From Data to Insights: Advanced Analytics & ML with Python, R, SQL, VBA & Excel for Real-World Impact

Transform raw data into actionable intelligence. Our data into actionable intelligence articles (with codes) offer practical techniques and real-world examples of advanced data analysis and machine learning using Python, R, SQL, VBA, and Excel. Ideal for Analytics Specialists, Analytics Engineers, Business Analysts, Data Analysts, Data Scientists, Data Engineers, Machine Learning Engineers, and Applied Researchers seeking to drive impactful results. Subscribe for hands-on learning!

New data into actionable intelligence articles (with codes) are included weekly. Sign up / Subscribe to get access to all articles.

The latest articles in this subscription are:

Article 183 : Multiple Linear Regression in Financial Investment Analysis Using SQL: Modeling Asset Returns with Market and Economic Factors

This article explains how investors and analysts can leverage SQL-driven multiple linear regression to model asset returns, quantify factor exposures, and support rigorous, data-driven investment decisions.

Article 182 : Multiple Linear Regression in Financial Investment Analysis Using VBA: A Step-by-Step Guide to Modeling Asset Returns in Excel

This article demonstrates how multiple linear regression, automated with VBA in Excel, enables investors and analysts to model asset returns, evaluate risk factors, and support informed investment decisions through transparent, data-driven analysis.

Article 181 : Linear Regression for Actuarial Science and Risk Analysis Using Python: A Complete Guide to Modeling Insurance Claims

This article explains how actuaries and risk professionals can use Python-based linear regression to model insurance claims, develop rating structures, and support transparent, data-driven decisions for pricing, reserving, and portfolio management.

Article 180 : Linear Regression in Actuarial Science and Risk Analysis Using SQL: Practical Methods for Modeling Insurance Claims Data

This article demonstrates how SQL-based linear regression enables actuaries and risk professionals to model claims, quantify insurance risk, and support robust, data-driven pricing, reserving, and portfolio management.

Article 179 : Linear Regression in Actuarial Science and Risk Analysis Using VBA: An End-to-End Guide to Modeling Insurance Risk in Excel

This article details how linear regression, automated with VBA in Excel, enables actuaries and risk analysts to model claim costs, quantify insurance risk, and deliver transparent, data-driven insights for pricing, reserving, and risk management.

Disclaimer

The information contained within these articles is strictly for educational purposes. If you wish to apply ideas contained in these articles, you are taking full responsibility for your actions. The author has made every effort to ensure the accuracy of the information within these articles was correct at time of publication. The author does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause.