I am often caught between whether I should be a Data Analyst or Data Scientist and I’m sure I am not the only one. Some people go as far as mixing Data Analysis with Business Analysis To solve this dilemma, I decided to take the help of this online course I found on Heels and Tech (input link to Data Analysis landing page). The course helped me in clarifying the difference between Data Analyst and Data Scientist and now, I am finally able to find out whether I should be a Data Analyst or Data Scientist.
I would like to break things down in a simpler way.
First of all, what is Data?
Data is the backbone and heartbeat of any business. It helps you understand your customers and improve your processes. Data scientists/Analyst use their analytical skills to transform data into profit for every organization.
Who is a Data Analyst?
A Data analyst are responsible for identifying business problems and using various tools and techniques to solve business related issues.
Who is a Data Scientist?
A Data scientist take their understanding further than data analysts by building models against various factors that lead to success, they harness the power of data to answer business questions and drive smart decisions. Data scientists will use the best statistical and machine learning tools to convert data into actionable insights. They analyze both structured and un-structured data in order to create new value for your business.
Now, you are wondering, what exactly is structured and unstructured data?
Structured data is highly-organized and formatted in a way so it’s easily searchable in databases. Examples include: Names, Dates, Addresses, credit card numbers, stock information, geolocation, text file, spreadsheet which can be extracted from a Database.
Unstructured data has no pre-defined format or organization, making it much more difficult to collect, process, and analyze. Examples include photos and videos, text. Mobile activity, social media activity, satellite imagery, surveillance imagery – the list goes on and on.
Unstructured data is most often categorized as qualitative data, and it cannot be processed and analyzed using conventional tools and methods.
Structured data has the advantage of being constantly searchable, which means that all learner information can be found whenever needed. Unstructured data provides valuable insights into a person’s hobbies an interest. Talk about merging a users activity on Instagram and on google, thereby making a decision.