Jaspersoft, the company that hosts the information mentioned below, empowers people around the world every day to make better decisions faster by bringing them timely, actionable data inside their apps and business processes through an embeddable, cost effective reporting and analytics platform. Given the expertise in the field, the relative webpage provides the essential backgroud on advanced analytics.

In brief, advanced analytics employs predictive modeling, statistical methods, machine learning and process automation techniques beyond the capacities of traditional business intelligence (BI) tools to analyze data or business information.

Indeed, while basic BI and analytics can provide a snapshot of the business, advanced analytics provides the ability to forecast future trends or outcomes for a deeper understanding of the business. Advanced analytics offers a wider set of capabilities to deal with challenges that traditional rearview BI can not, enabling stronger strategic decision making for the future.

Why Is Advanced Analytics So Important Today?

With huge amounts of data being generated every day, businesses are looking for new ways to take advantage of all that data. Advanced analytics helps companies to do that. It enables companies to optimize their operations and innovate to gain a competitive advantage. With better customer analysis, predictive analytics, and statistical modeling, advanced analytics is helping companies to improve decision making and keep pace with extremely competitive, quick-changing markets. Where traditional analytics and BI tools fail to hold up, advanced analytics positions companies toward future success.

It represents a potential way for many businesses to extract value from their data, whether that be data stored in a data warehouse or real-time data generated by business operations. Businesses that employ advanced analytics tools are able to build upon knowledge discovery to inform the likelihood of future events, providing greater confidence for more repeatable business results.

Some techniques often used with advanced analytics include, among others:

• data mining,
• machine learning,
• data visualization,
• sentiment analysis,
• network and cluster analysis,
• forecasting, pattern matching,
• complex event processing,

All or some of these techniques can be used to explore and model a company’s data to improve the business based upon actionable insights.