The Report Mega Data Centers: Market Shares, Strategies, and Forecasts, Worldwide, 2017 to 2023 provides information on pricing, market analysis, shares, forecast, and company profiles for key industry participants. - MarketResearchReports.biz
Albany, NY -- (SBWIRE) -- 03/29/2017 -- Worldwide mega data center markets are poised to achieve significant growth with the Internet of Things (IoT), the wireless data explosion, and increased use of video creating more digital data to be managed. The use of smartphone apps and headsets or glasses that are augmented reality platforms to project digital information as images onto a game image or a work situation create a lot more data to be managed.
The mega data centers are different from cloud computing in general, and different from the existing enterprise linear computing data centers. The mega data centers are handling infrastructure automatically, eliminating manual process for infrastructure, creating a separate application layer where all the work gets done. The operative nomenclature is containers. The operative software is orchestration.
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Mega centers are moving data at the speed of light. This represents a huge change in computing going forward, virtually all the existing enterprise data centers are obsolete because moving data at the speed of light demands different infrastructure from moving data using existing cabling that is not fiber. This study addresses these issues. As enterprises and cloud vendors build data centers with the capacity to move data inside the data center at 400 GB per second, more data can be managed, costs will continue to plummet, and efficiency goes up.
The mega data centers are needed to handle all manner of new quantities of digital information. All manner of devices will have electronics to generate digital data turning it into monitored digital information with alerts to permit response to streams of information that demand response, as for example cardiac data going into a cardiac monitor in a hospital intensive care unit. New monitoring situations emerge. The connected home will provide security on every door, window, and room with alerts that can be sent to and accessed from a smart phone. The refrigerators and heaters will be connected and be equipped with rule based logic to detect problems and send relevant info so they can be turned on and off remotely.
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In industry, work flow will be automated beyond single process to multi process information management. The sheer scale of the fabric is fundamentally changing how the market leaders monitor and troubleshoot the data center. Components and links behave the same. Baselines and outliers are key to active auditing for problems. Priority-driven alerting and auto-remediation are in place.
Amazon (AWS), Microsoft, Google, and Facebook data centers are in a class by themselves, they have functioning fully automatic, self-healing, networked mega datacenters that operate at fiber optic speeds to create a fabric that can access any node because there are multiple pathways to every compute node. Five of the largest-scale internet firms – Apple, Google, Microsoft, Amazon and Facebook – continue to invest heavily in building out datacenters globally, with capital spending at the companies totaling more than $115 billion over the past 14 quarters. In Q2 2016, capex at the five companies increased 9.7% sequentially and 60.5% over the same quarter two years ago. The pace of capex at large-scale internet firms in general has been increasing over the past several years.
As more people connect and as Facebook creates new products and services, this type of traffic is a small proportion of all the data that needs to be managed. Inside the Facebook data centers machine to machine traffic is several orders of magnitude larger than what goes out to the Internet.
This is the 691st report in a series of primary market research reports that provide forecasts in communications, telecommunications, the Internet, computer, software, telephone equipment, health equipment, and energy. Automated process and significant growth potential are a priority in topic selection. The project leaders take direct responsibility for writing and preparing each report. They have significant experience preparing industry studies. They are supported by a team, each person with specific research tasks and proprietary automated process database analytics. Forecasts are based on primary research and proprietary data bases.
The primary research is conducted by talking to customers, distributors and companies. The survey data is not enough to make accurate assessment of market size, so WinterGreen Research looks at the value of shipments and the average price to achieve market assessments. Our track record in achieving accuracy is unsurpassed in the industry. We are known for being able to develop accurate market shares and projections. This is our specialty.
The analyst process is concentrated on getting good market numbers. This process involves looking at the markets from several different perspectives, including vendor shipments. The interview process is an essential aspect as well. We do have a lot of granular analysis of the different shipments by vendor in the study and addenda prepared after the study was published if that is appropriate.
Forecasts reflect analysis of the market trends in the segment and related segments. Unit and dollar shipments are analyzed through consideration of dollar volume of each market participant in the segment. Installed base analysis and unit analysis is based on interviews and an information search. Market share analysis includes conversations with key customers of products, industry segment leaders, marketing directors, distributors, leading market participants, opinion leaders, and companies seeking to develop measurable market share.
Over 200 in depth interviews are conducted for each report with a broad range of key participants and industry leaders in the market segment. We establish accurate market forecasts based on economic and market conditions as a base. Use input/output ratios, flow charts, and other economic methods to quantify data. Use in-house analysts who meet stringent quality standards.
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