"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"
Mega
Data Centers: Market Shares, Strategies, and Forecasts, Worldwide,
2017 to 2023
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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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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