Introduction to Data Science - Unit : 1 - Topic 1 : INTRODUCTION TO DATA SCIENCE

 

INTRODUCTION TO DATA SCIENCE:

Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. Data science uses complex machine learning algorithms to build predictive models.

The data used for analysis can come from many different sources and presented in various formats. Data science is about extraction, preparation, analysis, visualization, and maintenance of information. It is a cross disciplinary field which uses scientific methods and processes to draw insights from data.

Data Science lifecycle

A data science lifecycle is defined as the iterative set of data science steps required to deliver a project or analysis. There are no one-size-fits that define data science projects. Hence you need to determine the one that best fits your business requirements. Each step in the lifecycle should be performed carefully. Any improper execution will affect the following step, ultimately impacting the entire process.

Phases	Description
Identifying problems and understanding business	Discovering the answers for basic questions including requirements, priorities and budget of the project.
Data Collection	Collecting data from relevant sources either in structured or unstructured form.
Data processing	Processing and fine-tuning the raw data, critical for the goodness of the overall project.
Data analysis	Capturing ideas about solutions and factors that influence the data life cycle.
Data modelling	Preparing the appropriate model to achieve desired performance.
Model deployment	Executing the analysed model in desired format and channel.

 

Roles in Data Science

Applications of data science

Presently application of data science is very vast. You can see it everywhere in your daily life. Some prominent examples are given here.

Ø  Internet Search Engines

Ø  Speech Recognition

Ø  Recommender Systems (YouTube, Netflix, Amazon)

Ø  Self-driving Cars

Ø  Image Recognition

Ø  Comparative analysis of Price

Ø  Fraud and risk detection

Ø  Gaming

Ø  Robotics

Ø  Airline route planning