Data Science: The Future

What is data science? 

Data science, in simple words, is the study of data. Mainly, it deals with the developing methods of recording, storing, and analyzing data to extract useful information effectively. The vision or long-term goal of data science is to gain insights and knowledge from any type of data — both structured and unstructured. 

In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics in them. Thus, data science is all about the present and future. That is, finding out the trends based on historical data can be useful for immediate decisions and ways to find the patterns which can be modeled and can be used for future predictions to see what things may look like in the future accurately. 

Why choose data science? 

Data Science has turned out to be a necessity for companies due to the amount of data generated and the evolution in the field of Analytics. To make most of their data, companies from all domains may be Finance, Marketing, Retail, IT, or Bank. All are looking for Data Scientists. This growth has led to a massive demand for Data Scientists all over the globe. With the kind of salary that a company has to offer and IBM is declaring it as a trending job of the 21st century, it is lucrative. This field is such that anyone from any background can make a career as a Data Scientist. 

What is seen in Data Science? 

Machine Learning: Machine Learning is the way to learn how to visualize the data, which involves algorithms and mathematical models, chiefly employed to make machines learn and prepare them to adapt to everyday advancements. These 

models can also help to find the behavior and helps to predict the future. 

Big Data: Humans are producing too much data in the form of clicks, 

orders, videos, images, comments, articles, RSS Feeds. These data are generally unstructured, and it is often named as Big Data. Big Data tools and techniques mainly help in converting this unstructured data into a structured form. 

Skill sets required: 

Python coding: Python is majorly preferred to implement mathematical models and concepts as it has libraries/packages to build and deploy models. R-programming language can also be used as an alternative

MS Excel: 

Microsoft Excel is considered an essential requirement for all data entry jobs. It is of great use in data analysis, applying formulae, equations, diagrams out of a messy lot of data. 

Hadoop Platform: 

It is an open-source distributed processing framework. It is used for managing the processing and storage of big data applications. 

SQL database/coding: 

It is mainly used for the preparation and extraction of datasets. It can also be used to solve problems like Graph and Network Analysis, Search behavior, fraud detection. 

Technology: 

Since there is so much unstructured data out there, one should know how to access it. It can be done in a variety of ways, via APIs, or web servers. 

Techniques 

• Mathematical Expertise: Data scientists also work on machine learning algorithms such as regression, clustering, time series. which require a very high amount of mathematical knowledge since they are based on mathematical algorithms. 

• Working with unstructured data: Since most of the data produced every day, in the form of images, comments, tweets, search history, is disorganized. It is a handy skill in today’s market to know how to convert this unstructured into a structured form and then working with them. 

Career Opportunity/option : 

In a world where 2.5 quintillion bytes of data is generated every day, a professional who can organize this humongous data to provide business solutions is indeed the hero! Much has been spoken about why Big Data is here to stay. Building on what’s already been written and said, let’s discuss Data Science career opportunities and why ‘Data Scientist’ is the decent and passable job title of the 21st century. 

According to the Harvard Business Review, “it is one of the high-ranking professionals with the training and curiosity to make discoveries in the world of AI and Big data.” Therefore, it is no surprise that Data Scientists are coveted professionals in the Big Data Analytics and IT industry. With experts predicting that 40 ZB of data will be in existence by the year 2020, Data Science career opportunities will only shoot through the roof and regarded as the best. There is a shortage of skilled professionals in a world, and again, increasingly turning to data for decision making. This has also led to the enormous demand for Data Scientists in start-ups and well-established companies. A McKinsey Global 

Institute study states that “by 2018, the US alone should encounter a shortage of about 190,000 professionals with great analytical skills. With the Big Data wave showing no signs of slowing down, there’s a rush among global companies to hire Data Scientists to manage their business-critical Big Data”. 

So, we can conclude that there is broad and giant scope in data science and machine learning; we can regard it as our future.