Data Career Skills Audit

We equip you with top tech skills and launch bold careers in data, software, AI, cybersecurity, and more.

Assess if your organization is ready for a data-driven future. Check each item that applies. Click Here!

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Find out where you are and what you need to thrive in the data industry. Check each item that applies.

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1. Career Clarity & Domain Awareness

I understand the difference between Data Analyst, Data Engineer, Data Scientist, and BI Developer. I know which career path I want to pursue in the data field. I’m familiar with real-world applications of data in sectors like finance, health, logistics, or agriculture. I’ve explored job descriptions and qualifications for data roles in Kenya and globally.

2. Technical Skills

I can write SQL queries, JOIN tables, and use aggregation. I can analyze data with pivot tables, formulas, and charts in Excel. I can use basic libraries in Python or R (e.g., Pandas, NumPy, ggplot). I’ve built dashboards using Power BI, Tableau, or Looker. I know how to handle missing values, outliers, and duplicates. I’m familiar with tools like BigQuery, Snowflake, or AWS S3. I use Git to track project changes or collaborate with others.

3. Data Engineering & Workflow Tools (Optional but Valuable)

I understand ETL/ELT concepts and tools (e.g., Airflow, dbt). I’ve worked with both structured and unstructured data. I can build or understand a basic data pipeline. I’ve used or plan to use Databricks, Redshift, or Azure Data Factory.

4. Analytical & Statistical Thinking

I can choose the right chart type to tell a story with data. I know basic stats: mean, median, standard deviation, correlation. I can use A/B testing or hypothesis testing frameworks. I’m confident interpreting trends, distributions, and outliers in datasets.

5. Professional Skills & Portfolio

I’ve created at least 1 real-world data project or portfolio item. I can explain my work in simple language (data storytelling). I’m familiar with GitHub, Kaggle, or Tableau Public for sharing work. I have a data-oriented LinkedIn profile or CV.

Score Summary

Score: 0/40

33–40: Data-Career Ready – You’re job-ready or nearly there.
24–32: Emerging Talent – Great foundation; strengthen your gaps.
15–23: Learning Stage – Build your portfolio and technical range.
0–14: Beginner – Start with foundational training and hands-on projects.

Your Next Step: Enroll in a path-aligned course. Whether you want to be a Data Analyst, Data Engineer, or Data Modeller, we’ll match you with the right learning path.

Click here to explore our Free Career Roadmap and start your journey.

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