Snowflake Cortex is a suite of Machine Learning (ML) and Artificial Intelligence (AI) capabilities letting businesses leverage the power of computing on their data. The machine learning functions like FORECAST, TOP_INSIGHTS and ANOMALY_DETECTION allows access to the leading large language models (LLMs) for working on both structured and unstructured data through SQL statements. Using these functions, data/business analysts can produce estimations, and recommendations and identify abnormalities within their data without knowing Python or other programming languages and without an understanding of building large language models.
FORECAST: SNOWFLAKE.ML.FORECASTfunction enables businesses to forecast the metrics based on historical performance. You can use these functions to forecast future demand, Pipeline gen, sales, and revenue over a period.ANOMALY_DETECTION:SNOWFLAKE.ML.ANOMALY_DETECTIONfunction helps flag outliers based on both unsupervised and supervised learning models. These functions can be used to identify the spikes in your key performance indicators and track the abnormal trends.TOP_INSIGHTS: SNOWFLAKE.ML.TOP_INSIGHTSfunction enables the analysts to root cause the significant contributors to a particular metric of interest. This can help you track the drivers like demand channels driving your sales, and agents dragging your customer satisfaction down.
In this article, I will focus on exploring the FORECAST function to implement the time series forecast model to estimate the sales for a superstore based on the historical sales.