6 answers
Gourav
Student
Vadodara, Gujarat, India
1
Question
Asked
896 views
What exactly do data scientists and data analysts do?
I'm trying to explore these fields and looking for universities in the US that offer these programs
Login to comment
6 answers
Atul Bhankharia
Sales
454
Answers
Mount Laurel, New Jersey
Updated
Atul’s Answer
Data Scientists apply algorithms, machine learning, write software to derive results that is analyzed by Data Analysts who determines that the data is enough to make determination of what exec mngt looks for to make an informed decision.
The key is to define what information elements are needed/required to provide the charts/results.
In the US they offer degree to become Data Scientist.
The key is to define what information elements are needed/required to provide the charts/results.
In the US they offer degree to become Data Scientist.
Thank you, this is really helpful.
Gourav
Sachin Chorge
Data Scientist
7
Answers
Bengaluru, Karnataka, India
Updated
Sachin’s Answer
Data Science is fun if you love loads of data and records, like to work on multiple new processes and more importantly dealing with humans.
There is actually quite a thin line between Data Science, Machine Learning and Artificial Intelligence. and the best part is all the top notch techniques start with Data Science.
As a Data Scientist, we will often find us discussing different Processes with customers, internal or external. We will find that people have business requirements from the data, Examples like explained in the other answers here. These requirements are sometimes concrete, but most of the time, they would have abstract requirements.
According to me, the best part of being a Data Scientist is this piece, when we are trying to discover what story the data is telling us and how does it match with the requirements. Do we need something additional there, or does the data in hand suffice.
First of all, don't be surprised if we are spending lot of time, in cleaning up the data, making certain assumptions, validating those assumptions with our customers before even we start making a good sense on the further piece. With lot of tools available at our hand, nowadays, its not actually that big a task, but definitely takes time and effort, not maybe with the code, but with all those assumptions.
Then we start analysing and visualizing the data, the trends, the charts and the story. While there are chances, that we get carried away in the process, its always important, to go back to the customers and validate/ take their views on these initial findings.
The final piece is the Modelling and Output visualization. We will normally that its not a coding job at all. Hundreds of reusable codes will be easily available, just with a few googling, or directly using Chat GPT now. The important point to note here is we have to be completely conversant with the statistics behind those models, the parameters which need tweeking to fine tune the model.
Then finally presenting the Model Outputs to customers. Make sure you are using models which you are able to explain to them, because nobody is going to just take any conclusions blindly or just because some xyz model is giving the output.
For me, these interactions with customers, understanding processes, the discovery phase, analysis phase make this an awesome job. Coding is actually easy and simple...the fun part is applying our own intelligence.
I haven't put any tools or roadmap here, because I am sure you can easily find it with a bit a googling and help from ChatGPT.
There is actually quite a thin line between Data Science, Machine Learning and Artificial Intelligence. and the best part is all the top notch techniques start with Data Science.
As a Data Scientist, we will often find us discussing different Processes with customers, internal or external. We will find that people have business requirements from the data, Examples like explained in the other answers here. These requirements are sometimes concrete, but most of the time, they would have abstract requirements.
According to me, the best part of being a Data Scientist is this piece, when we are trying to discover what story the data is telling us and how does it match with the requirements. Do we need something additional there, or does the data in hand suffice.
First of all, don't be surprised if we are spending lot of time, in cleaning up the data, making certain assumptions, validating those assumptions with our customers before even we start making a good sense on the further piece. With lot of tools available at our hand, nowadays, its not actually that big a task, but definitely takes time and effort, not maybe with the code, but with all those assumptions.
Then we start analysing and visualizing the data, the trends, the charts and the story. While there are chances, that we get carried away in the process, its always important, to go back to the customers and validate/ take their views on these initial findings.
The final piece is the Modelling and Output visualization. We will normally that its not a coding job at all. Hundreds of reusable codes will be easily available, just with a few googling, or directly using Chat GPT now. The important point to note here is we have to be completely conversant with the statistics behind those models, the parameters which need tweeking to fine tune the model.
Then finally presenting the Model Outputs to customers. Make sure you are using models which you are able to explain to them, because nobody is going to just take any conclusions blindly or just because some xyz model is giving the output.
For me, these interactions with customers, understanding processes, the discovery phase, analysis phase make this an awesome job. Coding is actually easy and simple...the fun part is applying our own intelligence.
I haven't put any tools or roadmap here, because I am sure you can easily find it with a bit a googling and help from ChatGPT.
Shawn Velten
Data Scientist
2
Answers
Columbus, Ohio
Updated
Shawn’s Answer
Data Scientists are more and more becoming the core of all businesses today. They apply big data techniques, such as building SQL queries, building and maintaining databases, apply machine learning, and use statisical methods for forecasting results to trend and find outliers in the day to day business. Data scientists use SQL to pull, clean, and transfer big data so that business analysts can use it to build visual dashboards to tell a story of what is going on within the business.
Vanitha Vasudevan
Talent Acquisition
2
Answers
Edison, New Jersey
Updated
Vanitha’s Answer
Hey Gourav, I see that you are interested in Data. Data is the king and how to represent the data is the most critical challenge for any size company. A Data Analyst will be more involved in analyzing, presenting and reporting to the users. A Data Scientist is one more step ahead in data using Statistical modeling tools to build a predictive, analytical approach to present the data. You should first start learning to write simple SQL Queries, try to learn free courses that are available on Udemy or Coursera to get a heads-up and there are Bachelor courses that are targeted toward Data Science and Data Management.
Thank you, Vanitha!
Gourav
Tiffany Stephenson-Super
Senior Recruiter
25
Answers
Columbus, Ohio
Updated
Tiffany’s Answer
I 100% support Atul's answer to your question. Additionally, the best colleges/universities in the US for this major, according to US News and World Report are: University of California at Berkeley, Carnegie Mellon University, MIT, Stanford Univeristy, University of Washington, Cornell University, Georgia Institute of Technology, Columbia University and Unoversity of Illinois at Urbana-Champaign.
Thank you Tiffany!
Gourav
Robert Mingus
Culinary Director
67
Answers
Poplar Grove, Illinois
Updated
Robert’s Answer
Gourav,
I am a student earning my bachelor's degree in data science, and for the position, you may be doing statistical work or data analytics where you research data by the thousands. There are many outlets you can do as well. You can work for a company using R programming or SAS. Either way you will be valuable to any company doing so.
Retired Executive Chef Rob Mingus
I am a student earning my bachelor's degree in data science, and for the position, you may be doing statistical work or data analytics where you research data by the thousands. There are many outlets you can do as well. You can work for a company using R programming or SAS. Either way you will be valuable to any company doing so.
Retired Executive Chef Rob Mingus
Thank you so much Robert!
Gourav