8.3 results in 1234.567. The result is 1234.567000, with a length of 11.6 and a value of 1234.567.
Float	Float is a 4-byte single-precision floating-point data type. It can represent values roughly between ±3.4 × 10⁻³⁸ and ±3.4 × 10³⁸ with 7 digits of precision.	With 7 digits of precision, ± 3.4 x 10-38 to ±3.4 x 1038
Double	Double is an 8-byte double-precision floating-point data type. It can represent values roughly from ±1.7 × 10⁻³⁰⁸ to ±1.7 × 10³⁰⁸ with about 15 digits of precision. Double uses floating-point representation. It allows fractional values and a wide range of sizes.	With 15 digits of precision, ±1.7 x 10-308 to ±1.7 x 10308

3. DateTime Data

Alteryx offers separate Date, Time, and DateTime data types with standard formats. If your data is not in Alteryx's standardized format, you may need to transform it first. Note that working with dates and times can be challenging.

If the source data uses a non-standard date or time format, you can use the right DateTime functions or transformation tools. It helps Alteryx parse and convert the data into a usable format.

Date, Time, and DateTime values have standard text forms, but they are still separate data types. You can use Alteryx DateTime functions to parse, format, compare, and convert dates and times. The standard formats are listed as follows:

4. Boolean Data

The Boolean data type represents logical values: true or false. You can compare two Boolean values to test for equality or inequality.

5. Spatial Data

Spatial data describes geographic locations, shapes, and relationships. In Alteryx, spatial objects can represent points, lines, polylines, polygons, and other geographic features.

Spatial data, also called geospatial data, describes things or events on or near Earth's surface. Examples include a park's location, the distance between two workplaces, or state boundaries.

By combining spatial data and analytics, you can gain deeper insights into your business questions. Geographic coordinates, such as latitude and longitude, define locations. Spatial objects represent more complex geographic features such as points, lines, and polygons.

Alteryx provides spatial tools to create spatial objects, calculate distances, match geographic features, and perform other spatial operations.

Key Alteryx Tools

Let’s walk through some key Alteryx tools that support data preparation and workflow development.

1. Auto Field Tool

The Auto Field tool automatically adjusts the field type and size of incoming data to improve the data structure in an Alteryx workflow. The tool examines the data in each selected field and determines the best field configuration.

Let’s look at what this tool does.

• The Auto Field tool can optimize string field sizes based on the values present.
• It optimizes numeric field types when appropriate.  
• It reduces unnecessary field sizes, which can help reduce memory usage.  
• It processes multiple fields without needing you to set up each one manually.

2. Prompt Tool

The Prompt tool became generally available (GA) in Alteryx Designer 2025.2 as part of Alteryx's GenAI tools. This tool lets you send prompts to a configured large language model from an Alteryx workflow and use the model's response as the workflow output. 

In Designer 2026.1, the Prompt tool includes JSON Schema support, which allows you to define structured output, including expected data types and required fields.

3. Precision Match Tool

The Precision Match tool is a GenAI-assisted tool that performs fuzzy matching on string data to standardize variations of the same text. For example, it can standardize values such as “color” and “colour,” or “US” and “United States.”

In Alteryx Designer 2025.2, the GenAI tools, including Precision Match, were part of the Designer Desktop installation instead of requiring a separate installation.  This tool is particularly helpful when handling V_String and V_WString data types during data preparation.

4. AMP Engine

Alteryx Multithreaded Processing (AMP) Engine is Alteryx's workflow processing engine that executes operations in parallel. It improves performance for many workflows, especially for large datasets. It can process independent records or workflow tasks at the same time. 

The AMP engine improves workflow performance compared to the original engine. You can enable or configure AMP in Alteryx Designer at the workflow level. So, ensure compatibility when updating older workflows. That is because some tools or workflow configurations may behave differently when using AMP.

5. Alteryx Designer-Server Decoupling

Alteryx introduced the decoupled update model with the 2025.2 release. This feature allows you to upgrade Designer separately from Server. However, 2026.1 was the first release to allow users to decouple workflows. 

With the new feature, you can upgrade Designer without upgrading Server. For example, you can publish workflows to supported older Server versions with Designer 2026.1. However, if a workflow uses a new Formula function or tool not available on the older Server, it may encounter execution issues.

6. V_String Data Type in Cloud and AMP Environments

The maximum supported length and behaviour for the V_String variable-length string data type can depend on the Alteryx product, processing engine, tool, and data source. 

When designing workflows for Alteryx Cloud or AMP-enabled environments, ensure you meet the relevant field length limits, rather than applying the same limits to all fields.

Frequently Asked Questions

1. What are the data types in Alteryx?

The main Alteryx data types include String, numeric, DateTime, Boolean, SpatialObj, and more.

2. What is V_String in Alteryx?

It is a variable-length string data type you can use to store text.

3. How do I convert data types in Alteryx?

You can use the Select, Auto Field, or Formula tool to change or convert field data types in Alteryx.

4. What is Fixed Decimal in Alteryx?

Fixed Decimal is a numeric data type in Alteryx. It stores decimal numbers with a set precision and scale.

5. Does Alteryx support JSON data types?

Alteryx processes JSON data by importing and reading text strings into standard tabular data columns, such as String, Int32, or others.

Conclusion

This article discussed the main Alteryx data types, including String, numeric, DateTime, boolean, and Spatial.  Understanding Alteryx data types helps you choose the appropriate field definitions, prevent conversion errors, and build more reliable workflows. Correctly defining and managing data types is important for accurate calculations, reliable transformations, and consistent workflow results.

If you are curious to learn more about Alteryx and its data types, you can enrol in an Alteryx course at MindMajix. By the end of the course, you will gain a clear understanding of Alteryx data types and develop your skills in the data analytics field.