Data Science

The Exclusive Combination of Artificial Intelligence and Machine Learning is Driving Transformations in Data Science Platforms

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Data science tends to incorporate a plethora of different job titles across several organizations and industry verticals, right from research scientist to analytics officer. As per a survey conducted by IBM, the demand for data scientists is likely to soar twenty-eight percent by 2020. Rise in use of both unstructured and structured data in different end-user sectors is heightening the adoption of big data. For example, keeping in tab with Seagate Technology PLC, the global size and capacity of data is projected to proliferate to forty-seven zettabytes and one sixty-three zettabytes in 2020 and 2025, correspondingly, from twelve zettabytes in 2015.

According to Allied Market Research, the global data science platform market is projected to cite a substantial CAGR from 2021 to 2030. The fact that data science platform facilitates all four phases of the data science production track such as DevOps, data preparation, business delivery, and model development has made it a preferred choice in several verticals. Furthermore, the active utilization of machine learning and data science is propelling the telecommunication industry. The telecom organizations happen to function with full data flow as they fully operate with huge infrastructures and communication channels. Evaluating and undertaking this data with the aid of data science platforms has turned out to be one of the most hands-on solutions.

At the same time, beyond mere computing, cloud computing corporations are also providing full-sized solutions for Data Analytics. For example, Google Cloud doles out a solution called BigQuery, a mountable data warehouse providing data scientists with the capability to accumulate and evaluate petabytes of data, everything in a single platform.

The key players are offering new-fangled platforms that can be set up as a single-tenant solution on Private Cloud, AWS, Azure, or GCP. In June 2020, Aigenpulse brought forth a new data intelligence solution crafted to accelerate drug development. Aigenpulse platform makes use of the up-to-date machine learning and AI tools to supply innovative analytics to prop up precise decision-making. Moreover, scientists can develop a number of datasets at the same time, making them free for higher-value duties and responsibilities.

NITI Aayog has recently come up with NDAP (the National Data and Analytics Platform). The platform intends to regularize access to public government data by driving the information convenient, approachable, intraoperative, collaborative, and accessible on a user-friendly platform. As per a press release, NDAP happens to lay out foundational datasets from various government supports and introduces tools for visualization and analytics. All database on the platform can be transferred to any other source and coalesced freely.

The official launch sticks to a beta release of the platform in August 2021 that laid out access to a restricted number of users for proper evaluation and feedback. NDAP takes recourse to a use-case-based method to make sure that the datasets presented on the platform are custom-made to the prerequisites of data users from several fields such as the private sector, academia, government, and many more.  The database are homogenized to a common diagram, which makes it easy to unify datasets and ensure cross-sectoral study.

One of the officials from National Institution for Transforming India noted that one of the prominent features of the National Data and Analytics Platform is that it makes the top foundational datasets independent with each other, allowing easy cross-sectoral breakdown. Rise in high-end digital technologies are rapidly transmuting societies and economies, with massive implications for daily operations from government. This exclusive platform is a serious milestone, which intends to aid the country’s progress by facilitating proper decision-making clouts. NDAP will also strengthen the government’s endeavor to reinforce the data ecosystem.

Covid-19 scenario-

Here, it’s worth mentioning that the outbreak of the pandemic has had a positive impact on the global data science platform market. Rise in data applications, the growing trend of remote working culture, and emergence of cutting-edge data science platform solutions gave way to upsurge in demand for data science platform in business organizations. It played an important role for the proper operation of sectors such as manufacturing, BFSI, healthcare, and many more.

The importance of the platform, during the global health crisis, has become obvious ndeed. The lockdown across the world compelled the majority of organizations to creep up on digitalization for smooth procedure of work. Especially, with the companies incorporating intelligence and automation into their businesses, the data science platform industry received even a stronger boost.

Keeping in line with a survey conducted by Flexera, around fifty percent of organizations have planned to heighten their cloud usage in the last two years, throughout the crisis. The numbers in India are even more propitious, with the major sectors such as education, healthcare, entertainment, education, gaming, and healthcare constantly inclining to the cloud to confirm pliability and business continuity. This, in turn, has resulted in greater usage of the data science platform.

Koyel Ghosh is a blogger with a strong passion and enjoys writing on miscellaneous domains, as she believes it lets her explore a wide variety of niches. She has an innate interest for creativity and enjoys experimenting with different writing styles. A writer who never stops imagining, she has been serving the corporate industry for the last three years.

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