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In recent years, the popularity of data science has surged drastically. 

Industries such as agriculture, retail, risk management, fraud detection, marketing, media, and business analytics are the few among many to adopt data science as their integral part. 

Data science has proven to be a marvelous revenue generator. In the year 2015, it helped organizations generate $122 billion profit and is expected to be responsible for $274.3 billion by 2022, globally. 

Data backed business decisions have made organizations realize the value of data science and the right expertise to apply it. 

There is no doubt that the future of data science is very bright. Let’s understand in more detail.

What is Data Science?

Primarily, data science handles processes and systems used to draw information or insights from a massive quantity of data. 

Data science is extremely vast and involves the application of several statistical procedures. It is more of an exaggerated form of data analysis, such as statistics, data mining, predictive analysis, etc. 

How Will Data Science Rule in The Future?

Data science is applicable and vital to every business churning out a high volume of data. The data we have today is just a minor fraction of what it could be in the future. Let us see how data science will become inevitable in future. 

1- Organizations Will Adapt to Business Data Management

In recent years, a huge explosion of data was observed, which was held back both by organizations and consumers. By now, each person on earth is generating an average of about 1.7 MB of data per second, and the stored data is reaching 44 ZB.

Every business, organization, and consumer is generating data constantly and is expected to generate even larger data volumes as the IoT (Internet Of Things) devices will come into use in the near future. 

For example, by the end of 2019, consumers would have spent around 103 billion U.S. dollars on smart home systems, and the figure is expected to rise 157 billion U.S. dollars through 2023. Similarly, the industrial Internet of Thing’s market size is estimated to reach some 77.3 billion U.S. dollars by the end of this year.

Companies like an online grocery shopping can collaborate with a CPG data technology company to offer health and wellness information directly to its consumers.

Apparently, it will raise the need of data scientists for analyzing the data and acquiring the vital insights from it.  

2- The Regulations of Data Privacy will Still Exist

Data science also deals with using collected data in a beneficial way that meets privacy clauses. 

These days, consumers are more cautious about the consequences of sharing the data and the breaching of data. They are well aware of the GDPR that allows consumers to request organizations to delete certain data types. 

Hence, entrepreneurs cannot take the risk of handling such data casually. This is where the role of data science and scientists becomes more prominent. 

3- Data Science Will Keep Evolving

The magnitude of opportunities for data scientists will keep evolving in the near and distant future. The role of data scientists may be fragmented into multiple fractions, according to their specialization in different niches. Data scientists may be asked to focus on a specific area and hold expertise in the same. 

The specialization in areas could be anything from data mining and statistical analysis, cloud and distributed computing, data management and architecture, business intelligence and strategy, ML/cognitive computing development, data visualization and presentation, market related data analytics, etc. 

This field is highly intricate and sophisticated, and therefore the in-demand jobs, which involve data science like data scientist, data engineer, business analyst, research analyst, financial analyst, and others, require a degree in data science.

As data science requires more specialized skills, such a degree is an added benefit to cope with this ever-increasing and ever-challenging field. 

4- Data Science Will Have Extended Value to Business

Data science’s ability to extract more information from basic data is an added advantage to businesses. 

For example, a customer’s basic data in a customer service system can be used to draw more data by an employee, like rating of their business in different surveys by a particular customer, their retention period on a certain product page, return history, etc. 

This opens a source to understand the customer behavior, interest and feedback, which can be further used to create a business strategy or improve the services of an organization. 

In fact today, there are many tools available that are being used to analyze the performance of a business. For example, a comprehensive analytics tool uses data to make it easier for marketers to make measurable decisions. It helps to recognize bad traffic, perform audience analysis, check the performance of each page, and perform automatic conversion of real-time sources using an array of data.

5- Sources of Fresh Data Will Keep Growing

The concept of IoT is not new to the market but is not more common these days. But in the coming years there is a possibility that the interconnection between the devices will grow.  

This will further increase the need for collecting data from a more distinct range of sources, such as retail environments, manufacturing streams, employees, vehicles, etc. Certainly, the need for data science will keep growing.

Conclusion

With the above-mentioned factors, it is not difficult to understand why the need for fresh data scientists and data analysts is growing each year. It is not just the data scientists and data analysts, but every bright mind in related fields needed to fill the gaps. 

In the next few years, there will be a torrent of data, which will prove to be a propelling factor for the data science model, creating more scope for the data scientists and more possibility of using data innovatively.   

Summing up the whole article, you can be sure that the future of data science is bright and going to last for the next several decades to come.