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Table of Contents

  • Introduction
  • Common Advanced Analytics Techniques
  • Use Cases for Advanced Analytics
  • References

Introduction

Advanced analytics is a data analysis methodology that uses predictive modeling, machine learning algorithms, deep learning, business process automation, and other statistical methods to analyze business information from a variety of data sources. Advanced analytics tools both combine and extend prescriptive analytics and predictive analytics while adding various options for enhanced visualization and predictive models. 


By combining consumption models with historical data and artificial intelligence, advanced analytics can help an organization determine precise answers to key questions. It can’t predict the future, but it allows organizations to act more quickly and with a greater degree of confidence about future outcomes. With more accurate predictions, organizations can avoid making costly and risky decisions.


Advanced Analytics uses data science beyond traditional business intelligence (BI) methods to discover deeper insights, make predictions, or generate recommendations. In so doing, it can help address some of the more complex business problems that traditional BI reporting cannot. With better customer analysis, predictive analytics, and statistical modeling, advanced analytics is helping companies to improve decision-making.

Common Advanced Analytics Techniques

There are a number of advanced analytics techniques. For example, one of which is data mining, which is a process that sorts through large data sets to identify patterns and establish relationships to solve problems through data analysis. You also have a technique called sentiment analysis, which uses natural language processing, text analysis, and biometrics to identify the emotional tone behind a body of text. 

Below is a list of some of the common advanced analytics tools.

  • Data Mining
  • Sentiment Analysis
  • Cluster Analysis
  • Complex Event Processing
  • Big Data Analytics
  • Machine Learning
  • Data visualization

Use Cases for Advanced Analytics

Below is a list of some of the common advanced analytics use cases.

  • Supply Chain Optimization
  • Marketing Analytics
  • Risk Analysis
  • Human Resources Analytics
  • Business Operations

References

  • Hanna, Katie Terrell. “What is advanced analytics?” TechTarget, https://www.techtarget.com/searchbusinessanalytics/definition/advanced-analytics. Accessed 8 July 2022.
  • “Definition of Advanced Analytics - IT Glossary.” Gartner, https://www.gartner.com/en/information-technology/glossary/advanced-analytics. Accessed 8 July 2022.
  • “What is Advanced Analytics?” TIBCO Software, https://www.tibco.com/reference-center/what-is-advanced-analytics. Accessed 8 July 2022.
Mensah Alkebu-Lan

About The Author

With 15+ years of experience in designing, developing, and maintaining JVM-based applications, ensuring seamless delivery of various IT projects, and successfully creating and executing software applications. Mensah also possesses strong expertise in leveraging Agile/Scrum methodologies, producing detailed technical documentation, and designing optimal software solutions.