What is the IFERROR function in power bi

This recipe explains what is the IFERROR function in power bi

Recipe Objective - What is the IFERROR function in Power BI?

It evaluates an expression and returns a specified value if the expression returns an error; otherwise returns the value of the expression itself.

Step 1 - Open Power BI report

Step 2 - New Measure

Go to Fields pane -> Right-click on Dataset -> New Measure

Step 3 - Dax query(IFERROR function)

Write down the formula as Check = IFERROR(10/0,100)

As we all know, we cannot divide any number by zero, so this measure will return 100, which is an error value that we have specified.

In this way, we can use the IFERROR function in Power BI.

What Users are saying..

profile image

Ed Godalle

Director Data Analytics at EY / EY Tech
linkedin profile url

I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills... Read More

Relevant Projects

Avocado Machine Learning Project Python for Price Prediction
In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.

Learn How to Build a Linear Regression Model in PyTorch
In this Machine Learning Project, you will learn how to build a simple linear regression model in PyTorch to predict the number of days subscribed.

AWS MLOps Project for ARCH and GARCH Time Series Models
Build and deploy ARCH and GARCH time series forecasting models in Python on AWS .

Deep Learning Project for Text Detection in Images using Python
CV2 Text Detection Code for Images using Python -Build a CRNN deep learning model to predict the single-line text in a given image.

Multilabel Classification Project for Predicting Shipment Modes
Multilabel Classification Project to build a machine learning model that predicts the appropriate mode of transport for each shipment, using a transport dataset with 2000 unique products. The project explores and compares four different approaches to multilabel classification, including naive independent models, classifier chains, natively multilabel models, and multilabel to multiclass approaches.

Personalized Medicine: Redefining Cancer Treatment
In this Personalized Medicine Machine Learning Project you will learn to classify genetic mutations on the basis of medical literature into 9 classes.

Azure Deep Learning-Deploy RNN CNN models for TimeSeries
In this Azure MLOps Project, you will learn to perform docker-based deployment of RNN and CNN Models for Time Series Forecasting on Azure Cloud.

Build a Hybrid Recommender System in Python using LightFM
In this Recommender System project, you will build a hybrid recommender system in Python using LightFM .

Build a Similar Images Finder with Python, Keras, and Tensorflow
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.

Credit Card Default Prediction using Machine learning techniques
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.