26 Sep 2022 Data Scientist vs Data Analyst: What is the Difference?
Data Analysts and Data Scientists are some of the most sought after professionals in the world today due to the increasing demand for data experts in various industries.
However, for beginners considering a career in Data, making the distinction between these roles and choosing which to go for often poses a serious challenge. This is because while these roles have many things in common, they also differ greatly from each other.
This article takes a deep dive into the roles and responsibilities of Data Scientists and Data Analysts to help you better understand what these roles entail as well as the differences and similarities that exist between them.
Let’s begin by explaining what Data Science is and Who a Data Scientist is.
What is Data Science?
Data Science involves the extraction of insights from large amounts of data using various scientific methods, algorithms, and processes.
Who is a Data Scientist
A Data Analyst is an expert who is responsible for gathering data to identify trends that help in strategic decision-making. Data Analysts mostly perform statistical analyses to solve problems. In the process of analyzing data, they often clean data and do away with the irrelevant or unusable bits.
Data Analyst vs. Data Scientist: Roles & Responsibilities
Data Scientists are mostly involved with designing data modeling processes, creating algorithms and predictive models.
Unlike their Data Analyst counterparts, a data scientist may be more focused on developing new tools and methods to extract the information the organization requires to solve complex problems.
Meanwhile, Data Analysts work as part of an multidisciplinary team to determine an organization’s goals and then focus on mining, cleaning and analyzing data.
As a Data Analyst, you will:
- Analyze and interpret data related to customers and company processes, including researching areas like customer behavior and purchasing power to help businesses improve.
- Build a data-focused understanding of customer behavior and how to predict what customers want to see and experience.
- Run quantitative analysis to discover inefficiencies and hurdles that hamper projects or initiatives
- Report regularly on business key performance indicators (KPIs) to allow effective monitoring of business performance on a weekly, monthly, quarterly and yearly basis.
As a Data Scientist, you will:
- Use predictive analytics to better understand customer behavior and preferences, ad performance, and other customer-facing metrics to boost revenue.
- Develop algorithms and data models to help improve efficiency, service, and brand reach.
- Create unique A/B testing frameworks and customized tools to monitor business performance
- Analyze new data sources and how it impacts business performance.
Data Scientist vs Data Analyst: The Differences
Having highlighted the roles and responsibilities of Data Scientists and Data Analysts, the table below gives an overview of the differences that exist between both roles.
It is important to mention that the roles and responsibilities of data scientists and data analysts may vary depending on where they work and where the company is sited.
Other job opportunities and roles in Data Analysis
There are also numerous job and career opportunities available to Data experts. For instance, Data Analysts could choose to niche down and focus on a particular specialty.
For example, Database Analyst is a role Data Analysts easily settle in. Database Analysts examine, review and understand data using a wide range of tools. They also conduct surveys, plan and update existing data sets in line with an organization’s demands.
Data Analysts also do well as Business Analysts as they possess the skills required to identify goals, develop better systems for data collection, and analyze current processes to uncover pain points and areas of improvement in a business or organization.
Excellent Market Research & Sales Analysts are brilliant Data Analysts as well. Their responsibilities involve researching, compiling, and analyzing information on products and market conditions to identify new markets, sales opportunities, and effective sales and marketing strategies.
Financial, Marketing, Advertising, Customer Success, Operations and Pricing Analyst, are just a few more of the many specialties and titles available to data analysts.