You do not need to have a tech background. I know many analysts and engineers who come from psychology, education, linguistics, etc backgrounds. What you should do is leverage all the skills from your background to help you transition. People with a non-STEM background have a different perspective of how to tackle a problem and that perspective might yield a better solution. I recommend transitioning into a data analytics role that is located in the industry that you have experience in. Ex: If you have experience with HR, then go look for HR data analytics positions. Come from car sales, go look at sales operation data analyst positions or data analytics positions at car manufacturers.
You do not. If you don’t have a degree, I recommend getting certified in a specialized data tool, depending on which job role you're interested in (Tableau, Power BI, Azure, etc). I recommend getting the entry level cert for whatever tool it is you choose. Just remember, certs don’t equal experience so you should be doing projects and hands-on labs as you're studying. Those projects will give you experience AND confidence that you're learning and retaining the information you've been studying.
For data analyst and data engineering positions, you generally do not need an extensive background..and it really just depends on the industry that you're working in. Having a basic understanding of statistics(mean, median, mode, standard deviation) will suffice. When it comes to data science, the skillset does require probability and statistics knowledge (which can be picked up in a Udemy course).
For entry level data analyst roles, you do not need to know how to program. However, learning basic Python or R can set you apart and give you more negotiation power when you receive an offer. It shouldn’t be a main focus when you’re studying for a data analyst position. Clicking and pointing is just fine. However, you do need to know how to code for data engineering, and data scientist positions.
SQL is extremely important in the data industry and you should learn it. It is basically used to communicate with a database so you can retrieve the data to analyze. The basics are not hard to learn because it isn’t a true programming language like Python or Java or Golang, you aren’t building a program with SQL. It’s literally keywords that you use to communicate with a database, similar to how you use keywords to talk to google. It’s just a format that you use to talk to a database/data warehouse. If you're interested in becoming a data analyst.
There are tons of opportunities. Companies are realizing that they need to leverage their data to understand how to improve their businesses on every scale! From internal process, external processes, improving customer satisfaction, understanding what new products and services to offer, etc. Companies who fail to utilize their data are and will be not be competitive, therefore they will be left behind. Many companies are in the beginning stages of sorting, managing, and analyzing their data. Therefore, they need data analysts, data engineers, and scientists to help them with that.
Business analyst: They focus on analyzing processes, systems, problems and give suggestions on how to improve them. This is definitely more of a functional role. They receive data/dashboards from a data analyst and use that information to give suggestions to stakeholders on how to make improvements.
Data Analyst: They focus on creating dashboards which are then used by stakeholders(business analysts and managers) for insight on how to solve a business problem. This is a technical role since it focused on data.
Data Engineer: They gather and clean data from multiple sources/applications and store that data in one centralized place, typically called a data warehouse. This role is highly technical as it involves programming.
Data Scientists: They also gather and clean data from multiple sources, including data warehouses and unstructured data sources(text files, emails, videos, photos, etc)...and decide if the data will be useful for modeling(machine learning concept).
I tell people to start with Tableau or PowerBI since those are very much in-demand and are too complicated to learn. All data viz tools do the basics, it’s similar to choosing which gas station to go to...they all pump gas, but they offer different pricing, snacks, features like a car wash, etc. There's lots of demand for each of the different tools. Just pick one and go.
Same answer as above, pick one of the popular ones and just start learning. The data services they offer all basically do the same thing to a certain extent, the services just have different names. I would focus on learning the fundamentals behind the service itself, that way if you do need to switch to another cloud providers adjacent tool...it won't be a steep learning curve because the skills needed are the same. Ex: Learning Amazon Redshift and applying for a job that uses GCP BigQuery. If you already know the fundamentals of Data Warehousing and SQL, BigQuery won't be hard to quickly pick up.
Entry level business analyst salary: $60-70k (USD)
Entry level data analyst salary: $65-85k (USD)
Entry level data engineer salary: $85-95k (USD)
Entry level data scientist salary: $90-100k (USD)
I got you covered. I actually created a masterplan infographic that gives you the fundamental steps you should take to land your next role. Feel free to save and share it with your friends!