Alteryx Data Types

When Alteryx imports data via an input tool, it assigns a data type to each field based on its best assumption of the data source type. This blog will cover the various Alteryx data types and their significance, and the role datatypes play in the system. 

Alteryx is a powerful tool that combines data preparation, geospatial analytics, and data science capabilities. Alteryx Data provides an easy-to-use solution for handling/preparing data at lightning speed, with the ability to view data changes for each step. Automation is simple to implement and can be changed at any moment. This blog will go through all of the significant Alteryx data types and use them.

In this blog, you will be finding the following topics:

What is Alteryx?

Alteryx is a self-service and advanced analytics platform that allows you to design workflows once and then forget about them. All you have to do now is import the data and execute the process, and Alteryx will take care of the rest. Alteryx has four tools:

  • Alteryx Designer creates workflows
  • Alteryx Server automates and collaborates
  • Alteryx Connect manages data.
  • Model deployment with Alteryx Promote

Alteryx is known for empowering its users by allowing them to extract value from their data while preparing, blending, and visualising all of their data sources quickly and easily. This includes the ability to use complex predictive and geographic analytics without code.

If you want to enrich your career in Business Intelligence & Analytics domain, then visit Mindmajix - A Global online training platform: Alteryx Online Training  Course. This course will help you to achieve excellence in this domain.

What are the Data Types of Alteryx?

Alteryx handles values differently depending on the data type. String, numeric, DateTime, and boolean data types and spatial objects are supported by Alteryx. 

1. String Data

A string represents alphanumeric data containing letters, numbers, spaces, or characters. A string is similar to plain text. Even if the characters in a string are digits, they are all handled as text. While a string may contain text that appears to be a number, it must first be converted to a numeric data type before performing computations.

Strings with varying lengths are more efficient to store. This is because fixed-length strings set aside space for a specific number of characters, whereas variable-length strings only use the space required by the data in that cell. To avoid data being truncated, set a high limit for fixed-length strings.

StringIf the length is less than the longest string you intend to record in the field, the Latin-1 String with Fixed Length Values is truncated. There is a limit of 8192 Latin-1 characters.Any string of plain Latin-1 characters has a consistent length from value to value.
WStringA Wide String can contain any character. However, the maximum number of characters is 8192.Any string with any character and a consistent length from one value to the next.


The length can be changed. To fit the entire string within the field, the field length varies.Any string that contains solely plain Latin-1 letters and has a variable length.
V_WStringa long string with varying lengths The field's length adjusts to accommodate the entire string, and any character is acceptable.Any character-containing string whose length varies from one value to the next.

2. Numeric Data:

Numeric data types include integers, decimals, floating, and doubles. Numeric data types, except Fixed Decimal, are not length-adjustable.

ByteA binary data unit has eight digits. A byte field is a 28-bit positive whole number in 0 to 255.0, 1, 2, 3....253, 254, 255
Int16It is a two-byte numeric number without a decimal.–32,768 to 32,767
Int32There is a four-byte numeric number that does not include a decimal.–2,147,483,648 to 2,147,483,647
Int64The numbers -(263) to (263)-1 are 8-byte numeric numbers without a decimal.–9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
Fixed Decimal

A numerical value that has been decimalized. The length (precision) of a fixed decimal is equal to the width of the integer (left side of the decimal) plus the decimal point plus the width of the scale (right side of the decimal). The negative sign is included in the length of a number.

In Alteryx, a Fixed Decimal is set to 19.6 by default. The decimal point and the negative sign are included in the precision limit of 50. Fixed Decimal is the only numeric data type having a length that can be altered.





A value of 1234.567 equals 1234.57 when the length is 7.2.

A value of 1234.567 with a length of 7.3 causes a field conversion error, and Null output since the value does not fit within the specified precision.

A value of 1234.567 multiplied by 6.1 equals 1234.6.

1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 = 1234.567 x 8.3 =

Because the value does not fit inside the provided precision, a field conversion error and Null output occur from a value of -1234.567 with a length of 8.3.

The result is 1234.567000, with a length of 11.6 and a value of 1234.567.


A single-precision floating-point value. It has four bytes and can represent numbers between +/- 3.4 x 10-38 and 3.4 x 1038 with a precision of seven digits.

A float is a floating-point number with a decimal added to save memory in large arrays of floating-point values.

With 7 digits precision, +/- 3.4 x 10-38 to 3.4 x 1038




This is a double-precision floating-point value. It has 8 bytes and can represent integers between +/- 1.7 x 10-308 and 1.7 x 10308 with a precision of 15 digits.

In a double, a decimal can be placed anywhere. A double is a data type with twice as many bits as a float and is frequently used for decimal numbers.

With 15 digits, +/- 1.7 x 10-308 to 1.7 x 10308




3. DateTime Data:

Date, Time, and Date and Time in Alteryx are fixed. If your data isn't in Alteryx's standardized format, you'll have to perform some work with it. Working with dates and times might be tricky; however, an excellent utility called Date Time Macro translates dates and times into human-readable and Alteryx-readable formats. When employing functions in a tool with an expression editor, the Date, Time, and DateTime data types can be treated as strings. The structure is as follows:

  • Date – “yyyy-mm-dd”
  • Time – “hh:mm:ss”
  • DateTime – “yyyy-mm-dd hh:mm:ss”

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4. Boolean Data:

TRUE or FALSE data values are stored as a single byte in the BOOLEAN data type. To test for equality or inequality, you can compare two BOOLEAN values. The Boolean literals t'and'f can also be used to approximate a BOOLEAN value. BOOLEAN values are case-insensitive, therefore 't' is the same stand 'f' is the same as F. 

BoolAn expression has only two possible values: True or False.The phrases 'True' and 'False' appear in the findings where 'False' = 0 and 'True' = non-zero.

5. Spatial Data:

In data analytics, spatial data is commonly utilized to provide a geographic context for a complete picture of data occurrences. Spatial data usually referred to as geospatial data, describes things or events on or near the earth's surface. It could be a park's location, the distance between two workplaces, or the state's borders. When spatial data and analytics are combined, you can gain deeper insights into your business questions. Numeric values indicate the longitude or latitude of a coordinate. Alteryx Designer has a set of spatial tools that may be used to extract useful information and insights from spatial data using spatial analytics.

SpatialOBjA geographical object is present in a data record. Several spatial object fields could exist within a table.You can use a point, line, polyline, or polygon as a spatial object.

[Also Read Alteryx Interview Questions and Answers that helps you in cracking your interview]


We covered all of the different Alteryx data types and how to use them in depth in this blog. Alteryx data types are an excellent tool for assisting you and your company. With Alteryx's broad capabilities, you'll be able to get the most out of your data by quickly and efficiently delivering better data insights and informed decisions.

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Last updated: 03 Apr 2023
About Author


Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .

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