Data science is study of data that involves emerging methods of recording, storing and analyzing the data, to easily extract the needed information to take the necessary decisions for business. The phrase ‘Data Science Platform’ can be described as a software including a variety of technologies for advanced analytics uses and machine learning. It allows data scientists within a single environment to discover actionable insights from data, plan a strategy, and also in communicating the collected insights throughout an enterprise. As data science projects involve a number of different tools designed for the modeling process, it is important for the data science teams to have a centralized location for collaborating easily.
Capabilities of Data Science Platforms
As per the blog published by Research Dive , the prime data science platforms provide the flexibility of open source tools and the scalability of adaptable compute resources. A quality data science platform incorporates best practices that have been refined and developed over years of software engineering. Version control is one of those best practices, which allows the data science team to collaborate on projects without losing already done work. In addition, a good data science platform will line up data architecture of any type. Also, to better facilitate the collaboration, a data science platform also helps the data scientists to unburden low-value tasks, such as running reports, reproducing past results, and scheduling jobs.
Application Areas of Data Science Platforms
Data science platforms offer collaborative and flexible environments by enabling the organizations to integrate data-driven decisions into customer facing and operational systems. This improves the customer experience and also enhances business outcomes.
The active use of data science and machine learning is boosting the telecommunication industry. The telecom companies operate with intense data flow as they majorly function with vast communication networks and infrastructures. Analyzing and processing this data with the help of data science platforms is one of the most practical solution.
Data science platforms has also significantly helped in the emergence of wearable and applications that can monitor patients on a constant basis. This helps in preventing potential health problems. When it comes to finding cure, data science platform also plays a crucial role in the progress of pharmaceutical research. Thus, to develop cure, machine learning algorithms are used to analyze and extract biological samples from patients.
The Banking, Financial Services and Insurance (BFSI) sector has a huge amount of data that is stored. Thus, to analyze this massive amount of data, it is now essential to incorporate the implementation of big data analytics. In BFSI sector, the importance of data science platform is crucial and hence it is integrated into all decision-making processes that are based on actionable insights from customer data.
Forecast Analysis of Data Science Platform Market
Global market for data science platform is projected to witness a significant growth during the forecast period from 2019 to 2026. Several factors such as adoption of artificial intelligence, increasing demand for public cloud, explosive growth of Internet of Things (IoT) applications, machine learning, rise and revolution in demand of big data are expected to drive the demand for data science platform market growth.
Lack of domain expertise and data breach are some of the major restrains for the growth of data science platform market. Data science is a novel field to many and there are a number of professionals that are not that experienced in the respective field to handle the complex issues. Hence, the availability of domain expertise in the respective field is considered to be the major restrains of the data science platform.
Increasing adoption of data analytical tools is giving significant uplift to the growth of the global market in the near future. As per the Research Dive report statistics, the global data science platform market is anticipated to grow at 31.1% CAGR and will reach up to $224.3 billion during the period of forecast. The report highlights prominent players operating in the global market. Some of them are Alphabet Inc. (Google), Databricks, Domino Data Lab, Inc., Civis Analytics, Dataiku, Cloudera, Inc., IBM Corporation, Anaconda, Inc., Microsoft Corporation., and Altair Engineering, Inc. These players are adopting several strategies such as collaborations, product development, and are also initiating R&D activities to stand strong in the global market.