Data Scientist vs Data Analyst

September 26: From the early days of human civilization, the most important decisions are based on “Gut-feeling”. Many researches show that gut-feeling can be useful, especially in highly uncertain circumstances and with limited data.

In current days, many decision makers, senior executive pride themselves on relying on gut-feeling, a strong intuition, for making important decisions

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The concept of gut-feeling or intuition has been quoted as the key for many scientific and business successes.  As said by Albert Einstein “The intuitive mind is a sacred gift” and by Steve Jobs “Have the courage to follow your heart and intuition; they somehow already know what you want to become”.

While gut-feeling can provide a spark or a hunch based on intuition and experience, it’s the data that provides insights, which we can verify, analyse and understand in a quantitative way. The method of analysing data and extracting insights to provide quantifiable inputs for decision making has gained significant importance in recent years.

This demand for analysing data and extracting insights has led to popularity of domains such as data science, analytics etc., and created huge demand for many new roles including data scientist and data analyst.

What does a data scientist do?

A data scientist is an all-rounder, who performs the entire gamut of tasks from gathering data, preparing data, looking for patterns to creating data models, algorithms for predictive analytics. Data scientist's goal is to provide advanced insights to businesses for decision making.

Data scientists use statistics, mathematics, programming, machine learning algorithms to understand the data and solve complex problems. They exercise a great deal of analytical skills, creativity and innovative ideas in their work. 

They possess  good communication and collaboration skills, as they often work with many stakeholders both internal and external to the business, such as data engineers, data administrators, architects, customers, subject matter experts, business leaders etc.,

What does a data analyst do?

A data analyst’s main goal is to interpret the data and help businesses in understanding the data and insights from a business perspective.

Data analysts use statistical techniques to extract business insights from data. They also create reports, visualisations and dashboards in the process of presenting data in an informative manner so that other business users can interpret and use insights in their work.

Data analysts have a strong understanding of the business, which helps them to interpret the data and answer complex questions related not only to the business operations but also the projects and future business prospects. 

Data Science vs Data Analyst: Skills

Data Analysts:

• Good business understanding
• Strong knowledge in data tools  such as advanced Excel
• Database knowledge and SQL to gather the data.
• Descriptive statistics techniques to extract insights from data.
• Business Intelligence tools such as Tableau, Power BI, et.,
• Statistical techniques for clustering, forecasting (ARIMA), etc.,

Data Scientists:

• Strong data preparation skills as more than 50% of the data scientists are to clean and transform the data.
• Essential Statistics for descriptive analysis and data transformation
• Programing skills with Python/R 
• Data mining techniques
• Knowledge of Big Data platforms such as Hadoop, Spark etc.,
• Machine Learning modelling for creating predictive models such as regression, classification clustering with various ML algorithms, Random Forest, Logistic regression, KNN, SVM, ANN etc.,
• Knowledge of productioning the models to make is available to business users

How To Become a Data Analyst?

It typically takes about 4-5 months as a full time learner to gain market ready skills to become a data analyst. High level steps as below.

1. Choose the right structured program to learn skills required for a Data Analyst role.
2. The program could be a full-time degree course in universities or a certification course for Data Analyst through a reputed institution based on your requirements.
3. The program should cover key topics including  statistics, mathematics, data analysis and business intelligence.
4. Do projects and learn to contribute to business outcomes through data analysis.
5. Take up an internship as a Data Analyst to work on live projects and appreciate the value addition to business through data analysis.
6. Apply for Data Analyst jobs and start your career as a Data Analyst.

How To Become a Data Scientist?

It typically takes about 6-8 months as a full time learner to gain market ready skills to become a data scientist. High level steps as below.

1. Choose the right structured program required for a Data Scientist role. 
2. The program could be a full-time degree course in universities or a certification course for Data Science through a reputed institution based on your requirements. 
3. The program should cover key topics including  programming-Python, SQL, Statistics, Mathematics, Machine Learning and Big Data.
4. Practice several end-end projects and compete in hackathons and kaggle competitions.
5. Take up an internship as a Data Scientist and work on live projects based on ML predictive modelling. 
6. Apply for Data Scientist jobs and start your career as a Data Scientist.

Data Science vs Data Analyst: Which is right for you?

If you are a beginner and want to pursue a career in data related domain, both Data Scientist and Data Analyst are good choices. 

Data Analyst is a good choice for you,  if you desire to pursue a career with a non-coding domain as data analyst roles usually don’t involve programming as it uses data tools and statistics to analyse structured data for insights. The learning curve is relatively smaller as compared to Data Scientist.

Data Science is a good choice for you, if you desire to pursue a career with advanced analytics involving complex unstructured data, involving programming and machine learning modelling for predictive analytics. 

You can also start your career as a data analyst role and eventually move on to become a data scientist in a few years down the road. The experience you gained as a data analyst can be immensely helpful to become a good data scientist and fast-track your career thereon. 

DataMites offers flagship courses Certified Data Scientist and Certified Data Analyst, comprehensive job-oriented certification courses for Data Scientist and Data Analyst roles respectively. Both these courses are accredited by International Institute of Business Analytics Certification - IABAC®, and internally reputed as top rated courses with the largest alumni network of more than 25,000 learners.  Contact DataMites for more information.

 

 

 

 

 

(Above mentioned article is a Consumer connect initiative, This article does not have journalistic/editorial involvement of IDPL, and IDPL claims no responsibility whatsoever)