Up until recently, oil was considered the most valuable resource on earth for it powers the cars on our roads and airplanes in the sky and is an important source of generating electricity needed to operate industries and light up our homes. Not anymore. The most valuable resource these days is data. With the proliferation of smart mobile gadgets, popularity of Internet of Things (IoT), and cloud, organizations these days are staring at gazillions of data. Just like oil, the data is of no use as such, but hold out immense potential if tapped into properly. To do so, data science platforms come in handy.
A data science platform comprises of all the tools needed for carrying out the lifecycle of the data science project spanning various phases such data ideation, integration and exploration, model development, and model deployment. It enables data scientists to improve their analysis by running, tracking, reproducing, sharing, and deploying analytical models faster. Typically, such tasks need massive engineering for building and operating analytical models. This is where a data science platform can help by offering additional powerful tools to improve analysis, which in turn, allows framing of better strategies.
The market for data science platform is expected to see booming growth over the course of next few years on account of surging application of data analytics and big data for different business decisions and operations. Enterprises across the world are increasingly opting for methods for simpler use of data through big data technologies to promote their business and this is catalyzing demand for data science platforms.
The data science platforms help derive insights from raw data, reproduce data tables for descriptive statistics, and create segments depending upon date, module, and event type for root cause analysis through data visualization. The algorithm leveraged in a data science platform can also offer functionality for predictive modeling and a mechanism, which can bring in the predictive models into operations.
Depending upon the type, the global market for data science platform can be split into close platform and open platform. The key end users driving up demand in the market are pharmaceuticals and healthcare, BFSI, meteorology, logistics, and transportation.
Latin America, North America, Eastern Europe, Western Europe, Japan, Asia Pacific excluding Japan (APEJ), and the Middle East and Africa are some of the key regions in the global market for data science platform. The region which holds a dominant position among them at present is North America. Presence of numerous large data centers and swift development of data science platform products in the region have phenomenally boosted its market.
APEJ, powered by nations of Singapore, India, and Korea, the flourishing IT industry and growing number of data centers, is also emerging as an attractive data science platform market. Western Europe and Eastern Europe are other key regions.