7 REASONS YOU SHOULD NOT BECOME A DATA ANALYST | LET'S BE REAL... | CAREER LIFE | Ohema Nae

Summary

This video outlines seven reasons one might consider avoiding a career as a data analyst. The speaker, a data analyst herself, discusses the need for patience in coordinating with others for data, the frustration of coding, dealing with imperfect data, managing expectations and de-escalating conflicts, enjoying data and interpersonal skills, resourcefulness in problem-solving, and the necessity to be a quick learner in adapting to new tools and processes. It highlights the challenges of the role while candidly sharing personal experiences.

Takeaways

• 🧑‍💼 Data analysts often need to 'babysit' team members to ensure they receive necessary data on time, which can be frustrating and time-consuming.
• 🕒 Patience is crucial for data analysts, as they must deal with delays and issues in data collection and processing.
• 🔍 Data analysts must be detail-oriented and able to identify and address data discrepancies and issues in the data they work with.
• 🤝 Strong communication skills are essential for data analysts, as they need to interact with various teams and stakeholders to gather requirements and present findings.
• 😡 De-escalating tense situations is a skill data analysts should have, as they may encounter frustrated stakeholders due to data or dashboard issues.
• 💻 Data analysts should enjoy working with data and people, as their role involves both technical analysis and interpersonal communication.
• 🔑 Resourcefulness is key for data analysts, as they often need to find solutions and answers independently, especially when under time constraints.
• 👥 Being aware of and navigating corporate politics and 'tussles' is part of the data analyst's role, especially when dealing with multiple teams and data sources.
• 📈 Quick learning and adaptability are important for data analysts, as they need to keep up with changes in tools, processes, and data sources.
• 🛠️ Data analysts must be prepared for manual work and dealing with scattered data from various sources, which requires patience and problem-solving skills.
• 🚫 The video script serves as a cautionary guide, outlining reasons why someone might want to reconsider a career as a data analyst based on the challenges involved.

Q & A

What is the main topic of the video script?

The main topic of the video script is the seven reasons why one should not become a data analyst, as explained by a data analyst.

Why does the speaker mention the need for patience in data analysis?

The speaker mentions the need for patience because data analysis can involve dealing with imperfect data, manual work, and the time-consuming process of troubleshooting issues.

What does the speaker mean by 'babysitting' in the context of data analysis?

In the context of data analysis, 'babysitting' refers to the need to constantly follow up and coordinate with other teams to receive the necessary data to perform one's job.

What challenges does the script highlight regarding the coordination of data from different teams?

The script highlights the challenges of coordinating data from different teams, such as the need to wait for them to send data, the possibility of delays, and the potential for miscommunication or misunderstanding of priorities.

How does the speaker describe the frustration that can come with coding in data analysis?

The speaker describes the frustration with coding as something that can be challenging and time-consuming, requiring patience and persistence to troubleshoot and resolve issues.

What is the importance of de-escalating situations in the context of data analysis?

The importance of de-escalating situations in data analysis is to handle conflicts or frustrations that may arise from data discrepancies, dashboard issues, or miscommunications with stakeholders in a professional manner.

Why does the speaker suggest that enjoying working with data and people is important for a data analyst?

The speaker suggests that enjoying working with data and people is important because a data analyst's role involves not only analyzing data but also communicating with teams, gathering requirements, and presenting findings.

What does the speaker mean by 'corporate tussle' in the context of data analysis?

In the context of data analysis, 'corporate tussle' refers to professional conflicts or disagreements that may arise in a workplace setting, often due to misunderstandings or frustrations with data and dashboards.

How does the speaker emphasize the need for resourcefulness in data analysis?

The speaker emphasizes the need for resourcefulness by explaining that data analysts often have to find answers independently, especially when dealing with new tools, processes, or time constraints.

What is the significance of being a quick learner in the role of a data analyst, according to the script?

The significance of being a quick learner in the role of a data analyst is to adapt to new processes, changes in tools, and to quickly build and analyze data in response to the demands of the job.