From a Data Scientist to a Data Analyst: 6 Tips to Keep in Mind

The data driven world has led to an increase in the number of data driven jobs across many industries. When it comes to data scientists and data analysts, the roles and skills vary from one workplace to the other.


Differences Between Data Scientists and Data Analysts

While there is no fixed skill test that determines data scientists and analysts, there are some widely accepted notions.

A data scientist usually deals with data handling, visualization and its interpretation so that it best helps businesses make smart decisions. This role requires delivering business insights, data structuring, mining, visualization and analysis, along with good programming knowledge and basics of machine learning. Learn more how to become a data scientist here.

Data analysts summarize data and identify any major patterns that can add value to future inputs. The role consists of collection, cleaning, and arrangement of data, as well as its presentation in easily understandable forms, like charts or graphs. 

6 Tips from a Data Scientist to a Data Analyst

1- Let Your Data Tell a Story

Data is best presented to people with visually appealing charts and interpretations. However, this also includes presenting logical facts that stakeholders can easily understand. This will give the business all details necessary to arrive at a conclusion. Combine data, visualization, and narration to present your insights.

2- Take an Interest in Coding

Coding is the cornerstone when it comes to growing your data science skills. It will open new pathways and opportunities. By the time you face a real problem, you will already be well equipped to deal with it.

3- Gain Domain Expertise

For growth in the data science sphere, it is important to gain domain expertise. This helps you identify which technology to use in different scenarios. This also helps to create domain specific solutions tailored to the latency, bandwidth, and system conditions that the industry specifically uses.

4- Creative Problem Solving

Critical thinking and creative problem solving are crucial skills in the data science field. Simple and out-of-the-box ideas often help you arrive at the solution much quicker. Be open to new perspectives and make decisions to solve problems effectively.

5- Learn New Skills

Honing your skills will keep you relevant in the field. Along with constantly brushing up on skills you are familiar with, make it a point to learn new skills whenever possible. This will facilitate easy shifting to new job roles and will open new doors. 

6- Maths and Statistics

Data based decisions rely heavily on numbers, probability, and statistics. Having a strong grasp over them allows you to have an upper hand. Once the basic concepts are clear, you can make models and tools designed to optimize your solutions. 


These tips will undoubtedly help you to progress in data science and develop better solutions to complex problems. A data scientist or analyst should always be prepared to take in new information and use it to the best of their ability. With data being the most important resource for most industries, this is a career path that has a lot of opportunities, and these tips will help you get ahead. 


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