Data Analytics Resources
The insurance industry is becoming more competitive and dynamic; our products are becoming more sophisticated. Actuaries must provide better and faster business insights to senior management; regulators and investment analysts require more transparency. Traditional analysis using Excel with intensive manual processes will not be able to meet all these challenges. We cannot just work harder; we must work smarter.
Fortunately, technology has also evolved exponentially. We have computers that can perform up to quadrillions of floating point operations per second and Artificial Intelligence (AI) systems that do "deep learning." Below is a list of data analytics resources that will prove useful when you want to explore beyond traditional Excel analysis. This is only the tip of the iceberg, but it will provide you a large jump start to your quest to provide insights from data analytics to your management.
Note particularly the Open Data Sources section, pointing you to a vast range of external data to bear on your company's strategic needs
Open Data Sources
- US Open Data
- Canada Open Data
- UK Open Data
- US Census Data
- US Health Data
- UK Health Data
- Amazon Public Data
- Factual
- Gapminder World
- Google Trends
- Google Finance
- Microsoft Azure Data Market Place
Business Intelligence
Data Integration
Data Visualization
Advanced Analytics
Database
NoSQL
Programming Tools
Development Platforms
Excel Utilities
- Office 365
- SharePoint Excel Services
- @Risk
- Solver
- Crystal Ball
- Spreadsheet Inquire
- Analysis ToolPak
- VBA Libraries
- Power Pivot
Certification
- Cloudera Certified Administrator for Apache Hadoop
- Cloudera Certified Professional: Data Scientist
- EMC DATA SCIENTIST
- Certified Analytics Professional
Free or Low-Cost Self-Directed and Massive Open Online Courses (MOOCs)
- Khan Academy
- Big Data University with courses on R, Python, SQL, Hadoop, Machine Learning
- Machine Learning course from Stanford
- Process Mining Course from Technische University Eindhoven
- Data Science Specialization Track from John Hopkins
- CalTech JPL post-grad/PhD Summer School on Big Data Analytics (very advanced)
- Python Courses from University of Michigan (Coursera) and MIT (EdX)
- Introduction to Databases course from Stanford
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