Mastering Data Profiling in Alteryx

Alteryxis an incredibly powerful data analytics tool used by Business Analysts, Data Analysts, System Integrators for a wide range of purposes. Learn how to utilize the Data Profiling functions to help you build out workflows even faster. First, let’s look at what Metadata is and what data types are.

What is Metadata?

Metadata is information that describes data or other types of information. It provides context and additional details about a piece of data, is helpful to better understand and use that data.

What are Alteryx Data Types?

In Alteryx the most common piece of metadata is the data type. Data types define whether a field is text (string) or is a number. Only number data types can have mathematical formulas applied to them. Data Types can also impact how quickly a workflow runs and how much processing power calculations take.

Alteryx has a very useful reference guide on data type differences: Data Types | Alteryx Help

What is Data Profiling?

Data profiling is the process of analyzing, summarizing, and validating data to gain a better understanding of its structure, content, and quality. It involves identifying patterns, anomalies, and inconsistencies in data sets, which helps in making informed decisions about data usage.

Data Profile View in Alteryx

The Importance of Data Profiling in Alteryx

In Alteryx, data profiling is important because it enables users to quickly and easily assess the quality and reliability of data sets. By identifying issues such as missing values, outliers, and data inconsistencies, users can take corrective action before using the data for analysis or other purposes. This not only helps in improving the accuracy and reliability of data but also saves time and resources that might otherwise be spent on data cleaning and preparation.

Additionally, data profiling helps in identifying data relationships, such as correlations between variables, that can be leveraged to gain insights and make better decisions. It also helps in identifying data security and privacy risks, such as sensitive information that may be exposed due to poor data management practices. Overall, data profiling is a crucial step in the data analysis process that helps in improving the quality and usability of data sets.

Alteryx Data Investigation Tool Section

Data Profiling Tools in Alteryx are available under the Data Investigation Section of Alteryx Designer for Desktop. These tools are meant to assist in the identification of potential problems with your data, while most tools designed to fix these problems are under the Preparation Tools section.

Alteryx Data Investigation Tools

How to Use the Basic Alteryx Data Profiling Tool

The Alteryx Basic Data Profiling Tool provides useful information about your incoming data. It will show you a set of statistics for each of the columns in your data.

Field Name lists the name of each column, while Name gives you a separate statistic for that column and Value is the Count or status.

You can add a Crosstab tool after the Basic Data Profile tool to flip the data and make it easier to read. Another technique is to add a Filter tool, and Filter on the Name field for items of interest, such as Nulls.

A setup for the Basic Data Profiling tool may look something like the following. Crosstab and Filter Tools are optional.

Screenshot of Alteryx Basic Data Profiling Tool

How to Profile Data with the Alteryx Browse Tool

The Basic Data Profiling Tool expands on the statistics available to you in the browse tool and allows you to see all statistics on all fields at the same time. While the Browse tool shows the same data profiling information, it requires you to click into each individual column to view information on it.

Add a Browse tool to your Alteryx Workflow and Click on one of your column names to view detailed Data Profiling information on that column.

Note: Browse Tools can be added to any tool with the keyboard shortcut: CTRL+SHIFT+B

Screenshot of Alteryx Data Profiling from the Browse Tool

Alteryx Field Summary Tool

The Field Summary Tool provides statical detail about your dataset on a column-by-column basis. It’s commonly used for data exploration, data validation, or feature engineering, prior to feeding your dataset into a predictive model.

Scatter Plots and value distribution graphs require the addition of browse tools which can all be added at the same time by using the CTRL + Shift + B keyboard shortcut.

Screenshot of Alteryx Field Summary Tool

Working With Alteryx Metadata

Alteryx metadata refers to information about data that is stored and managed within the Alteryx platform. It includes details about the structure, content, and quality of the data, as well as information about how the data is processed and transformed within the Alteryx workflows.

Alteryx metadata can include a wide range of information, such as:

  1. Data source information: including the type of data source, location, and access credentials.
  2. Field-level information: such as field name, data type, and any transformations or calculations applied to the data.
  3. Workflow information: including details about how the data is processed and transformed within the Alteryx workflows.
  4. Dependency information: showing any upstream or downstream dependencies between data sources, fields, or workflows.
  5. Data quality information: such as data profiling results, data lineage, and data validation rules.

Alteryx metadata is an important part of the Alteryx platform, as it helps users to understand and manage their data more effectively. It can be used to identify data quality issues, track data lineage, and optimize workflows for better performance. Alteryx provides various tools for working with metadata, such as the Metadata Loader tool and the Data Profiling tool, to help users manage and analyze metadata efficiently.

View Alteryx Metadata with the Metadata Results View

From the Results pane at the bottom of your workflow, you can switch between Data and Metadata view. This view is read only but gives you detailed information about the data type of each field at that point in time. The screen is read only

Alteryx Metadata Results View

Alteryx data type changes can be made with several different tools. The most common tool used is the Select Tool, but you can also use a ToString Formula, ToNumber Formula, the embedded select tool that’s part of the Join tool, or you can change data types using the Multi-Field Tool.

An often overlooked Alteyrx Tool is the Auto Field Tool. It will take incoming data, sample it, and automatically assign a data type to each column and fit the data to the smallest size possible. The tool is mostly used with large datasets with a high number of columns so you won’t have to manually assign a data type to each one.

Metadata related to the workflow itself can be found under Workflow – Configuration and includes information such as Engine Temp File Path, Version, Workflow Directory, and File Name.

Other Alteryx Tips and Tricks and Optimization Guide

If you’re reading this article it’s safe to assume you’re on your way to becoming an expert in Data Analytics and are well versed in the Alteryx Analytics Platform. We put together a collection of our favorite time saving Alteryx Tips and Tricks for Beginners to Advanced users.

We also put together our Top 10 Ways to Improve Workflow Speed to help troubleshoot workflows that take a long time to run, and how to reduce the amount of time that it takes to develop workflows.

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