Data Science—Present and Future

What is Data Science?

DATA science is the application of different algorithms, scientific tools and processes for extracting structured and unstructured data; with the ultimate aim of identifying meaning patterns in it. It is a discipline of creating useful data.

Growing at an immense rate, Data Science is a field which is power-packed with AI technology, Machine Learning and Deep Learning.

With the rapid changes occurring in the worldwide business scenario, there is a dire need for adoption of these new trends and techniques into businesses, by optimizing their data analyzing and data management processes.

Data Science and its Importance

All business structures comprise of, and are surrounded by different data. But unless and until this data is converted into meaningful and valuable information, it is meaningless!

Once the data, whether structured or unstructured, is mined and worked on, the hidden patterns can be identified and later that meaningful data can be utilized for various business functions.

The major importance of Data Science lies in its wide range of uses in almost all aspects of our life; whether assisting us in simple activities like asking Alexa for the weather update to more complicated activities like prognosticate diseases or predicting incarceration rates.

Though all the complexities of life can't be accurately perfected, Data Science nonetheless is the present and future of business operations and processes globally.

Latest trends in Data Science

In this decade, we have been witness to a massive output of data, which has been generated from innumerable sources.The need of the hour is, now, to utilize this vast amount of data.

The art of Data Science is to extract this data, using scientific tools, processes and algorithms, and also to find the meaningful patterns behind it. However, along with these data problems, come innovative solutions. These solutions set different data science trends. A few of the data science trends are mentioned below:

  • Graph Analytics

With the large volume of data available, graph analytics acts as a powerful, yet flexible tool. It uses graphs to analyze complicated data points and understands their relationships.

The graphs help to present the complex data in an abstract and visual way. This makes the reading of data more insightful and easier to digest.

  • The areas where graph analytics can be applied are:
  • Bots that abet fake information on social media can be filtered out.
  • Reduces the instance of cyber financial crime.
  • Helps to quickly find flaws in the power and water grids by analyzing them.
  • Data Fabric

Data fabric is a set of powerful architecture that is adaptive, flexible, and secure. With data fabric, you can manage your data and applications spanning several hybrid multi-cloud environments, unleashing the power of data for your organization. It helps you to modernize data storage by managing your data.

Moreover, your data is fully encrypted and provides the highest level of security. All these benefits ultimately lead to a cutting down of costs for an organization.

  • Augmented analytics

Augmented analytics infuses the features of Artificial Intelligence to help its users to plan a new model. It does away with faulty conclusions and biases and drives better insights for optimized decisions. This helps to boost the Business Intelligence process.

  • Python language for Data Science

Being accepted as the universal language for programming purposes, it is best suited for Data Science and AI

Python is stacked with numerous programming languages and libraries making it an excellent option for working on large sets of data. Some of its most popularly used libraries include—TensorFlow, Scikit Learn, PyTorch and Keras.

  • Extensive Automation in Data Science

The recent innovations in automation are converting the complex AI into easier tasks. The whole process of Data Science which consists of problem identification, data collection, processing, analyzing and delivering outputs, is made much simpler with the addition of “automation” in Data Science.

  • Gigantic Data Storage in the Cloud

With the invention of Data Mining, the size of data has grown tremendously with maximum businesses making their presence online. Thus the demand for data storage has increased, with data science playing a major role in the control and utilization of this vast database. 

This further demands for “cloud storage” solutions. There are various big names which provide vast storage options such as Microsoft, Google and Amazon. They offer extensive cloud computing solutions along with high scalability and zero downtime.

New Job Opportunities with Data Science

The current day’s business world and overall organizations are turning increasingly towards analytics. Organizations of all shapes and sizes have been collecting huge amounts of data in recent years. 

Hence there is an enormous demand for people by global businesses today, who can mine and interpret their vast storage of data. 

These are the “data scientists” who operate between the business and the IT world. They work on large volumes of data and analyze and interpret it for the businesses to leverage it into actionable outcomes.

Let's talk about some most in-demand job titles and career options in Data Science:

  • Data Scientist

A very lucrative job option in the Data Science field, the Data Scientists study business data and develop a hypothesis to understand and interpret it into an understandable pattern.

These patterns are further studied to know the impact they will have in the future on the business. Data Scientists also help come up with solutions in case the company deals with these impacts in the future.

  • Data Mining Engineer

They are the expert Data Miners who analyze the data of their company, along with the information gathered from the third party. Apart from examining the data, they create sophisticated data for analyzing the data further when required.

  • Data Architect

They create blueprints and define policies, processes, technologies and models that data management systems use to collect, organize, store and access companies’ data.

  • Business Intelligence Analyst

They study and analyze data to help figure out the market and business trends that develop clarity about the company’s standing. In other words, the Data Analysts automate data to help you understand what is going on in your business and help you plan for the future by improving the company's decision-making abilities.

The right set of qualifications are required for enjoying the numerous job opportunities available worldwide in the Data Science industry. And the demand for these qualified individuals will just continue to rise as more and more businesses and organizations become aware of the gigantic role played by Data Science and AI in global development. 

In fact, those who are already in data science roles can see their career grow and salaries increase shortly. According to Payscale, the average income of a Data Scientist in India is Rs. 824562 per annum.

Snable's data science training program

Helping people gain their dream jobs.

If you are looking for a career in data science, you can look forward to a lucrative one.

We, at Snable an IT company in Nagpur, help you in your journey to becoming a data scientist, with our world class training and skilling-up course in Data Science.

In just 6 months, our Data Science course at Nagpur, helps you to become an expert at understanding, analyzing, and interpreting data. You also become proficient in utilizing the latest tools and techniques.

Learning Data Science is essential in today’s IT landscape. Get ready to Master the Science of DATA!

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