 What's going on everybody? My name is Alex Freberg and in today's video we're going to be talking about everything you need to know about what a data analyst actually does in their job day-to-day. We're also going to be walking through qualifications, skills, and the salary that you can expect as a data analyst. So let's start with the job description and I'm going to take you through each part of what a data analyst actually does in their job. And the very first part of that is defining the problem. The first thing that you have to do is determine what the client actually needs. Do they need a dashboard? Do they need reports? Do they need you to do some type of analysis on their product and give some type of recommendation? And when you get that you have to create a plan of action. When are you getting this data? Where is it coming from? Where are you putting the data? And what are the times frame for all these steps? And often it can be your job to communicate that to the team. The next thing that you want to do is collect the data. And data can come from a ton of different sources. So whether that's a SQL backup, a FlatFly, or an API, or if they have all of those, you have to be able to get all that data into one place. Then you need to work with your programmers to create an ETL process which means extract, transform, and load. So you're going to work with your programmer to actually get the data. And then you're going to create business rules to transform it for how you actually want it to look in your system. And then you actually have to load the data. This can also be known as creating an ETL pipeline. If you have data that's going to be coming in either weekly or monthly, you don't want to have to do this process manually every single time. And so creating a pipeline is going to be creating an automated process to bring that data in the same way every single time. And that's going to save you a lot of time every single time that you bring that data into your system. And the very last thing is aggregating your data, which basically just means standardizing your data and putting it all together instead of having it as separate sources. And the next thing that you'll do as a data analyst is actually clean the data. And data is always messy. Trust me, I have seen just about everything that you can imagine. They're using three different date formats. Some people's names are capitalized for absolutely no reason. And somebody forgot to add the customer ID so you can't actually map the patient in your system. And you do all this because you want to make the data a lot more usable for later processes. And part of this is normalizing and standardizing the data so that when you do your visualizations or your reports later, all the data looks the same that can be used in any part that you need to be used in. And the last part of this is data validation, which is basically just quality assurance and you're looking through your data and running queries on your data to make sure that your data looks how it's supposed to look. The next thing that you need to do is set up your data for reports and visualizations and oftentimes you do this through creating views. A view allows you to combine several tables into one and then choose a subset of that data that you actually want to use for your reports and visualizations. And each view may need to be formatted differently based on what you're going to be using it for in the report or the visualization. And for the very last thing you're actually going to create your reports and your visualizations. I know for myself I use SQL for all my reports so I like to automate that process so that if a client wants it every week or every month, I can just create a store procedure or a job that automatically sends that out with the latest data every single week or month. You can also connect that data to a data visualization tool like Tableau, Power BI, Python or R. And lastly you just want to make sure that your report and visualization solves a problem that you intended it for it to solve. So it goes back to the very first thing that we looked at which is what does the client want, what do they need. And so this step just makes sure that that is actually resolved. Next let's look at some of the qualifications for a data analyst. Oftentimes you are going to need a bachelor's. I haven't seen a lot of jobs where they have not required a bachelor's degree. So oftentimes that is the minimum requirement for you. And often they want those degrees to be in something like computer science, statistics, mathematics, finance or something like that. A master's degree may be required for some positions. It doesn't happen often, but I have seen some data analyst positions that do require a master's. I don't think you need a bachelor's degree in order to become a data analyst, but I think it definitely helps, especially when a lot of jobs require a minimum of a bachelor's. Next let's look at some of the skills that data analysts actually use. The first one is SQL, then we have R and Python, Tableau, Power BI which are our data visualization tools, SAS or SPSS, Excel and then some type of cloud platform like AWS or Azure. Now let's look at salary. For an entry-level job you can expect $45,000 to $60,000, a mid-level from $65,000 to $80,000, and then for a senior-level position anywhere from $85,000 to $110,000. There definitely are a lot of things that data analysts do and a lot of things that you need to learn in order to become a data analyst, but I will say that almost all these things you can learn for free online or for a very affordable price on things like Udemy or Coursera or edX. And so there are so many options for actually learning the skills that you need to become a data analyst. And I highly recommend just looking into it and seeing if this is something that you're really interested in. I hope that helped you understand a little bit more about what a data analyst actually does in their job. Thank you guys so much for watching. I really appreciate it. If you want to support the channel, I have a Patreon link in the description. Be sure to like and subscribe and I'll see you in the next video.