5 traits of great Data Analysts

The role of the data analyst sits at the heart of digital transformation. Businesses are flooded with information, but they need people who can translate data into decisions, especially in an AI-first world. Demand for data analysts who can work across digital tools, platforms, and AI-driven systems continues to surge. If you want to stand out, these are the skills that matter most now:

Be organised and outcome-focused

Great analysts think in roadmaps, not just reports. In a digital landscape where speed matters, sloppy data practices slow everything down. Good data analysts should be able to easily explain and justify every decision they make, based on the cold, hard facts of the data they have gathered and interpreted. You can have as much acumen as you like, but without the ability to put together a comprehensive data strategy, which explains to your c-suite what the outcome of this information could be, you can easily struggle.

Build clean workflows, document your logic, and tie every insight to a business result.

Be a translator (Especially in an AI World)

Analysing data is a complex role and, as the expert in the team, you should expect to field a range of questions from your colleagues to help them understand the work you do. You don’t just analyse data, you bridge the gap between AI outputs, stakeholders, and strategy. Expect to interpret machine learning predictions, troubleshoot LLM hallucinations, and explain it all in plain English.

Take the time to answer their questions and explain how you gathered and interpreted all of the relevant data.

Be curiously humble

Digital tools and AI can be wrong, and so can you. To some degree, this goes hand in hand with being approachable. No matter how obvious the answers may seem to you, not everyone has the same level of data analysis skills and understanding.

Always challenge assumptions, stress-test models, and welcome feedback. Rigour is more valuable than bravado.

Be fearless with data tools

Although you may be an expert at the platforms, languages, or software, embrace the unfamiliar. From dbt to DuckDB, CRM to Social, Power BI to Python, or prompting GenAI tools like ChatGPT for analysis, you need to adapt fast. Since finding correlations and causal relationships should be your strength, you should have an innate curiosity about the company and its functions, which will help you interpret intriguing data.­

No single platform is enough anymore. Stay tool-agnostic and digitally fluent.

Be human in a digital-first world

AI can process, but it can’t contextualise. You bring the empathy, business understanding, and judgment that tech can’t replicate. The best data analysts will have a head for big data and be willing to get their hands dirty.

Data is digital, but insight is still human.