Introduction

It will come as a surprise for you to study how much data science notifies your life every day. Marketing campaigns, Amazon recommendations, Siri, uber, sites related to price comparison, image recognition and gaming all are empowered by data science to varying degrees.

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And, you may have heard about data science all throughout last year and you may not really get a clear picture of what data science really is. It is actually termed as an interdisciplinary field in which systems and processes are utilized to extract insights or knowledge from the data.

People who are data scientists gather, handle, interpret and analyze huge volume of data with a variety of applications. In 2016, Data science is estimated to reach a significant status as a large number of organizations are realizing how vital this field is to notifying their decisions in the day-to-day life.

In 2018, with the trends in marketing estimating a surge in an overall requirement for data-savviness, personalization, and advertising, it is evident that data science won’t go anywhere for a long period.

Data Science Trends

The top 10 technology trends for the year 2018 provide an overview of several major data science trends for the year 2018. The adoption of AI(Artificial Intelligence) is evident today in almost all the decision-making applications and business systems.

Over the next several years, we can witness a steady rise in services and apps driven by artificial intelligence. Almost all the managed software platforms such as the ERP are looking to get their present systems integrated with AI for value addition and enhanced performance. This trend includes the utilization of virtual services and digital assistants.

The intelligent things are smarter, semi-robotic versions of equipment and regular gadgets to make our lives easy. The immersive experience connected with virtual reality and augmented reality is already transforming the world around us. The interaction between machines and humans will enhance as research breakthroughs in virtual reality and augmented reality will come up.

There are various technologies that will coordinate with the foundations of big data and data science and broaden such industries into numerous new spaces that are starting to be understood and appreciated.

Future of Data Science

Data science is a comparatively new field, with “data science” term being coined in 2001, but the future of data science looks extremely bright. Today, data science has grown immensely across multiple organizations which include energy, finance, government, and travel. Universities recognized the significance of providing programs and courses in data science.

A large number of people are looking forward to a career in data science as it promises a long-lasting career and highly paid jobs. People are opting for training in data science to gain comprehensive knowledge in this field and make a career in this area.

Companies are also looking for data science professionals with complete expertise in it and lot of job opportunities are getting generated day-by-day as all kinds of organizations are starting to use data science. Wanted Analytics conducted a study recently and it specified that only 4 percent of 3,32,000 IT professionals in the US at present possess the skills needed to become a data scientist. This shows the demand for data scientists in the present IT market.

The high increment in job opportunities is because organizations now understand the significance of analyzing the data for the growth of the industry. The chief economist of Google, Hal Varian stated that “the capability to take data-to-be in a position to interpret it, to process the data, extricate the value from it, to envisage it, to make it understandable for others-that is going to be an extremely vital skill in the years to come..”

The ways in which data science can add value to the business of the organization is empowering officers and management to make better decisions, directing the actions depending on the trends which in turn guide in defining the goals, provoking the staff to adopt best possible practices and put attention on the topics that matter the most, recognizing the opportunities, decision making with evidence that is data-driven and quantifiable and testing these decisions, refining, and identification of the targeted audiences and recruitment of most eligible data science professionals for the organization.

Conclusion

Ultimately, data science targets to find and bring out knowledge which is actionable from the data and this can be utilized to make predictions and decisions, not to just describe what is happening. Data science can also be applied to many knowledge domains like computing and this can be termed as the most exciting part of data science. From a very long time, biology, chemistry, physics and other disciplines of natural science were practicing their own versions of data science. Definitely, data science can add value to the business of the organization by adding insights and statistics across the workflow.

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Introduction It will come as a surprise for you to study how much data science notifies your life every day. Marketing campaigns, Amazon recommendations, Siri, uber, sites related to price comparison, image recognition and gaming all are empowered by data science to varying degrees. And, you may have heard about data...