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5 Critical Best Practices for a Data Analyst

If you have decided to begin a career in Data Analytics, by all counts you really have made a good decision. You can look forward to a job that’s is going to be far from boring. Infact get ready to be challenged, as you work on multiple projects that will not only sharpen your skills, but will give you an edge in today’s volatile, highly competitive business environment.

To really succeed however, here are 5 critical best practices, that if followed will help you become a methodical, successful analyst, much in demand in the analytics workspace.

1. It’s all about a well-defined business problem

Ensure that the project you are working on aims to solve a well defined business problem, that if solved will impact the profitability of your organization. It is easy to get lost in data, but remember that even if you are having fun exploring data that is giving you some awesome insights, unless it answers the defined problem, it won’t really help solve anything.

2. External Data is important as well

It is often easy to overlook external data, and one of the most common mistakes data analysts make is assuming they can find all answers just with internal data. Take the time to explore what external data can be relevant and use it. This will give you more valid variables and make your analysis more interesting, actionable and give you better insights.

3. Remember you are only one link in a chain

Data analysts can often get so absorbed in their analysis that they forget that the key to getting the best insights lies in continuously keeping in touch with other divisions like marketing, finance, HR and operations. You must always keep them in the loop. Don’t negate the importance of their inputs as they are on the ground running and often have critical insights that can add great value to your data.

4. Good insights get lost in poor visualizations

Today there are a variety of excellent visualization tools available to help you showcase your insights. However you need to choose your visualization tools carefully and ensure that the tool you have, gives the stories you weaved, a wow factor. There is no better way to convince management of the viability of your insights, than with an impacting, powerful visual.

5. Adhere to security and governance procedures at all times

Data security is a topic of big discussion today and there are some very strict laws and guidelines that you must ensure you are aware of and that you conform to at every stage of the data analysis. Don’t risk all you analysis getting thrown out, just because you did not know of a certain rule or you did not adhere to a certain procedure.

Image courtesy By jscreationzs

Interested in a career in Data Science?
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Sanchita Lobo

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Sanchita Lobo

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