Normally with data analytics, we look to historical data to make sense of what has happened in the past. Whether production reports for lending or reviewing branch traffic, these reports can then be used to estimate budgets, goals and staff requirements for the future. But what if your data and reporting tool could do that for you? That is quickly becoming a reality with predictive analytics. With the improvement in analytical tools, predictive analytics is quickly becoming a standard feature. Below are a few of the current market products that offer predictive analytics natively in the application.
Looker:
Looker is a business intelligence (BI) and data analytics platform that helps organizations explore, analyze and visualize their data. It allows users to create dashboards, reports and custom data visualizations to make more informed, data-driven decisions. This tool is designed to work with Google Cloud and is the preferred analytics tool for their platform.
For Looker, the term it uses for predictive analytics is forecasting. The platform leverages the ARIMA algorithm to generate the forecast and can be used in both graphical visualizations and tables. Two valuable components of Looker are Prediction Interval and Seasonality. Prediction Interval allows a confidence interval in your data that accounts for uncertainty and adds to your accuracy of forecasting. Seasonality accounts for cyclical or repetitive trends to assist with forecasting. This can be especially helpful when looking at hourly transactional data.
Power BI:
Power BI is a business intelligence (BI) and data visualization tool developed by Microsoft. It helps organizations analyze data, create interactive reports and share insights across teams.
Power BI has a forecasting feature built directly into its line graph visualization. This feature allows you to change your forecast by using forecast length, confidence intervals and seasonality. An added function specific to Power BI allows users to adjust for outliers in their data. This enables users to fine-tune their data to a more accurate forecast.
Regardless of the product that you leverage for predictive analytics, it is safe to say that this feature will only continue to grow and become an integral part of your data strategy.