Predictive analytics is a technique that analyses historical data and current data in order to create predictive models and actionable insights for business. These predictive models are able to forecast business outcomes based on patterns of behavior found within a company’s big data. But what is predictive analytics’ purpose, and what is its full potential?
There are many advantages to using predictive analytics as opposed to descriptive analytics techniques. One main advantage is its ability to extract real-time insights from historical data and new data. The software’s predictions about future outcomes also come with high levels of confidence. Using a predictive model allows you the ability to make better decisions in your business processes by laying out informed predictions for future events.
Descriptive analytics simply interpret large data sets, it doesn’t provide any actionable insights for possible scenarios based on any particular set of conditions that can be extracted from past data. Descriptive models do little to advance business intelligence and decision making compared to predictive models that involve deep learning and insights for solving your business problems. TIBCO’s predictive analytics are also capable of predicting potential business problems and market behaviors from your data sources. With their predictive analytics tools, you can avoid different variables that may negatively affect your business’ output and profits.
Which predictive analytics software should I use?
TIBCO is an enterprise solutions company whose elite predictive analytics software combines statistical analysis and machine learning to make predictions that can help you optimise your business processes. Their predictive analytics take advantage of technological advancements in artificial intelligence capabilities in order to efficiently extract insights and create an accurate forecast for business managers. TIBCO offers several forms of business intelligence solutions, but its predictive analytics software specifically implements advanced data science and analytics techniques.
TIBCO’s predictive analytics software integrates the entirety of a business’ data sources to create a real-time estimate from both new data and past data. Its predictive analytics techniques allow for more accurate forecasts than the typical descriptive models that are the industry standard.
Potential applications of predictive analytics
TIBCO’s predictive analytics have applications that span several different industries. Beyond forecasting future events to improve decision making and increase profits, predictive models’ actionable insights can be applied to more specific business problems. Its predictive analytics model promotes optimisation in marketing campaigns and customer service by creating algorithms based on your demographics and customer behavior. Some common predictive analytics applications for customer service include neural networks and decision trees that visually map out decisions and consequences in relation to marketing campaigns and customer experiences. Not only does TIBCO create predictive analytics models that optimise your output, but it can also help you make better-informed decisions on testing additional products and choosing potential vendors.
The use of predictive analytics is also crucial in business users’ financial services. TIBCO uses data modeling insights to predict fraud and identity theft, and it can detect anomalies in transaction data. This anomaly detection also allows you to perform preemptive maintenance to avoid future setbacks that can affect output. TIBCO’s machine learning and data collection use trade and account surveillance to create algorithms that improve the value in your companies software and its ability to avoid future threats.
By applying predictive analysis to your business operations you will see an increase in decision making speed and positive outcomes. The artificial intelligence and algorithms can also automatically generate new revenue streams for business users while simultaneously lowering the costs of business operations. Predictive analytics application is essential for processing large data sets compiled from internal and external data sources.