3 attitude changes to help you become a better data analyst

by Sumana Bhattacharya

August 19, 2021

Data analysts examine data using data analysis software. By recognizing various facts and patterns, the relevant results they extract from the raw data help their employers or clients make critical decisions. If you are considering a job in data analytics, you will need to embrace these three mindsets to excel as a data analyst.

In your daily life, adopt an analytical attitude

Great data analysts develop fact-based conclusions rather than having a preconceived answer to a topic or problem. This is one of the most essential realities of a data analytics job that you need to understand before deciding to change careers. Choose a discussion on a topic you don’t know much about to practice this attitude. Compile all the relevant and objective facts you can uncover and use them to develop a position in the argument. Better yet, create two opposing arguments based on the same evidence. Compare your ultimate position to any preconceived assumptions you may have had.

Investigate the use of analytics in your industry

Data analysis is not a separate field. Wherever data is collected, analytics can be used and analytical responsibilities differ by industry, department and function. As a result, outstanding data analysts come from a variety of professional backgrounds. Consider your current or planned domain and think about how the data is being used there. You can search for public datasets if you have no preview or access to reports or datasets. Continue your research.

Improve your abilities

Start learning the skills and tools that will make you invaluable to potential employers now that you’ve adopted an analytical mindset and understood the context in which data is used in your business. For starters, data analysts must have a soft skill set to be successful in their jobs. Whatever the industry, communication, organization, project management, leadership and critical thinking are essential. You will also have to master the technical skills required for the job in addition to soft skills. Machine learning, predictive analytics, data visualization, MapReduce, and a broad understanding of big data and data science are some of the most in-demand technical analysis talent.

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Sean N. Ayres