Adoption of Deep Learning Frameworks Triggers Need for Data Science Platforms

San Francisco, California, May 24, 2017: The rapidly growing big data across enterprises and the growing popularity of data analytics solutions have necessitated the evolution of data science platforms world over. The upsurge in implementation of deep learning technologies across numerous organizations to improve business decisions has stirred exciting developments in the data science platform. Factors such as these and key trends shaping the dynamics of the data science platform market are elaborated on in a report penned by TMR Research. The report is titled, Data Science Platform Market – Global Industry Analysis, Size, Share, Trends, Analysis, Growth, and Forecast 2017–2025.” The research study offers comprehensive insights into the key drivers and restraints, market share and size of various segments, and competitive landscape.

The study covers the recent offerings by various players and assesses the scope of the recent innovative platforms developed by top technology companies in major regions. The surging demand for advance analytics tools and predictive modeling solutions amidst businesses has spurred the demand for data science platforms to facilitate deployment of machine learning technologies. This is a key factor driving the market for data science platforms. Data science platforms are increasingly used by businesses to gain actionable insights from big data and to convert these information to business intelligence. Ceaseless research and development in deep learning technologies have facilitated large-scale data processing, boosting the data sciences platform market.

The advent of data science platforms that integrate the work of various data scientists is a key factor stimulating the demand for data science platforms. Prominent consumer web and mobile application developers are keen on leveraging the capabilities of deep learning frameworks. Top technology players such as IBM are developing innovative data science platforms and offering a variety of cognitive business applications to enable their enterprise clients to adopt deep learning technologies. The use of data science platform enable researchers working on deep learning applications to get a wider access to vast computing capabilities, thereby bolstering its adoption. The soaring popularity of hybrid cloud, artificial intelligence, and Internet of things (IoT) are further expected to catalyze the data science platforms market growth.

However, the limited awareness of data science platforms among enterprises, mainly attributed to the general lack of reliability of these solutions, is likely to hamper its adoption for some time. However, spiraling investment by prominent technology players to develop innovative platforms by integrating advanced open source analytics in their offerings is anticipated to open up exciting opportunities for market players to capitalize on. Some of the major data science platforms are information and telecom, banking, financial services, insurance, defense, healthcare and life sciences, energy and utilities, and manufacturing.

North America is a prominent regional market for data science platforms. The growth of the market is fuelled by the presence of numerous market players and constant product innovations. Asia Pacific is expected to provide lucrative growth avenues in the coming years. The substantial demand for data science platforms in this regional market is driven by extensive governmental policy support for digitalization and smart city initiatives in various regions gathering steam.

Some of the major players operating in this market are IBM, Domino Data Lab, Wolfram, Microsoft Corporation, RapidMiner Inc., DataRobot Inc., Sense Inc., Alteryx, Inc., Continuum Analytics, Inc., and Dataiku.