Top practical skills for a data professional

In today’s job market, there are a lot of skillsets to have and it is easy to feel overwhelmed. I recently know someone who was hiring and when I asked what skillsets they were looking for, they replied “everything” (yes, that is exactly what they said). Whereas I understand their response, I do not necessarily agree you need to know “everything” to be a star employee.

During my 7 years of experience in the data field, here are the top key skillsets you will need as a data professional:

SQL

SQL is the bread and data of data analytics. This is the tool that helps you query the data source. There are many variations of SQL but essentially, all variations are meant to allow you extract the data from where it is stored.

Python

Python is the language that will help you work the magic with your data. With its extensive libraries like Numpy and Pandas, an aspiring data professional is able to derive key insights from the data. Python is also relatively low cost and easy to learn for an entry-level data analyst.

Statistics

Statistics is what enables you to deliver accurate and key numerical metrics about your data. Having a statistical background will help you form the necessary hypotheses (null and alternate) for your analytics project. Having the correct hypothesis allows you to collect the correct sample data, build the right models, and test your models for significance.

Visualization

Today there are plenty of visualization tools but some of the popular ones are Tableau and PowerBI. These are the tools that are going to help you communicate your insights to your technical and non-technical business stakeholders. With the ability to create charts, maps, trendlines, a data analyst will be able to convey a message in a language that is direct and easy to understand.