There are several data forecasting software tools available in the market that can help businesses analyze historical data and make predictions about future trends. Here are a few popular data forecasting software options:

1. Tableau: Tableau is a widely used data visualization and business intelligence tool that also offers forecasting capabilities. It allows users to analyze historical data, create visualizations, and apply forecasting models to predict future outcomes.
2. IBM Watson Studio: IBM Watson Studio is a comprehensive data science platform that provides various tools for data analysis and predictive modeling. It offers advanced forecasting techniques and allows users to build and deploy predictive models using machine learning algorithms.
3. SAS Forecast Server: SAS Forecast Server is a part of the SAS Analytics platform and is specifically designed for forecasting and demand planning. It provides a wide range of forecasting techniques, automated model selection, and advanced data exploration features.
4. RapidMiner: RapidMiner is a predictive analytics platform that offers data preparation, modeling, and evaluation capabilities. It provides a visual interface for building forecasting models using machine learning algorithms and supports time series analysis.
5. Microsoft Excel: Although not strictly a dedicated forecasting software, Microsoft Excel includes built-in forecasting functions and tools that can be used for basic forecasting tasks. It is widely accessible and can be a good option for simple forecasting needs.
6. Alteryx: Alteryx is a data preparation and analytics platform that offers forecasting capabilities. It provides drag-and-drop tools for data blending, predictive modeling, and time series forecasting.
7. Forecast Pro: Forecast Pro is a specialized software for forecasting and demand planning. It offers a range of statistical forecasting methods, automatic model selection, and advanced analytics features.

When selecting a data forecasting software, consider factors such as the complexity of your data, the level of expertise required to operate the software, integration capabilities with other systems, and the specific forecasting techniques and features that are important to your business.