According to a definition, data analyst is the type of data scientist, who is hired temporarily to collect various data about certain organization, analyze it and present their conclusions to a manager of said organization, offering ways to improve business.
The most interesting part is – not only tech companies are interested in services of data analyst – companies in various areas of business – from traveling agencies to perfumery and wine selling businesses are hiring data analysts constantly.
Kwame Awuku, self-employed data analyst, gives a great example on what typical order for a data analyst is in a recent video about whole structure of his job:
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What qualifications are essential for an entry-level data analyst?
First, and basic one – Barchelor’s degree in spheres such as Mathematics, Computer Science, Finance or Statistics.
Second one – to complete courses for data analysts, where they basically teach you how to use the most common data mining tools and write reports with recommendations.
Tools you may need to use as a Data analyst:
Microsoft Excel®
SQL
Google Analytics ™
RapidMiner™
Google AdWords™
Kwame Awuku has his own blog, dedicated to providing courses to data analysts, I recommend you to check it out if your goal is to raise your qualifications as a data analyst:
https://courses.coglitics.com/?ref=341360/*
Sources:
https://www.careerexplorer.com/careers/data-analyst/
https://www.roberthalf.com.au/our-services/it-technology/data-analyst-jobs
https://www.rasmussen.edu/degrees/technology/blog/what-does-a-data-analyst-do/
That’s actually quite interesting topic. Anywhere on the internet we can find information about how easy it is to become data scientist. Well, that true that gaining knowledge and skills on fields of programming is relatively easy. A friend of mine wrote and interesting article on how he became he became a real-world data scientist whithin a year and it does not seem like a peace of cake. Technical skills is one thing, but when one starts to work with professionals on real cases, things may turn out to be different than expected. There are variety of skills (such as advanced mathematic knowledge or problem solving connected with hardware) that one may need to face real challanges.
Here is an article: https://www.datasciencecentral.com/profiles/blogs/data-science-insights-after-a-rookie-year-in-the-industry
Thy video that you’ve inserted is from a guy named Matt Tran and his channel on YouTube is called Engineered Truth. He is a shady person. Don’t trust a single word he says. Watch this: https://www.youtube.com/watch?v=zFbeyeQ2cCs
Given the ever-increasing volume of information, Data Analyst will become one of the most popular professions of the future.
Someone will need to sort the data, separate the necessary from the garbage. And I think the salaries of these guys will be fabulous.
Interesting topic but I wouldn’t find the guy from the video as a good example of a data analyst, he mainly focuses on tools which are ready to use and that is not the main point in being data analyst. Also, we have to remember that being data analyst is much different than being data scientist because the second one uses more AI in his/her job.