Best practices

Increasing customer retention is one of the highest ROI go-to-market activities you can do. Here's a step-by-step guide on creating a churn risk alerting system with SQL, Python, AI and email.

AI is ushering a new era of augmented analytics. Data leaders and executives across industries need to consider how they're using augmented analytics to make better, faster, real-time decisions.

Enterprise analytics consolidates data from across your organization to reveal strategic insights that drive growth. Learn more about how to get started and the role of AI.

Finding and sharing true insights is hard: legacy BI was not designed for deep exploration while data teams struggle to hire a balance of technically proficient and business-savvy individuals. New technology, platforms and AI are changing the game.

A great SQL IDE is a must-have for data practitioners of all levels. In this post, we talk about all the best IDEs, their pros and cons and which to consider based on your needs.

BI and data analytics are close cousins but do have their differences. In this article we explore their definitions and the pros and cons of each to help guide in your decision.

Data cleaning is the first step of making good use of any data. However, it has its challenges. In this post we explore the challenges and best alternatives.