Understanding Data Science

What Is Data Science ?

Data science is about collecting the data from different sources and processing it to form data sets that can be transformed into statistical models/analysis or try make predictions basis the data in hand. Based on these collected information’s not only data driven products are made but also this information can be communicated to other data scientists for reports, visualisation and blog posts.

In a nutshell Data Science is collating information and processing it to understand patterns or behaviours which can later be used to make various applications.

Before we look at the skills required for a data scientist the two inherent qualities a data scientist must have is passion for numbers and deep interest in following different patterns that data has.

Skills that a data scientist should have?

  1. Know what questions to ask?
  2. Sound data interpretation skills.
  3. Understanding the structure of the data.
  4. Knowledge of Statistics.
  5. Data scientist work in team.

To understand the importance of each one of these skills let’s take an example, if you are working on an online advertisement, to run an advertisement you should know what kind of people are visiting your website what interactions they are doing with your website. So once you design an add then you also need to understand what time of the day most of the visitors are coming to your website, duration of the ads they are running, once you are aware what questions need to be asked you will have to interpret this data and understand how it is getting stored in the database once done.

So if this sounds like too much don’t get bogged down as data scientists work in team and it’s not necessary that you should know all the aspects of the project, but it’s imperative to have command on what you are assigned to do.

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“Industries that you can expect to contribute being a data scientist”

1. Entertainment platforms like Netflix:- Where the movies are recommended to the users basis the data captured about what they like to watch.
2. Social Media:- Recommending new connections, constructing online feed and whom to follow suggestions.
3. Web apps:- Like Uber, data collected is not only used to improve user experience but also to share lot of findings that are collected offline to share on blogs.
4. IT:- This is single biggest industry using data scientist for own as well as outsourced services.
5. E-commerce:- To suggest products basis their interest and interactions on website.
6. Unconventional sectors:- Urban planning, genetic engineering, Astrophysics etc.

Where ever there is data to churn and extract relevant information Data scientists are of use, so the possibilities of both churning the data and it’s applications are very vast.

Tools for Data Science

Most commonly used tool for data science is Python Programming & R.

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