3 answers
Arvaiya
Student
Rochester, Minnesota
7
Questions
Asked
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can Data Science be overwhelming?
If it is overwhelming can you tell me why it is? What is the most overwhelming task in this career or you have done?
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3 answers
Manesh Tailor
Field Engineering Director
5
Answers
London, England, United Kingdom
Updated
Manesh’s Answer
Hello, I notice that you're brimming with questions about the field of Data Science. It's wonderful to witness your keen interest and determination to delve deeper into this area, aiming to comprehend how you can thrive in it. In an attempt to address your multitude of queries, I'll consolidate my responses into a single, comprehensive answer. Please bear with me as this might turn out to be quite lengthy.
While I must admit that I'm not a Data Scientist by profession, I hold a degree in Statistics and have a solid background in Monte Carlo Simulation and Bayesian Analysis. I also work in close collaboration with our Data Science Team, so I'm more than willing to offer my perspective on this subject.
In response to your initial question about the characteristics needed to become a Data Scientist, a robust understanding of Mathematics is crucial. A deep comprehension of Statistics is essential as it forms the backbone of data interpretation and results analysis. If you have a passion for Statistical Math, you're off to a great start. Another vital trait is curiosity. You should be the kind of person who loves to ask questions and seeks evidence. Moreover, you should be willing to challenge your own hypothesis. It's often easy to justify a hypothesis or viewpoint using data, but striving to disprove it is a unique skill.
Additional skills and knowledge that will significantly aid you include the ability to query data using SQL. Despite the existence of numerous No-SQL databases, the fundamental understanding of joins, filters, relationships, and data navigation from a Database is indispensable. Complementing this is the need for some programming skills. You don't necessarily need to master a specific language like Java, Python, or NodeJS (although that would be beneficial), but having a mindset that grasps programming logic, iteration, parsing, and programmatic operations is a critical skill.
One common frustration among Data Scientists is the lack of control over certain aspects. These include:
a) The data source - initially, you have little control over what data is collected, the collection method, and frequency.
b) The data's accuracy and completeness - issues like incomplete or inaccurate data collection can arise.
c) The systems used for data mining - the suitability of the data storage for your analysis type and the budget for acquiring better tools.
d) Time estimation - it can be challenging to predict how long it will take to obtain specific answers, which can be stressful when under pressure as businesses increasingly rely on data science results for crucial decisions.
However, these challenges are balanced by the rewarding outcomes of your work. The impact you can make on a business or research output can be exhilarating. The significant contributions you can make to companies can be incredibly rewarding and satisfying.
While I must admit that I'm not a Data Scientist by profession, I hold a degree in Statistics and have a solid background in Monte Carlo Simulation and Bayesian Analysis. I also work in close collaboration with our Data Science Team, so I'm more than willing to offer my perspective on this subject.
In response to your initial question about the characteristics needed to become a Data Scientist, a robust understanding of Mathematics is crucial. A deep comprehension of Statistics is essential as it forms the backbone of data interpretation and results analysis. If you have a passion for Statistical Math, you're off to a great start. Another vital trait is curiosity. You should be the kind of person who loves to ask questions and seeks evidence. Moreover, you should be willing to challenge your own hypothesis. It's often easy to justify a hypothesis or viewpoint using data, but striving to disprove it is a unique skill.
Additional skills and knowledge that will significantly aid you include the ability to query data using SQL. Despite the existence of numerous No-SQL databases, the fundamental understanding of joins, filters, relationships, and data navigation from a Database is indispensable. Complementing this is the need for some programming skills. You don't necessarily need to master a specific language like Java, Python, or NodeJS (although that would be beneficial), but having a mindset that grasps programming logic, iteration, parsing, and programmatic operations is a critical skill.
One common frustration among Data Scientists is the lack of control over certain aspects. These include:
a) The data source - initially, you have little control over what data is collected, the collection method, and frequency.
b) The data's accuracy and completeness - issues like incomplete or inaccurate data collection can arise.
c) The systems used for data mining - the suitability of the data storage for your analysis type and the budget for acquiring better tools.
d) Time estimation - it can be challenging to predict how long it will take to obtain specific answers, which can be stressful when under pressure as businesses increasingly rely on data science results for crucial decisions.
However, these challenges are balanced by the rewarding outcomes of your work. The impact you can make on a business or research output can be exhilarating. The significant contributions you can make to companies can be incredibly rewarding and satisfying.
Tylor Mondloch
Data Science
3
Answers
Billings, Montana
Updated
Tylor’s Answer
I wouldn't describe it as overwhelming, but it's also important to be able to organize your thoughts. Your preferred form of note-taking and thought-mapping, even if it's old-school paper, is critical - otherwise all the parts of a process and the options at each step will become very hard to navigate.
the most overwhelming task in my career happened early on, when I'd been working in the field for about a year. We needed to develop a custom clustering algorithm, because our use-case was extremely specific. I spun my wheels for a while, going down rabbit holes... it wasn't productive at all. Eventually I started back at page 1, started organizing all my thoughts into a flow diagram / decision tree, and was able to view the whole situation holistically. That's how I broke out of the overwhelmed mindset.
the most overwhelming task in my career happened early on, when I'd been working in the field for about a year. We needed to develop a custom clustering algorithm, because our use-case was extremely specific. I spun my wheels for a while, going down rabbit holes... it wasn't productive at all. Eventually I started back at page 1, started organizing all my thoughts into a flow diagram / decision tree, and was able to view the whole situation holistically. That's how I broke out of the overwhelmed mindset.
Olivia Wandzilak
Solution Analyst
2
Answers
Phoenix, Arizona
Updated
Olivia’s Answer
Hi Arvaiya! I graduated with a Business Data Analytics degree about a year ago and have been working in data analytics/processing for the past 8 months since joining Deloitte. Data science, like any other subject, may be overwhelming when you first start to learn the subject matter. My first introduction to the topic was in college through my classes and before then, I had basically no exposure to any data-related topics. That being said, it was a bit overwhelming at times trying to understand a completely new topic. Overtime, like with any new subject you are learning, you become more and more familiar with the concepts and feel more comfortable with complications that arise. From my experience in my current role as a relatively new addition to Deloitte, I would say it is overwhelming to receive code errors and feel confident in your abilities to resolve the error. However, that is part of the learning process! Learning from errors/mistakes is what strengthens your skills. You can also always leverage other people for help when you need it.