Regression analysis forecasts are forecasts of future events or trends based on historical data. They can be used in many industries such as finance, retail, manufacturing and logistics to help companies better align their plans and decisions. With the Vertex AI, such a regression analysis can be performed based on a tabular data set using a specially created machine learning model. 

The Vertex AI is a holistic machine learning platform on the Google Cloud that enables users to perform forecasting and analysis on large amounts of data – without any programming knowledge. With the Vertex AI, a tabular data set can be automatically trained in a machine learning model and output as an endpoint. The data record can be stored easily and conveniently in a BigQuery database on the Google Cloud.

1. Forecasts in a timeline: Based on the timeline of a tabular data set, you can use the Vertex AI to make a forecast using regression analysis. The timeline data points correspond to the table rows in the tabular data set.
2. Detect anomalies in model monitoring: Another feature of the Vertex AI is anomaly detection, which makes it possible to detect unusual or unexpected changes in the data. This can be useful for early detection and troubleshooting of potential outliers or exceptional trends.
3. Features in the forecast: You can assign feature values ​​with weights to individual table columns of your tabular data set. This calculates in the forecast how much your forecast metric is influenced by another metric. On this basis, you can primarily price in synergy effects.