Data Science Platform Market Opportunities, Outlook, Growth Prospects, Product types and Competitive Analysis
Data science platform market is estimated to rise with a CAGR of 31.1% by generating a revenue of $224.3 billion by 2026. Asia-Pacific holds the highest growth rate, expecting to reach $80.3 billion during the forecast period.
Data science is the preparation, extraction, visualization, and maintenance of information. Data science uses scientific methods and processes to draw the outcomes from the data. With the help of data science tools and practices one can recognize the data patterns. The person dealing with data science tools and practices uses meaningful insights from the data to assist the companies to take the necessary decision. Basically, data science helps the system to function smarter and can take autonomous decisions based on historical data.
Access to Free Sample Report of Data Science Platform Market (Including Full TOC, tables & Figure) Here! @ https://www.researchdive.com/download-sample/77
Many companies have a large set of data that are not being utilized. Data science is majorly used as a method to find specific information from a large set of unstructured and structured data. Concisely, data science is a vast and new field which helps to build, asses and control the data by the user. These analytical tools help in assessing business strategies and taking decisions. The rising use of data analytics tools in data science is considered to be major driving factor for the data science platform market.
Data science is mostly used to find hidden information from the data so that business decisions and strategies can be conceived. If the data prediction goes wrong, business has to face a lot of consequences. Therefore, professional expertise are required to handle the data carefully. But as the data science platform is new, the availability of the workforce with relevant experience is considered to be the biggest threat to the market.
Service type is predicted to have the maximum growth rate in the estimated period. Service segment is projected to grow at a CAGR of 32.0% by generating a revenue of $76.0 billion by 2026. Increasing difficulties in terms of operational work in many companies and rising use of Business Intelligence (BI) tools are predicted to be major drivers for the service type segment.
Speak to our Expertise before buying Data Science Platform Market Report@ https://www.researchdive.com/connect-to-analyst/77
Manufacturing is predicted to have the highest growth rate in the forecast period. Data scientists have acquired a key position in the manufacturing industries. Data science is being broadly used for increasing production, reducing the cost of production and boosting profit in manufacturing area. Data science has also helped the companies to predict potential problems, monitor the work and analyze the flow of work in the manufacturing work area. Manufacturing segment is expected to grow at a CAGR of 31.9% and is predicted to generate a revenue of $43.28 billion by 2026.
North Americas has the largest market size in 2018. North America market is predicted to grow at a CAGR of 30.1% by generating a revenue of $80.3 billion by 2026. The presence of large number of multinational companies and rising use of data with the help of analytical tools in these companies gives a boost to the market in this region. Asia-Pacific region is predicted to grow at a CAGR of 31.9% by generating a revenue of $48.0 billion by 2026. Asia-Pacific is accounted to have the highest growth due to increasing investments by companies and the increased use of artificial intelligence, cloud, and machine learning.
The major key players in the market are Microsoft Corporation, Altair Engineering, Inc., IBM Corporation, Anaconda, Inc., Cloudera, Inc., Civis Analytics, Dataiku, Domino Data Lab, Inc., Alphabet Inc. (Google), and Databricks among others.
Request for Data Science Platform Market Report Customization & Get 10% Discount on this Report@ https://www.researchdive.com/request-for-customization/77
Comments
Post a Comment