If you are still deciding on a career choice between data scientists and data analytics, this article might help you. While comparing the two, we have listed the differences between both roles’ skill sets and job responsibilities. So, let us understand the essentials of Data Analyst vs Data Scientist.
Table of Content
- Difference Between Data Analyst and Data Scientist: Data Analyst vs Data Scientist
- Who is a Data Analyst?
- Who is a Data Scientist?
Difference Between Data Analyst and Data Scientist: Data Analyst vs Data Scientist
|1. Gather data from databases and warehouses.
2. Write SQL queries and scripts.
3. Create reports with BI tools.
4. Spot trends and patterns from datasets.
|1. Perform ad-hoc data mining.
2. Use statistical methods and data visualization techniques.
3. Build AI models.
4. Automate tasks using machine learning models.
|1. Good understanding of statistics and probability.
2. Knowledge of Python and SQL.
3. Data wrangling.
4. Exploratory data analysis.
|1. Strong foundation in calculus, linear algebra, and statistics.
2.Proficient in Python, SQL, R, SAS, MATLAB, Spark.
3. Machine learning and cloud computing.
|Degree in computer science, IT, engineering, mathematics, statistics, or economics. Domain knowledge in the field is necessary.
|Similar educational background as a Data Analyst but with a deeper understanding and expertise in the domain.
|1. Delivering reports.
2. Examining patterns.
3. Collaborating with stakeholders.
4. Consolidating data.
|1. Problem-solving using data.
2. Analyzing data patterns.
3. Building data visualizations.
4. Developing predictive models.
|5.6 LPA (AmbitionBox)
|12.8 LPA (AmbitionBox)
Who is a Data Analyst?
A data analyst is a professional who collects, processes and performs statistical analyses on large datasets. They translate numbers and data into actionable insights to help organizations make informed decisions.
Here’s a more detailed description:
Data Analyst Role and Responsibilities
- Data analysts gather data from various sources, clean it to ensure its quality and accuracy, and then interpret it to identify patterns and trends.
- They use statistical tools to interpret data sets, paying particular attention to trends, patterns, and correlations that can be used to drive business decisions and strategies.
- Data analysts often create visual representations of data, such as charts and graphs, to make the data more accessible to stakeholders.
- They work closely with business units and departments to understand and address their data analysis needs.
Skills Required for Data Analyst
- They possess strong mathematical and statistical skills.
- Data analysts are proficient in programming languages like SQL for database querying and Python or R for data analysis.
- They have expertise in data visualization tools like Tableau, Power BI, or Excel to represent data visually compellingly.
- Analytical thinking and attention to detail are crucial skills for data analysts.
Education Required for Data Analysts
Typically, data analysts have bachelor’s degrees in computer science, statistics, mathematics, economics, or business. Some might also have a master’s degree or specialized training in data analytics.
Data Analyst Job Description
- Data analysts collect and store data on sales numbers, market research, logistics, or other behaviours.
- They bring technical expertise to ensure the quality and accuracy of that data, process it, and perform detailed analyses.
- After analyzing the data, they present their findings clearly and concisely, often using tables, graphs, and charts to describe their discovered patterns.
Data Analyst Salary
According to AmbitionBox:
Who is a Data Scientist?
A data scientist is a professional who specializes in extracting insights and knowledge from complex and unstructured data. They use a combination of various disciplines, including statistics, machine learning, data mining, and big data technologies, to analyze and interpret large datasets.
Also Read – Top Industries Hiring Data Scientists in 2024
Here’s a more detailed description:
Data Scientist Role and Responsibilities
- Data scientists are primarily problem solvers. They determine the questions that need answers and devise different approaches to solve the problem.
- They pull, merge, and analyze data, looking for patterns or trends.
- Data scientists use various tools and programming languages to develop and test new algorithms, including Tableau, Python, Hive, Impala, PySpark, Excel, Hadoop, and more.
- They simplify data problems, develop predictive models, build data visualizations, and present their findings to stakeholders.
Skills Required for Data Scientists
- They have a strong foundation in calculus, linear algebra, statistics, and probability.
- They are well-versed in programming languages like Python, SQL, and R.
- Data scientists are proficient in data visualization using tools like Power BI and Tableau.
- They have expertise in machine learning, cloud computing, and other advanced data analysis techniques.
Education Required for Data Scientist
- While there’s no fixed educational path to become a data scientist, most professionals in the field have advanced degrees (Master’s or PhD) in disciplines like computer science, statistics, mathematics, or engineering.
- Many data scientists also undergo specialized training or certifications in data science and machine learning.
Data Scientist Job Description
- Data scientists are primarily responsible for designing and implementing processes and layouts for complex, large-scale data sets used for modelling, data mining, and research purposes.
- They also develop predictive models and machine learning algorithms to extract insights from data.
- Communication is a key aspect of their role, as they need to present their findings to non-technical stakeholders.
Data Scientist Salary
According to Ambition Box:
What are the eligibility criteria for becoming Data Scientist?
For becoming a data scientist you should have either of the following: A bachelor's level degree in data analysis or data science. A postgraduate degree in either Business Analytics, Data Science, Data Science, and Analytics or Big Data
Besides educational qualification, what can you do as add-on?
In addition to the educational background, you can complement your degree by: Doing an internship with any Data Science firm Taking up courses related to Data Science, Probability, Statistics, and Linear Algebra Learning the basics of Information Extraction, Natural Language Processing, Computer Vision, Speech Processing, and Bioinformatics. Exploring the Optimization, Information Theory, and Decision Theory Gaining experience in data analysis, database designing, and its management.
Who can become a data scientist?
Software developers, business and data analysts as well as system and database administrators can become data scientists.
Which sectors require data scientists?
Top industries that recruit data scientists include: IT and Cyber security Digital marketing, BFSI, Media and Entertainment, Healthcare, Retail, Tele-communications, Automotive and Mining and oil & gas industry
What should a data scientist do to excel in their career?
An existing data scientist can do the following to excel in their career: Go for a project management course, acquire certifications in SAS or SQL and learn machine learning.
Can a fresher become a data analyst?
Yes, anyone who has completed graduation can go for the profile of data analyst. You would be required to have certain skills and certifications to kick start your career.
Which professionals can switch to a career as a data analysts?
The following professionals can opt for a career as a data analyst: Non-experienced professional System or database administrators, software developers, IT and Test analysts.
How does a fresher start a career as a data analyst?
Any fresher will at first be recruited as a junior data analyst or as an entry-level professional. You would be required to go for certification courses to upgrade skills and switch to a mid or senior-level position.u00a0
What are the desired skills for becoming a data analyst?
You should preferably have skills in programming, machine learning, data mining, and data visualization.
Who can become a data analyst after graduation?
Graduates with a degree in engineering, maths, statistics, and science-related subjects can become data analysts.
What is the career scope for data analysts?
At present, the career scope is limitless since every organization needs data for business growth. Data analysts can comprehend the data for finding methods to increase productivity and cost-cutting.