Many people have this question in mind while entering into Data related fields. These two are different job profiles but the destination or career path is one and the same.
Both are good career opportunities but you need to decide between the two based on your goal on what you want to become. Here we have discussed both the roles thoroughly.
Data Analyst is the entry level job whereas Data Scientist is a much advanced career or job role. People while moving into data related fields, first go with Data analyst related job roles. They practice fully fledged into this role and once they have experience of around 5-7 years, they move into the role of Data Scientist. The kind of work differs between Data Scientist and Data Analyst. Data Scientist is much more about analysis of data and performing visualization of data on tools like Tableau or POWER BI.
It is more of running SQL queries or python codes for analysis purposes. Data Scientist is more of an advanced career path. It involves algorithms and AI or ML based algorithms to implement using coding. Data scientist is an advanced role and requires some years of experience before moving into it.
A data scientist is required to create pipelines for data flow, analyse it, visualise it and create models around it for business operations.
Skillfin provides some amazing courses in Data Analyst. Listed below two best courses from them:
1. Bootcamp: The Data Analyst Skills Training (DAST) with Excel
You will learn Data analysis and basically visualization techniques using excel. Mostly taught through live videos. More people have some experience, basically working professionally.
Master the technique of Data Analysis and visualization using excel in this course. All the important tools and skills like Mysql, Tableau, Power BI, Python coding are covered.
Price: Rs 3,999
Really good one to understand excel functions for performing data analysis using Excel. Covers almost all the functions of Excel e.g Mathematical skill, formulas, filters, etc.
You will learn some extra coverage and new tips to do data analysis using excel. All the important functions like concatenate, len, Find, left, Mid , Trim and Find functions are covered
You will learn Excel functions to perform data cleaning, data manipulation and data analysis using the Text functions in Excel. This course is more for fresh graduates, since it is a free course. Freshers can take it and learn what data analysis is exactly and how to do it using multiple tools and options and specifically learning it from excel.
Data Analyst in short term means = Data Analyst + Creation of models. It involves tasks which a regular Data Analysis does, and along with it models are also created using AI techniques. All kinds of learning are involved.
It involves creating pipelines for data flow from source or enterprise to destination. Destination address can be anything. It can be a database or a visualization tool like Tableau.
It also includes forming a structured data of data. Converting live streaming of data which is non structured and converted into structured format.
Data analysis using Sql or Python programming: You can code with sql queries or Python to do data analysis. Also, you can use MS Excel as well to do data analysis.
Performing visualization using excel, Tableau through charts and graphs
It helps with creating models such that it can be used by businesses to increase sales and revenues.
The job description of a data analyst varies depending on the companies or projects with which they are associated, but the core needs for all the roles are the same. Core values are listed below:
This includes identification of numerous data sources and data extraction or collection automation.
Performance of data pre processing and sorting of structured and unstructured data.
It helps in analyzing large volumes of data in order to find patterns and trends.
It includes using algorithm and machine learning to build predictive and forecasting models.
Storytelling to non technical personnel or stakeholders utilizing immersive data visualization approaches employing the process known as esembling.
Developing data driven strategies and solutions to address business and handling sensitive information
A data analyst's job is to ensure that data is processed and sorted correctly in sensitive contexts.
A data analyst must be confident in their ability to spot patterns in data.
They should be able to spot anomalies and perform statistical analysis.
They must have knowledge of Machine learning and be able to apply associated models or algorithms to help machines learn from data.
Some really asked questions asked in interviews are:
There are so many job roles for data analysts and many designations are available in the market to appear. Few listed below:
Required to do data mining of unstructured data, apply statistics, ML methodologies to transform into structured data.
A Btech Degree in fields like Math, Physics, Computer Analyst, Engineering, etc.
A master’s degree in any field related to Data Analyst
Online certifications are provided.
Kinds of Employments:
Full-time: Opted and most common form of employment that ensures stability and career growth in this field.
A business intelligence developer is someone who converts business data into understandable format to help the development of the team. In Real terms, A business intelligence developer is the layman’s data analyst.
He/ She should have practised BI tools (e.g. Power BI) to understand the obtained data sets and present them in forms of graphs, diagrams or reports etc. It would be really helpful for business owners and customers to understand clearly.
B.tech degree in related fields like programming or computer analyst
Any Experience is appreciated in this field.
Part-Time: Not recommended and not something for BI developers
Full-Time: Most preferred, since job security is provided.
A machine learning engineer/ analyst is highly in demand in this field. He/ She is the one responsible for creation of an algorithm that would access the model, which in turn will provide the given data and produce in the form of a structured output. Educational requirements involve-
Part-Time: For extensive programming skills, who would want to freelance and want to apply from distance.
Full-Time: Preferred by engineers who have a strong technical background and are looking to establish their data analyst job profiles.
There are so many plenty of resources and videos available online and it is very confusing for anyone to start learning all the concepts together. When you are a beginner, it is possible that you might get overwhelmed with so many modules. There is a possibility that you might stop learning due to fear of learning. All I want to say is stay committed.
Maths is very important as it will help us in understanding various ML algo’s that play a major role in DS
2) Separate coverage to Probability
Probability is also important to statistics, and it is considered a prerequisite for Data Analyst.
Introduction to Probability Part 1:
3) Statistical skills
Introduction to Statistics Part 1
4) Coding Practise
You need to have a good grasp of coding concepts like Data Structures , Algorithms. Languages can be Python, R, Java or Scala.
Python Part 1:
R Part 1:
5) Machine Learning Algorithms
Introduction to ML Part 1:
All of the above skills are important and you need to study them in order to grasp them better.
Overall Data Analyst and Data Analyst differ on the basis of job role. Data analyst is the step 1 towards the data analyst. Data Analyst is for sure entry level job. Data Analyst is more for people having some experience in data related fields. Both are good career roles and you can choose based on your career path.