Grid Computing

Grid computing is a collection of computer resources for performing computing functions using resources from various domains or multiple distributed systems to reach a specific goal. A grid is designed to solve big problems to maintain the process flexibility. Grid computing is often used in scientific/marketing research, structural analysis, web services such as back-office infrastructures or ATM banking etc.

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People generate 2.5 quintillion bytes of data each day.
Customer/social analysis is considered the second most important big data analytics use case, followed by predictive maintenance.
36 percent of investment professionals use web scraping to derive data.
98 percent of sales representatives at construction companies that adopt analytics and geographic data reported dramatic decreases in their time frame for providing price quotes.
In a survey of approximately 700 business professionals, only 15% said their organization is currently very effective in delivering a relevant and reliable customer experience. In the same survey, only 3% of respondents said they are able to act on all of the customer data they collect; 21% say they can act on very little of it.
90 percent of the world’s data was created between 2015 and 2016 alone.
79 percent of enterprise executives say that not embracing big data will cause companies to lose competitive position and risk extinction.
90 percent of IT professionals plan to increase spending on BI tools.
70 percent of investment professionals use “alternative data” or plan to do so in the next year.
The big data industry will be worth an estimated $77 billion by 2023.

Grid Computing

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