This group session is about how you can transition from a non-tech domain to a tech domain as a data analyst. Transitioning from a non-tech background to a tech domain as a data analyst requires a combination of technical expertise, networking, leveraging domain knowledge, building a portfolio, and a commitment to lifelong learning. I will discuss how you can employ these strategies and considerations to successfully make the shift and embark on a rewarding career in the tech industry.

Key Takeaways from the Session

• The strategies and considerations involved in transitioning from a non-tech domain to a tech domain as a data analyst.
• The importance of developing technical expertise in areas relevant to data analysis, such as programming languages (e.g., Python, R, SQL), statistical analysis, data visualization, and machine learning.
• The value of networking and building connections within the tech industry, including attending industry events, joining professional associations, and leveraging online platforms for networking opportunities.
• How to leverage domain knowledge gained from their non-tech background to their advantage in the tech domain, recognizing the unique insights they can bring to data analysis in specific industries.
• The significance of building a portfolio that showcases their data analysis skills and projects, highlighting their abilities to handle real-world data problems and providing tangible evidence of their competence.

About Me:

• I am a Senior Data Analyst at Integreon with 4+ years of experience in the industry
• I aim to build a strong mentor-mentee relationship that extends beyond the learning process.
• I have expertise in SQL, Excel, Power BI, Data Visualization, Data Analysis, Python, Data Cleansing, data management, Data Modelling, DAX, ETL

Who should attend this Mentorship Session?

• Individuals who are currently working in non-tech domains but are interested in transitioning into the tech industry specifically as data analysts.
• Professionals who have a strong interest in data analysis and want to explore career opportunities in the tech domain.
• Students or recent graduates with a non-tech background who are considering a career in data analysis and want guidance on how to make the transition successfully.