Keeping up with the latest tools is important, with AI-powered options being the latest development in making it easier for non-technical analysts to access powerful data-derived insights. AI is taking root in the life of the analyst in three main domains:
1. Improving popular analytical software products and packages: We will continue to see more AI-powered features integrated into popular BI packages liked Excel, Tableau and Power BI
2. Extending the power of computing languages: More powerful AI-driven modules are now available for integration into scripts written in data-centric languages like R, Python Pandas and SQL
3. Harnessing LLMs to write queries: The average non-technical, non-coder analyst or business intelligence specialist can now ask large language models to write code that can answer questions about one’s own data
As these new tools and techniques continue to make life easier for analysts and non-analysts alike, one thing that will not change is the importance of knowing how to ask questions of one’s data. Having a solid grounding in subject matter expertise in one or more areas of the real world (e.g., marketing, operations, geo-engineering, logistics, education, business systems, etc.) remains a requirement for success.
