Top 3 Best Practices for Aspiring Data Analysts

The promising profession of Data Analytics has proved out to be extremely competitive yet one of the most practical skills required by project leaders to get meaningful analysis on the fly.

In today’s information age, the ambitious and young talent has the edge over the last generation of data analysts by learning from their mistakes and redefining the best practices for a lucrative launch in this field.

Here are the top 3 mistakes that one can be mindful of during the journey of preparing oneself to become a Data professional.

Stretch your analytical muscles

80/20 rule is universally applicable to every aspect of a profession and project.

Whenever you are exploring those Machine learning models for approaching a given problem, you must realise that the real world is different from academics.

You must take your time to learn about the fundamentals of an industry and the end business goals for the concerned stakeholders.

Relying on credible and complete data

There’s a general rule in the world of Data – rubbish in, rubbish out.

Often, the data analysts are not able to verify the source of the data they are asked to process. And if the given data, reports and insights are second-hand, the entire outcome is of no use to the decision-makers. Therefore, the data must not be redundant or drawn from incomplete sources or based on invalid assumptions.

Therefore, we must ensure to deploy the right processes and data analytics tools to ensure the credibility of the source of the datasets.

Confronting bias judiciously

Always remember, whenever confronting bias, know that intent does not surpass impact.

The analysis could be subjected to bias as it’s nothing less than a product of the subjective experience and knowledge of the users who have shared it.

It is quite possible, that one could unconsciously over-emphasise one aspect of the problem and undermine the other aspects. Therefore, we must consider the fundamentals and deploy the right statistical methods to overcome the element of bias during the process.

Summary

The future of data is observing an aggressive upward trend in terms of opportunities and scalability in any given industry.

It’d be a no-brainer to advance your career by pursuing an Advanced Certification in Data Analytics if you are preparing yourself to solve complex data problems and outperform your counterparts in today’s cut-throat competition to get that professional edge in 2022.