Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconTop 4 Data Analytics Roles To Look Out For

Top 4 Data Analytics Roles To Look Out For

Last updated:
13th Jul, 2017
Views
Read Time
6 Mins
share image icon
In this article
Chevron in toc
View All
Top 4 Data Analytics Roles To Look Out For

What does a data engineer do? How does that differ from what a data analyst’s role is? Who is a data scientist then?! Confused? Here’s an attempt by us to put these Data Analytics roles into different buckets. It’ll answer all these questions for you.
If you are looking to transition from IT, or any other field, to Data Analytics, then you may want to go through this carefully to understand your options. Moreover, if you are already in this field, and are considering a shift or upgrade, then here are all your options mapped out for you!
Data Analytics is an evolving field and although these roles are defined loosely. There are 4 buckets within Data Analytics roles.
Let’s take the example of an e-commerce company. Let’s try and understand all these different types of Data Analytics roles. Check out the video or infographic or just continue reading below!

Check out our data science certifications to upskill yourself

Top 4 Data Analytics Roles To Look Out For UpGrad Blog

As shown in the infographic here’re the top Data Analytics Roles:

Data Engineer

A data engineer creates the platform and the data structure within which all the data from the users is captured. For example, the items they buy, what is in their cart currently as well as on their wish-list. Data engineers should make sure that the captured data is stored in such a fashion that it is not only efficient but also easily retrievable.
They are comfortable in working with varied data sources, write ETL queries to collate data from all of them. Then they organize all this data in data warehouses or databases. So that, others in the company can make the best use of it.
To become a data engineer you need to acquire knowledge of languages such as Python, Java, SQL, Hadoop, Spark, Ruby, and C++. You should note, however, that knowledge of all of these is not mandatory but varies from company to company.

Explore our Popular Data Science Degrees

As a data engineer, you would be sitting at the rare intersection of a software engineering professional and a data analyst.
Who is a Data Scientist, a Data Analyst and a Data Engineer?

Data Analyst

Data analysts are expected to draw insights from the data, which directly impacts business decisions. They are directly involved in day-to-day

business activities. There are a lot of ad hoc analyses that a data analyst or a business analyst is expected to do.
For example, a data analyst in an e-commerce company helps the marketing team identify the customer segments that require marketing, or the best time to market a certain product, or why the last marketing campaign failed and what to do in the future to prevent such mistakes. Hence, for a data analyst, a good understanding of business, data, and statistics is essential.

Checkout: Data Analyst Salary in India

Top Essential Data Science Skills to Learn

The tools and languages that would be most commonly used by a data analyst would be Excel, SQL, and R, and in some cases Tableau as well.
How Can You Transition to Data Analytics?

Our learners also read: Learn Python Online Course Free

Data Visualiser/Business Intelligence Professional

There might be a data visualizer or a business intelligence professional at this e-commerce company. They are responsible for creating weekly dashboards to inform the management about various metrics. These metrics include weekly sales of different products, the average delivery time, or the number of daily cancellations of orders.

Read our popular Data Science Articles

upGrad’s Exclusive Data Science Webinar for you –

Transformation & Opportunities in Analytics & Insights

Data Scientist

A data scientist uses the data that the organization holds, to design business-oriented machine learning models.
As a starting point, data scientists can go through the available data of the company to look at various buying patterns, identify similar items on the website, and identify similar users. Then, they will create algorithms around the same so that the website can automatically recommend products to the users based on their navigation histories, purchase histories, and other such metrics. This solution must be effective enough that it can predict the future purchases, in real-time, for website visitors.
The way this is different from a data analysts’ role is that data analysts are expected to perform a lot of ad hoc analyses which can facilitate decision making within an organisation. Data scientists, on the other hand, not only perform ad hoc analyses and create prototypes, but they also create data products that make intelligent decisions by themselves. This is where machine learning becomes extremely critical.
The requisite tools and concepts for a data scientist is knowledge of algorithms, statistics, mathematics, machine learning, and programming languages such as R, Python, SQL, and Hive. A data scientist should have a business understanding and the aptitude for framing the right questions to ask. They should find the answers in the available data. Then communicate the results effectively to the team members, and all the stakeholders.
What Kind of Salaries do Data Scientists and Analysts Demand?

We hope that this helps you segment all the different Data Analytics roles and decide where you fit in best. Good luck with your career!
In case you have any questions, please write to us at analytics@upgrad.com or comment below.

If you are curious to learn about data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

Profile

Rohit Sharma

Blog Author
Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Frequently Asked Questions (FAQs)

1What is Data Analytics?

Data analytics is a generic term that refers to a variety of data analysis techniques. It is the science of evaluating raw data and drawing conclusions from it. Many data analytics approaches and procedures have been turned into mechanical processes and algorithms that operate with raw data and are intended for human consumption. Learners can use data analytics techniques to any sort of data to get the knowledge that they can utilize to improve things. Using data analytics techniques can lead to discovering trends and metrics that might otherwise be lost in a sea of data. Professionals can then utilize this data to improve a company's or system's overall efficiency by optimizing operations.

2Is learning Data Analytics difficult?

Data analytics is a very easy area to enter into because it is not overly academic, and you can pick up the necessary skills along the road. In order to accomplish the job of a data analyst, you will need to acquire a wide range of abilities. Math and statistics, analytics and modeling, machine learning methods, programming, data visualization, intellectual curiosity, communication, and business skills are just a few of the skills required. Data analytics allows you to have a continuous learning process in which you must have sufficient domain knowledge as well as technical expertise to query and draw insights from data.

3Do Data Analytics jobs pay well?

Data Analyst is a highly demanded job profile in the IT industry and one of the highest-paid. Since a huge amount of data is generated every day, Data Analytics experts have a variety of work options. With less than a year of experience, an entry-level Data Analyst can expect to earn an average total pay of ₹3,41,912. The typical salary for an early career Data Analyst with 1-4 years of experience is ₹4,26,604. The total average pay for a mid-career Data Analyst with 5-9 years of experience is ₹6,96,444. The average total salary for a Data Analyst with 10 to 19 years of experience is ₹9,42,653.

Explore Free Courses

Suggested Blogs

Data Science for Beginners: A Comprehensive Guide
5015
Data science is an important part of many industries today. Having worked as a data scientist for several years, I have witnessed the massive amounts
Read More

by Harish K

28 Feb 2024

6 Best Data Science Institutes in 2024 (Detailed Guide)
5020
Data science training is one of the most hyped skills in today’s world. Based on my experience as a data scientist, it’s evident that we are in
Read More

by Harish K

28 Feb 2024

Data Science Course Fees: The Roadmap to Your Analytics Career
5036
A data science course syllabus covers several basic and advanced concepts of statistics, data analytics, machine learning, and programming languages.
Read More

by Harish K

28 Feb 2024

Inheritance in Python | Python Inheritance [With Example]
17102
Python is one of the most popular programming languages. Despite a transition full of ups and downs from the Python 2 version to Python 3, the Object-
Read More

by Rohan Vats

27 Feb 2024

Data Mining Architecture: Components, Types & Techniques
10582
Introduction Data mining is the process in which information that was previously unknown, which could be potentially very useful, is extracted from a
Read More

by Rohit Sharma

27 Feb 2024

6 Phases of Data Analytics Lifecycle Every Data Analyst Should Know About
79397
What is a Data Analytics Lifecycle? Data is crucial in today’s digital world. As it gets created, consumed, tested, processed, and reused, data goes
Read More

by Rohit Sharma

19 Feb 2024

Sorting in Data Structure: Categories & Types [With Examples]
137475
The arrangement of data in a preferred order is called sorting in the data structure. By sorting data, it is easier to search through it quickly and e
Read More

by Rohit Sharma

19 Feb 2024

Data Science Vs Data Analytics: Difference Between Data Science and Data Analytics
67762
Summary: In this article, you will learn, Difference between Data Science and Data Analytics Job roles Skills Career perspectives Which one is right
Read More

by Rohit Sharma

19 Feb 2024

13 Exciting Python Projects on Github You Should Try Today [2023]
44748
Python is one of the top choices in programming languages among professionals worldwide. Its straightforward syntax allows software developers and dat
Read More

by Hemant

19 Feb 2024

Schedule 1:1 free counsellingTalk to Career Expert
icon
footer sticky close icon