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Advanced analytics is helpful in reforming and enhancing the business techniques. Advanced analytics is the process of reviewing data by independent or dependent means using sophisticated tools to produce deeper insights and solutions for better business practices. The advanced analytic techniques include data mining, pattern matching, forecasting, sentiment analysis, machine learning, network and cluster analysis, simulation and neural networks. These techniques analyses every data in depth and delivers results which culminate in the business intelligence process. Advanced analytics differ from business analytics in their purpose.

A business analytic technique focuses on understanding the process and the relationships between different factors. These will help in building a predictive model which will optimize the procedure to find the best choice. The advanced analytics techniques can be classified into:

  • Descriptive Analysis

  • Predictive Analysis

  • Simulation and Optimization

These three techniques differ on their execution but in common directs at extensive research to find the most suitable strategy for best results.The traditional analytical tools consist of researching the past data for performance analysis, the modern business analytical tools allow businesses to predict results and forecast future events. Big data analytics and location intelligence are the latest development of advanced business analytics. The business analytical tools are easily approachable by even a normal user and do not require any complex team of technicians for execution. These tools produce potentially important information from idle data which aid in business decision making. Advanced analytics serve more as a troubleshooter, identifying the problems and providing satisfying solutions.


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