22% of the analytics industry is based on big data. Analytics play a major role in businesses, as they deal in the analysis of data and find why anything happens in a concern. But when this analysis is coupled with algorithms and machine learning and finding insights from massive amounts of data it becomes data science.

It is all about obtaining data from several sources and then, mining and exploring the same to find information hidden in it. Usually these days it is used for predictive modeling, to deduce future problems and their solutions.

TOOLS AND TECHNIQUES INVOLVED:

There is an entire pipeline of the procedure involved in it. That is why there can be different roles of data scientists like data engineer, data architect or algorithm developer. The first step is of collecting the data using database management and storing, then it is about cleaning and scourging the same of any impurities and gaps, followed by exploring and modeling them into algorithms and lastly, the results are communicated and presented to the management.

There are several tools involved in this entire scheme:

• SQL or NoSQL
• Hadoop, Pig & Hive, Apache Flink and spark.
• Python, R, SAS
• Python libraries like Numpy, Matplotlib etc.
• R libraries like Dplyr
• Statistical models
• Linear algebra and calculus

All these tools techniques are to be accompanied by strong analytical skills and communication skills. Also, one should be curious and acknowledged with industry details.

APPLICATIONS OF DATA SCIENCE:

Data science is showing phenomenal growth in the last few years and is expected to grow like never before. Data science is used in the technology world extensively like creating search engines, robotics, and recognition systems.

But data science will have a great scope in many other industries and sector. Although it may take a few more years for data science to reach all the sectors it will be worth the wait. It has capabilities not just to find the solutions of today, but also can find solutions to future problems.

Sectors that can make use of data science are:

• Banking and finance: It is one of the very first industries which has accepted data science as a tool. It is used by big banks, trading firms and investment firms. Here it is useful in knowing the trading trends of financial market, mitigation of fraud and laundering and also knowing the investment pattern of customers.
• Agriculture: agribusiness can use data science for predicting weather patterns, yield, demand, prices of crops etc.
• Public health care: big data can help to predict a lot of issues like child mortality, the need for hospital facilities, malnutrition rate, number of doctors needed etc through various data sets of annual health reports.
• Education: one of the most sectors to concentrate on and ask questions like why such low numbers of government schools, why students drop out of school and why the amount of revenue provided is not enough? All these questions can be answered using datasets from government surveys.

Well, one thing is sure that data science has a major scope if used properly and timely.