Why do we continue to struggle with data? With all the powerful tools we have in processing power, data tools, and computer programming, we still search for some elusive truth to pervasive problems. AI hallucinates, 'good data' that we started with is suddenly unintelligible, systems that should talk to each other seamlessly continually experience errors and need correction.

What we fail to incorporate into our data world is the fact that data is language and has entwined in that language its own code that does not get captured in databases, APIs, LLMs and the systems we use day in and day out. So, how can we crack this data code?

By stepping back, we can incorporate the tools that already exist in applied linguistics used to crack the human language code into our approaches in how we tackle the data code challenge. Just because we call it data doesn't mean that it doesn't suffer from bias or the need for context. But by recognizing these linguistic challenges, and infusing that inside the data, we can create data code that can be cracked, data that tells us its biases, context, and purpose, and for who that data is actually useful to, and for whom it is not.

If you are interested in data, and why understanding language and jargon can help you crack the data code, this book is for you. If you've had a data challenge and have struggled to find a way to understand it, the practical foundational principles inside can help you frame your problem in a different way. And in doing so, help you crack the data code.