We live in a world with more data than ever before. Data science helps us turn this data into useful insights, but it often requires coding skills that not everyone has. No-code and low-code tools aim to change this by letting people work with data without writing code.
In this post, I’ll explore the evolution of no-code data science, discuss its benefits and pitfalls, and introduce a solution I’m building to simplify data analysis for everyone.
First, let’s define data science. Data science is about finding value in data. Today, we have huge amounts of data and need computers to help us make sense of it. You may have heard the phrase, “data is the new oil.” If that’s true, then we need tools to turn this “oil” into something useful—like turning crude oil into gasoline.
Many people have data and understand their business well. They want to learn from their data, but they may not know how to tell a computer what to do. Usually, this requires programming skills. But not everyone can program, or wants to spend time learning to code, or can afford to hire a programmer.