“The world is now awash in data and we can see consumers in a lot clearer ways.” ~ Max Levchin, Founder of Paypal

 “You can have data without information, but you cannot have information without data.” ~ Daniel Keys Moran

 There are several quotes like this, deciphering the presence of Data science in modern businesses. But still, many people are there unaware of the significance of data and how it is accelerating innovations in this world. Here is everything to apprehend about data science. 

What is Data Science? 

Some people think data is just simple figures and words, but this data’s importance to modern businesses is crucial. The amalgamation of computer science and statistics gave birth to Data Science. Before the invention of data science, nobody knew that we can extract so much information from raw data. In simple words, data science is a technique of extricating useful insights and inferences from raw data by processing it through various tools and software. This data and the analytics drawn from it are the basis for developing new age and smart products. 

Importance of Data science in this era

Data has a big hand in the evolution of modern businesses across every industry. Thus, businesses have identified that data science is not just a technological advancement but it has become a need for every company. A business can converge its attention on the core concerns and take actions based on forecasts made by data. Organizations have access to insights about their target audience through the analysis of raw data. 

Tools for facilitating Data Science 

Artificial Intelligence has produced several tools and software to facilitate the extraction of insights and facts from data. Some of the popular tools are:

1. Python – A python is a programming tool that has several high profile mathematical models and libraries. 

2. MS Excel – MS Excel is the first tool with the functionality of working on complex data, apply formulas, and create diagrams. 

3. SQL Coding – SQL coding is specialised in solving network analysis and graphical interpretations of various datasets. 

4. R programming – The software R is programmed to work on huge data, perform statistical analysis and visualize data. 

5. SAS – SAS offers multiple libraries and packages for statistics to organize and clean your data, which will form interpretations. 

6. BigML – BigML is an interactive cloud-based tool that utilizes machine learning algorithms to do risk analysis, forecasting and modelling. 

Application of Data Science 

The utilization of data science across different industries did not progress overnight. With expanding awareness in the market and cheap availability, data science has maintained its position in every organisation. The applications of Data Science in a diverse environment is stated below: 

1. Banking – The banking system is totally based on figures and hence, it has the greatest benefit of data science. With data and analytics, banks can make predictions and assess the number of customers in different policies they have. 

2. Fraud detection – By analysing databases of millions of people, the finance sector is able to locate the history and essential variables for every person and find out the frauds easily through risk modelling to save the organisation from losses. 

3. Manufacturing industry – Data science is used to optimize production costs, production hours, to yield maximum profits with minimal risks. The data helps the manufacturers to evaluate the methodologies and predict the potential problems of the future. 

4. Healthcare industry – Medical fields such as image analysis, geometric data science, drugs development are those sectors which demand data science at critical points. Data science simplify these processes and make them complete within a short period by helping in testing, assessing and interpreting reports. 

5. Advertisement sector – Websites visitors, button clicks, ad viewers, etc form databases of consumer preferences and help the business to provide such things which gain consumer attention. Product recommendations of various e-commerce platforms are backed by the user search option. 

Job Opportunities 

Data Science is a trending and emerging career option catching the eyes of several students and showing them a prospective and fruitful future ahead. There is an unignorable demand for data scientists in every company and to capture a job position of such high profile, judicious studies and skills are mandatory. Following are some trending job profiles for the trending field of data science: 

• Data Architect 

• Business Intelligence Developer

• Data Analyst

• Statistician

• Data Engineer

• Machine Learning Engineer

• Infrastructure Architect

Salary Insights – It has been assessed that around 46% of data scientists earn between 6 to 15 Lakhs p.a. 

Experience Insights – The studies have shown that 17% of the job requirements are for freshers in data science and 38% of the job demands professionals in data science with experience of more than 5 years. 

Industry Hiring Insights – 41% of data scientists are employed by banking and finance industries, 18% by the energy industry and 11% by pharma and healthcare industry.