Data Analyst VS Data Scientist VS Data Engineer

data analyst data scientist data engineer the simplest differentiation you will hear if this video is your vibe please remember to like and subscribe to this channel damsel and data the one you're watching right now thanks the common denominator between these three data related job titles is that they all tend to cause a bit of confusion for data job seekers and data hiring managers alike if i were to put these three roles on a spectrum i would put data scientists right in between data analyst and data engineer because it kind of takes aspects from each of the other two jobs and also builds on them with additional responsibilities and expectations so that being said i want to start this differentiation process at the beginning of the spectrum with data analyst data analysts have been around for ages making this job title probably the most common and frequently occurring of the three so what does a data analyst do they draw insights from and answer questions with data how do they do this they use their sql and scripting skills to extract and wrangle data their analytics and statistics skills to understand what the data is trying to tell them and to answer questions using it and they use their storytelling skills to present their findings in a way that's meaningful for the end consumer of the problems that they're solving data analysts are everywhere they can work in business contexts or in research contexts in pretty much any industry and in companies of all shapes and sizes as long as there is data available and a desire to learn from it and understand it in an advanced way there is a need for a data analyst the backgrounds of data analysts tend to vary a lot traditionally a data analyst would be someone with a bachelor's or master's degree in an area like math or computer science but the modern data analyst can also have a background in the natural sciences something business related or really anything as long as it has a quantitative component the education requirements aren't super strict and it's more based on your ability to work with and understand data key components of their role are extracting business intelligence from data building reports based on it and using a series of technical skills to do this they tend to work with a lot of different systems that hold and collect data depending on what kind of role they're in so they're also very sharp with picking up on new ui based tools in addition to the sql and scripting tools that pretty much every data analyst will work with moving along the spectrum let's talk about data scientists as i mentioned before this is the most ambiguous of the three musketeers and you will see the most variation in this role i'm not going to talk too much about what a data scientist is because i have a whole other video that talks exactly about that not me trying to get you to watch more of my videos turn up that watch time but for the most part in a nutshell i see a data scientist as being anywhere along the spectrum between data analysts and data engineers so it could be closer to one than the other taking some components of both with one additional ingredient machine learning like data analysts data scientists extract wrangle and draw conclusions from data but they also work with machine learning models data analysts can work with machine learning as well but they don't tend to go as in depth with it the major difference is that a data scientist would be expected to have a very deep understanding of machine learning applying advanced methods and using probably fewer out of the box tools data scientists may be doing some research in machine learning building models from scratch or working with deep learning for this reason data scientists are expected to have a bit more academic experience so they typically have graduate degrees in quantitative areas like math or computer science not a requirement it just tends to be that the expectation is a little bit higher in terms of academic training compared to data analysts data scientists tend to work with fewer user interface-based systems and data collecting systems and they focus more of their time writing the code to implement their scientific methods for working with the data they also may have advanced computer science knowledge to be able to develop their complex models in a scalable way this might mean having knowledge of working with cloud computing and distributed systems and writing computationally efficient code this part of a data scientist the computer science knowledge is the overlap that they have with data engineers so let's move on to that one data engineer is perhaps the most well-defined role of the three you can probably see the most consistency with this one so a data engineer is a specific flavor of a software engineer so if you're more interested in the software engineering side data engineer would be the fit for you and it's a software engineer that is focused on building and maintaining data infrastructure and data systems these are the brilliant people setting up the data warehouses data pipelines and databases that the data analysts and data scientists use to access and work with the data at smaller companies a data analyst or data scientist might also be doing this data engineering work or it could be a software engineer that's focusing on the data engineering work job titles especially around this data space are a product of how the company is set up and what kind of resources they have so it's very important to understand the job description to know what kind of gig you're getting yourself into as mentioned previously data engineers have strong computer science skills and as such they have a background in some kind of software development or computer science whether it's academic or self-taught they know all about databases big data tools and a variety of programming languages and frameworks they may also dabble in machine learning especially from the side of scaling machine learning models putting them into production and integrating them with broader systems because there isn't a concrete mutually exclusive list of attributes associated with each of these roles there's a significant degree of inconsistency between how individual companies and people define them so please do not come for me if you see a data analyst role where it's all about machine learning or a data engineering role where they it requires statistics knowledge i don't make the rules i'm just playing the data game to summarize the similarities and differences i've put together this super cheesy looking venn diagram and as aesthetically disgusting as it is i hope that it nicely summarizes everything we just talked about today if this is a topic you're interested to learn more about i left some links in the description for further reading check out my what is a data scientist video if you haven't already to dive deeper into data scientists and the different types of data scientists that we see some closer to data analysts some closer to data engineers and some on the research path and if that's not enough and you still want more please hit up my comment section let me know what else you want to see if you're left with any questions after this video i'm happy to address them that's all for me i will catch you next time thanks for watching bye

Channel: Damsel in Data

Views: 69,241

Keywords: data analyst vs data scientist, data scientist vs data analyst, data analyst vs data engineer, data engineer vs data scientist, data engineer vs data analyst, data scientist vs data engineer, difference between data analyst and data scientist, what is a data analyst, what is a data scientist, data science vs software engineering, data science vs computer science

Id: rKpdsnjJjOM

Length: 7min 21sec (441 seconds)

Published: Tue Feb 23 2021