PUNE, India, Jan. 28, 2020 /PRNewswire/ -- The growing adoption of cloud based solutions is driving the growth of global time series intelligence software market. Time series intelligence software uses a set of techniques to automatically collect, integrate and analyze raw information, such as industrial process parameters or business metrics, which is collected in correlation with time. The trend of connected society has been evolving due to continuous development of technologies such as 5G/LTE/IoT coupled with Big Data, which is generated using devices based on these connectivity technologies. The increasing volume of datasets creates concerns in operating and storing them on-site owing to infrastructure limitations.
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A small business spends around 7% of its annual revenue on IT expenses and these expense varies with size and type of business. Cloud based solutions have been proved successful to overcome these challenges. Cloud based time series intelligence software introduced by major players are gaining popularity and contribute a major share of market as compared to web based solutions. For instance, Timescale, Inc. recently announced release of Timeseries Cloud, a multi-cloud time series tool which is compatible with AWS, Microsoft Azure and Google Cloud. These solutions reduce the major IT expenses related to hardware and software purchasing, operations and downtime among other peripheral expenses. Cloud based time series intelligence software have enabled enterprises to expand their reach around the globe without having to incur the costs concerning IT infrastructure scaling. Thus, cloud based solutions is encouraging investments of enterprises towards time series intelligence software market
The cloud based time series intelligence software enables accurate and faster analysis of the data. Increasing business competition has posed a need for critical decision making to survive in the market. Critical decision making requires accurate insights at high speed. The cloud based solutions enables data scientists and analysts to perform complex calculations at a faster rate using high configuration servers. The trend of virtual desktop coupled with cloud technology is poised to drive the global time series intelligence software market over the forecast period. Continuous progress in the field of artificial intelligence has lured the time series intelligence software providers to enhance their products using this technology. For instance, Tensormake a U.S. based artificial intelligence start-up, has developed an automated time series forecasting software which uses deep learning for solving complex tasks with 90% accuracy. These present-day technologies are set to drive the time series intelligence software market and create new opportunities in the near future.
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The detailed research study provides a qualitative and quantitative analysis of the global time series intelligence software market. The market has been analyzed from demand as well as the supply side. The demand side analysis covers market revenue across regions and further across all the major countries. The supply-side analysis covers the major market players and their regional and global presence and strategies. The geographical analysis done emphasizes each of the major countries across North America, Europe, Asia Pacific, Middle East & Africa, and Latin America.
Key Findings of the Report:
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Global Time Series Intelligence Software Market
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