What is Data Science?
Since the dawn and evolution of humans on the planet earth, data has always been an integral part of everyone’s lives. Even when the humans used to live in caves and lived simple lives, they used different kinds of languages to store and pass on data among themselves. As the humans evolved and worked on towards the betterment of their lives, the importance of data in every domain of their lives was realized and eventually it led to magnificent inventions in the field of information technology that was used primarily to store, generate and transfer data pertaining to different walks of life.
However, after the dawn of the 21st century world has seen an immense generation and storage of data in almost every database, gadget, and other devices in every nook and corner of the world. This surge of data was not expected. The high velocity of data being generated today can be noticed by realizing that our digital footprint has expanded at a huge rate since the last decade. During 1995, we had only 130 billion gigabytes, which has expanded today to more than 40 trillion gigabytes.
There are different terminologies of Data Science available on the internet. However, the definition by the professors at the MIT (Massachusetts Institute of Technology) encompasses it beautifully within few words and it is stated that “Data Science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. “
This definition elaborates this new domain perfectly which normal data science enthusiasts often have hard time understanding it easily. Additionally, it emphasizes the importance and application to almost every sector of the corporate world because this data revolution has touched almost every aspect of our personal and professional lives and the benefit of learning from the data is important more than ever. There are many applications of Data Science in almost every domain like marketers who can devise strategies for their next marketing campaign and even Finance department can analyze and visualize the data to catch loopholes in the operations of the company to generate as much profit as possible via the associated data.
Data Science in the Corporate World
This amount of data is facing talent shortages of Data Scientists around the world. A report by McKinsey Global Institute warns of these shortages. “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the big data to make effective decisions”.
Given the shortage of data scientists, the employers who recognize the importance of data scientists being employed in their company are willing to pay top dollar for the talent. According to U.S. Bureau of Labor statistics, the average data scientist’s salary is around $100,560. They believe that such high salaries of data scientists are a proof that future for Data Science is quite bright, even during the recession period we are in nowadays.
Following are some of applications of Data Science in the corporate world:
- Better decision making via numerical data
Numerical data is the bloodline for any organization. It not only helps in assessing the trends via historical data but helps in better decision making as well. However, most of the data is unstructured i.e. data in the form of audio, video and log files. So, standards need to be set by the relevant departments related to pulling numbers and statistics though data science into structured data and applying relevant predictable models to simulate variety of possible outcomes to counter the business problem at hand.
- Improving products and services
Data science can be used in improving the reach of existing products and services to the potential markets, making comparisons to the products of the competition and even helps in analyzing and helping out with the feasible launch period of the products and services for ensuring success in the target market.
- Assisting the Human Resource Department
Selection of the right candidate for a particular position has often been a tedious job for the Human Resources professionals. As Data Science has revolutionized almost every sector of an organization, so it has improved the H.R. department as well. Data Algorithms like clustering helps in clustering or grouping data points related to the applicants in the search of the best possible candidate.
- Training Staff
Data science helps a great deal in training staff by pulling insights that employees need to know and populating the right information.
- Discovering the target audience
Data scraping is an important part of discovery of target audience. Although tabulated / structured data is an important part, however scraping social media feeds, website visits and other parts of the web helps too.
By using data science, one can collect vital information of different types of customers and try to relate them for tailoring services and suggesting your own products to increase sales and profits for the organization.
Lack of Understanding by the higher ups
There are still steps needed to convince the higher management to realize the importance of structured, semi-structured and unstructured data in the organization to understand it’s worth in not only generating useful trends and patterns via visualizations but also to predict the next course of actions via using supervised and unsupervised Machine Learning Algorithms like Regression, K-nearest neighbor, density estimation and recommendation analysis.
SAP, the leader in data and analytics, understands the problem this problem very clearly and believes that the demand of professionals from the data science domain may exceed the supply in a year by 250,000. A similar survey conducted by the KPMG found that almost 85% of the respondents did not know how an organization to resolve it’s business problems via all kinds of data present in the RDBMS of their companies.
Conclusion
In the first part of the series of data science for newly launched informatics portal Devops, I touched only the surface of what data science and it’s application in the corporate world. Like other sciences, Data Science is a very broad subject and it has many branches which will be discussed in the next article.
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