Rewind or your year's journey which the company gives at the end of the year. like Spotify, they will show you how many songs you had played this year, how many artists you had played, what genre you like most, which song you played many times, like all the details.
Now you can imagine what amount of your data they have based upon your usage. They can use these all data to advertise a particular album or product to generate their revenue. This is why the data field is getting bigger and bigger all the time and it is becoming more important.
The whole system of bringing data in to convert it into useful information is called a data ecosystem. It can be anything like detecting financial fraud, social media mining, reading customers' buying habits, etc. The people who run this ecosystem are called the data professionals. The data ecosystem is very huge so, there are different types of professionals for different kinds of work.
Data Professionals:
- Data Engineer
- Data Analyst
- Data Scientist
- Business Analyst
- Business Intelligent Analyst
Data Engineer
Data Engineers maintain and develop data architecture. They make data available for their business analyst or data analysis for business operation or action.
They Extract, integrate, and organize data from different sources.
They also perform some actions on data like cleaning, transforming, and preparing data to store that data into the warehouse or manage.
They design, store, and manage data repositories so that data can be quickly accessible.
Skills:
They have some good programming knowledge.
They need excellence in system and technology architectures.
Also, they need to have a deep understanding of relational databases and non-relational data stores.
Data Analyst
Data analysts convert the bulk of data into useful patterns and information. I already talked about deeply on data analyst, you can check here.
They inspect and clean data for the analytics operation.
They try to find patterns and correlations between data to get some useful information.
They provide visualization to nontechnical people like a business analyst so, that he can make business decisions based on that data.
He also helps data scientists retrieving data as per the request.
Skills:
Excel
tableau, power BI
Databases
Python (pandas, numpy, etc)
story telling
presentation skill
communication skill
Data Scientist
Data scientists are a creative person who tries to find very critical patterns or to create predictive machine learning model based on their mathematical and high-level programming skill. They analyze data for actionable insights.
Skills:-
Understanding of high-level programming languages
Huge understanding of databases
Expertise in machine learning and deep learning
Very deep domain knowledge
Business analyst and BI analyst
Business analyst wants to make their business decision according to data patterns and useful information about customer behavior so they work very closely to data analyst and data scientist to get the maximum amount of work.
The big difference between a business analysts and a business intelligence analysts is a business analyst is more into closely working with data analysts and data scientists. They give an idea of what to find and what is beneficial for the business. So, basically, they do insider work of the company.
Where Business Intelligence analysts are more into outside analysis like the market, economy, competitor, products, etc. They have less technical knowledge and they have most of the business skill on how to grow sales, how to create branding, how much production should we make, etc.
I wanted to keep this article small and less difficult as this is for beginners. I will post more in-depth content as we go through the basics. SO, that's it for today, if you have any doubt feel free to comment down below or ask us on our social media handle.
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1 Comments
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