Revology Analytics

AI/ML is not the ultimate solution for every data-related problem. We must first set up foundational descriptive and diagnostic analytics capabilities and more straightforward ML approaches before applying more advanced techniques.

It's essential to understand the business problems and work closely with functional partners to solve them in a way that aligns well with the company's analytical readiness and operating rhythm.

Beyond the Hype: Practical Revenue Growth Analytics Use Cases that Drive Impact — Revology Analytics AI/ML is not the ultimate solution for every data-related problem. We must first set up foundational descriptive and diagnostic analytics capabilities and more straightforward ML approaches before applying more advanced techniques. It's essential to understand the business problems and work closely

It often amuses me that in the era of ChatGPT (and despite the countless books I have in my library on AI/ML), I've never used any Deep Learning model for any of my client engagements or prior advanced analytics leadership roles.

If you need to use Machine Learning, keep it simple! — Revology Analytics It often amuses me that in the era of ChatGPT (and despite the countless books I have in my library on AI/ML), I've never used any Deep Learning model for any of my client engagements or prior advanced analytics leadership roles. For 99.95% of data problems in traditional (non-tech) companies, De

Today’s Data Scientist is Tomorrow’s (well-paid) Business Analyst!

Side note: let’s not call it Data Science anymore…

Today’s Data Scientist is Tomorrow’s (well-paid) Business Analyst — Revology Analytics Data science is an ever-evolving field, and its roles are also changing. As businesses increasingly rely on data to inform their decisions, there is a growing need for people with both the technical skills and domain/industry expertise to drive measurable value.

If you're interested in Machine Learning and data science, don't limit yourself to reading articles, or watching videos & tutorials. Instead, take the initiative to start building your skills today.

Become proficient in SQL, Python, or R to help you get started then spend the nights & weekends working with real data.