What is Data Science?

In 1960s, the term data science was used as an alternative to computer science. Peter Naur in 1960 used it for the first time. Later in 1966 it was said as an independent term.

Data Science is a field by which knowledge is extracted from data in both structured and unstructured way by using scientific methods, processes, and systems. It is similar to data mining. It includes informatics, computer science, operations research, statistics and applied sciences. Data science institute in Delhi offers students to learn data science and apply it practically.

Data science basically, turns data into action. This happens by creation of data products. Diverse data sources are used in this process to extract useful information. It is a combination of many fields, namely database management, data analytics, predictive modelling, machine learning, big data, coding, data visualization, reporting etc.

It is an emerging area of work that is to be followed with many steps: collection, preparation, analysis, visualization, management, and preservation of large number of information.

It has three phases: design for data, collection of data, and analysis of data.

One of the predecessor of data science is CRISP-DM (Cross industry standard process for Data mining). It has six steps: Data understanding, data preparation, modelling, evaluation, and deployment.

Where data science is used?

·       Fraud and Risk Detection:

It was first used by finance companies who were in a threat of debt and losses. While sanctioning the loans, a lot of paperwork was to be followed along with a lot of data. So here Data science comes into action.

·       Healthcare:

Medical image analysis is done with the help of Data science, it helps in research of genetics and genomics, it is used in drug development, it shortens the process of drug discovery.

·       Internet Search

Search engines like Google, Yahoo, Bing, Ask, AOL, and many others use Data science algorithms to provide the best search result

·       Targeted Advertising

Digital marketing is one of the major fields where Data science contributes a lot.

·       Website Recommendations

The user interested products are often displayed in the search results. If we see a particular product on some online shopping website, we may see again appearing on our search results or even on our Facebook ads or Google ads. These companies use this to promote and increase their sales. Amazon, Twitter, Google Play, Netflix, Linkedin, imdb and many more companies use this system.

·       Advanced Image Recognition

When we upload a picture with other people on Facebook and the suggestions start coming about tagging those people. This is the automatic tag suggestion feature used by Facebook and it has face recognition algorithm.

·       Speech Recognition

Some of the most popular examples of this category and Google, Siri, Cortana etc. It is the speech recognition feature that makes it possible to do task on just commanding the system.

·       Airline Route Planning

With the help of Data science, the airline companies have benefits such as:

1.     Predict flight delay

2.     Decide which class of airplanes to buy

3.     Whether to directly land at the destination or take a halt in between

4.     Effectively drive customer loyalty programs

·       Gaming

EA Sports, Zynga, Sony, Nintendo, Activision-Blizzard use Data science to upgrade.

·       Augmented Reality

It is the relationship between Data science and Virtual Reality. Pokemon Go is an example.

Data is gathered from different areas, such as cell phones, social media, e-commerce sites, healthcare surveys, internet searches. This paved the way for Big Data.

Skills required to be a data scientist:

·       R Programming

·       Superb understanding of machine learning tools and algorithms including k-NN, SVM, Decision Forests, Bayes, etc.

·       SQL Database/Coding

·       Good communication skills

·       Hadoop Platform

·       Python Coding

·       Machine learning and Artificial Intelligence

·       Data visualization

·       Good problem-solving skills

A data scientist should understand the business problem first to gather information. Then it is followed by data acquisition from web servers, logs, databases, API’s, and online repositories. Then data preparation is done. This step involves data cleaning and data transformation. Then it is followed by exploratory data analysis, it defines and refines the selection of featured variables that will be used in the model development. Then comes the core step of a data science project, that is, data modelling. Many techniques like KNN, Decision Tree, Na?ve Bayes for best business requirements. Then the visualization and communication are needed to be done. Then the deployment of the model.

Data Science surely has a promising future and good scope. There are specialized Data sciences courses in Delhi available.

Job roles of a data scientist:

·       Data Scientist

·       Data Architect

·       Data Administrator

·       Data Analyst

·       Business Analyst

·       Data/Analytics Manager

·       Business Intelligence Manager

A data scientist or engineer might be some percent of scientist, some of software engineer, and some of a hacker, which is why the definition of the job becomes convoluted. He has to play different roles in different situations.

Duties also include creating machine learning-based tools or processes, such as recommendation engines or automated lead scoring systems. For this knowledge of statistical analysis is must.

Responsibilities of a Data scientist:

·       Data mining and analysing data

·       Developing data models and algorithms best suited to a particular problem

·       Assessing effectiveness of the data model

·       Making use of different data gathering techniques

·       Use modelling to optimise customer experience

·       Develop processes and tools to monitor model performance and accuracy

·       Make right predictions and decisions

·       Doing additional analysis to present results in a clear and systematic manner

Data science training in Delhi offers people to learn such skills. They are trained to tackle such situations and become versatile after the training as there are any role of a Data scientist.

Some of the top companies that hire Data scientists:

·       Accenture

·       Intel

·       Infosys

·       Amazon

·       Tata Consultancy Services (TCS)

·       Cognizant Technology Solutions (CTS)

·       Capgemini

·       Hewlett-Packard (HP)

·       Wipro Technologies

·       HCL Technologies

·       Mahindra Satyam

·       Mu Sigma

·       Wells Fargo

·       Deloitte

·       PayPal

·       Dell

·       JPMorgan Chase

And many others.

Average salary of a Data scientist is INR 607,193 per year. For entry-level Data Scientist, it is INR 510,643 per year.