Data Experts Discover These Less Talked About Data Analyst Skills

by Priya Dialani

April 20, 2021

The skills of a data analyst go beyond simple data cleaning.

In today’s digital culture, what is quickly created on a daily basis is data. Therefore, let’s accept that data is ubiquitous. Many organizations have already started to harness the power of data and have leveraged data insights to their advantage. If you don’t use data analytics, you’re probably left behind. Therefore, the demand for data analysts is also increasing. But have you ever wondered what the skills of a data analyst are?

You probably know the skills required to become a data analyst, but do you know the extraordinary key skills of a data analyst? So much information on the web speaks to the skills necessary for data analysts, such as programming, data collection, data cleansing, and data processing to draw meaningful conclusions. These, of course, are necessary, but we’ll talk about the less talked about skills of a data analyst.

Although the skills mentioned above overlap somewhat with the skills and responsibilities of a data scientist, many people are confused between a data scientist and a data analyst. But to make a clear distinction for you, data scientists need to have a solid foundation in math and statistics, as well as business acumen. On the other hand, for professional data analyst skills you need a moderate level of math and statistics and coding skills.

Let’s dive into the less talked about skills of a data analyst.


While the core skills of data analysts are collecting, cleaning, and extracting information from data, the most effective data analysts can tell a story using the data. To provide a meaningful report, the best analysts will first see significant trends in the data. At a very basic level, data is used to find information and infer trends that organizations use to recommend to their customers. Constant reports, such as weekly or monthly, can help a data analyst identify key patterns in the data. All of these patterns, when accumulated together, can represent a trend over time.

Fast encoders

While the best data analyst skills include coding, the most effective data analysts are those who code extremely quickly. Thanks to this, they can surf huge datasets quickly, mining information faster than any other specialist.

This quick insight can help businesses act quickly on the things they need and drop the less important ones. Decision makers can quickly send such information to ML engineers, saving them a lot of time on tedious and mathematically impressive digs.


Good communication is definitely one of the skills required to become a data analyst. Still, did you know that data analysts have to collaborate a lot with other team members for effective data management and processing?

Data analysts process a lot of data every day. However, not all data is perfect and of good quality. Some data has a lot of holes. In such a situation, data analysts have two options: either continue to search for additional data or create artificial information to fill in the data gaps.

The best data analysts will work with other team members, such as a machine learning engineer or a data engineer, to gain more insight. Most of the time, data analysts can analyze the data on their own, but huge data sets are beyond their capabilities. Therefore, for large datasets, machine learning processes are required to process and analyze them. This often requires data analysts to collaborate with other team members. They help create algorithms based on their AI or machine learning experience and the data analysis expertise of the analyst.

Data analysts are key decision makers

If you’re wondering what the good of CEOs and CTOs are if data analysts are key decision makers, read on to get your answer. With so many essential skills for data analysts, people tend to overlook the core responsibility of a data analyst. They’re there to tell you what’s in your data, which is then explained by a statistician to your business executives.

To help you better understand, machine learning engineers essentially feed data to algorithms, run them, and repeat this until the appropriate results are produced. But machine learning engineers can’t see the information hidden in the data. Without insights, are algorithms still successful? This is where a data analyst comes in. They help ML experts and specialists see and tell them what’s in the data and what issues need to be addressed. If the data is summarized by a data analyst, half the work of making a decision based on the data is already done. Therefore, they play an important role in decision making.

Did you know any of these skills of a data analyst before? It’s time to hire more data analysts as they can be the possible solution to any problem just like the last piece of the puzzle that completes the whole structure of the puzzle.

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Sean N. Ayres