Data Science & Data Analytics
As we all know that the use of internet in the world is increasing day by day every individual is now some how related to the internet even if that person wanna use it or not.
All the tech giants like Google, Facebook, Amazon etc are hungry to expand there company as much as possible every search we do in google, every post we liked in facebook or every product we searched in amazon is tracked by the companies which help them to generate more revenue & expand their empire. Now you will think how do they get benefited by tracking our data? Let me give you an simple example to explain this thing; Let's say you are a music lover & you searched for an earphone at any online shopping site such as Amazon or Flipkart now you will see many products which includes some features you want and some features which you don't want & some are in your budget and some are not; now you specifically select an earphones of company XYZ which you checked for a while but then you realized that you have to use that money for something else & you did't buy that earphone. But when you check some other website the advertisement of that earphone keep on popping up in front of you & you get temped to buy that earphone. Now showing you that earphone again & again you lose your patients & buy that earphone. That was an rough example of how your data was so much important & how they manipulated you to buy that product by showing you that thing again & again.
The world of all the companies is driven by data as we know it & the workforce behind it is full of Data Scientists & Data Analysts. Now a days all the companies use data science & data analytics to make data a friendlier entity & drive there business to success.
Now let us see various aspects of Data Scientist & Data Analytics
* Data Science :
Data science is a huge field which focused on basically finding some actionable insights from a large sets of raw & structured data. Goal of the data scientist is to ask questions & locate wherever it can make use of the data & know where the data can be put forth for, answer specific questions using the data, find the right questions that he need to ask towards the data as well. So data scientist are basically concerned with all the data that moves into their hand from the data engineers who engineer all the data & bring in the data to the form & these data scientist pretty much go on analyzing data most of the times performing certain calculations, analysis & eventually it apply machine learning , AI etc to make sense of the data drive future trends and whatnot so much more & later it pass to Data Analytics.
* Data Analytics :
As well mentioned that data engineers drives the data into the company where data scientist take the raw data & convert it into information & this information is used by data analysts who go on processing these data & performing lot of statistical analysis on all the existing data sets which provided by the data scientist or they pick up something new & perform same as well. But analysts also concentrate on creating methods where our data data can be visualized but it make's it more easy to understand.
Main difference between data scientist and data analytics is that data analytics is a part of data science.
* Data Scientist VS Data Analytics :
Data Scientist |
Data Analytics |
Data
Science is an umbrella term for a group of fields that are used to mine
large data sets.
|
Data
Analytics is a more focused version which can be considered part to the large
process.
|
Data
Science isn’t concerned with answering specific queries with respect to data.
|
Data
analysis works better when it is focused, having questions that need answers
based on existing data.
|
Data
Science produce border insights that concentrate on which questions should be
asked.
|
Data
Analytics emphasize discovering answers to questions being asked at the
movement.
|
The
Scope of the Data Science is Macro.
|
The
Scope of the Data Analytics is Micro.
|
The
Goal of the Data Science filed is to ask the right questions & get the
right answer from the data.
|
The
Goal of the Data Analytics is to find some actionable data where you can make
sense out of it & drive business decision.
|
Field
for Data Science :
Machine
Learning, AI, SEO etc
|
Field
for Data Analysis :
Health care, gaming etc |
To
become Data Scientist person should have knowledge of :
*Python,R,SAS,Scala
*Working
with Unstructured Data sets
*BackEnd
Development
*Knowledge
of ML & DL
|
To
become Data Analyst person should have knowledge of :
*Knowledge
of Statistics
*Understanding
Python & R
*Data
Wrangling
*Knowledge of Pig & Hive |
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