Nana is a Data Quality Analyst specializing in improving reporting reliability and business intelligence. A graduate of Imperial College London, he has hands-on experience with Power BI, AWS Glue, and PySpark. He holds a Databricks Lakehouse Fundamentals certification, underscoring his expertise in modern data platforms.
Based on his early career and company interests, he appears to maintain a keen interest in the pharmaceutical and consumer goods industries. He also actively engages with his professional community, as seen by his participation in industry events.
Nana successfully transitioned his career from analytical chemistry and quality control roles in the life sciences sector to data analytics.
Read the full overview →They don’t appreciate bells and whistles unless backed by data. They like to do things independently and don’t look for support from others. They choose to analyze logically and value facts to emotions.
Calculativeness (C) reflects the degree to which a person is likely to be cautious, systematic and analytical. Those scoring high tend to emphasise quality and accuracy.
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