What is Data Science?
The term ‘Data science’ has been one of those subjects that has time and again been heard by most, but minimum thought has been put into it due to the perception behind it being, a complex term. The very term ‘Data’, needless to say refers to information or knowledge, and the term ‘science’ holds a key role here. Data science is the study of extracting knowledge from data. Signal processing, statistical learning, machine learning, computer programming etc are the many fields that come under the category of Data science.
'In simple term we have taken a large amount of data and analyze it and then we take a decision.'
Who is a Data Scientist?
The core job of a data scientist is to understand the data, extract information and create meaningful data products out of it. There are various technicalities involved in a data and despite software and hardware constraints, a scientist with all his expertise and knowledge has to crack the most complex data problems.
There are several social media websites, where billions of people around the globe interact and utilize these platforms. Ever wondered how have so many accounts and their data been kept secured and stored? Ever wondered how many accounts have been left underutilized or unused?
This is where the data scientist steps in and uses his skills of getting an insight to the data, understand theories and begin applying them. In this scenario, understanding the domain expertise becomes very crucial.
Roles and technologies of platforms
There are different technologies that have roles to perform in the area of data performance. These are the technical sets or stacks that are required to step into different levels.
Tech 1- ETL, Storm, Scribe, Flume.
Tech 2-R, HIVE, PIG, PYTHON, JAVA, MAHOUT.
Tech 3- Machine learning.
Tech 4- HADOOP.
Tech 5- Dashboards, Web apps.
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