The Anodot Cost forecasting platform is designed for business analysts and not for data scientists. To handle a large number of forecast tasks with no data science intervention the platform is autonomous, flexible granular, and based on machine learning.
The Forecast platform is, more importantly, accurate. The platform's median monthly accuracy is 98.5%. This is measured by MAPE (mean absolute percentage error), an industry metric that defines the accuracy of a forecasting method.
Forecast in CostGPT
CostGPT is an advanced AI assistant that can help you with a variety of tasks, including forecasting costs and usage in financial operations. This functionality is crucial for businesses looking to manage their cloud expenses efficiently and optimize resource allocation. Below, we’ll guide you through how to use CostGPT to answer queries related to cost and usage-based forecasts for FinOps.
How Anodot's Forecast Helps with Cost and Usage-Based Forecasting using CostGPT
- Data Analysis and Interpretation:
- Anodot analyzes historical usage data and cost patterns to provide insights into future trends.
- It can interpret complex data sets and generate understandable summaries and visualizations.
- Predictive Modeling:
- Using advanced algorithms, Anodot creates predictive models to forecast future costs based on past usage.
- It can consider various factors such as seasonality, growth trends, and upcoming projects.
Cost Forecast
Usage Forecast
Forecast in Budget
Important things to know about the Forecast platform:
- The platform uses the first 85% of the data for training forecast models, and the last 15% of the data as a validation set.
- There are 2177 forecasted metrics.
- The platform removes transient anomalies as a preprocessing step, meaning any errors are not biased by anomalies.