Data Processing: A Big Game for these Industries

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Welcome To Loginworks Softwares
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Data Processing A Big Game for these Industries
Data processing is a fast developing technology,
and has many benefits in the industry through
improved efficiencies, targeted marketing,
predicting trends, improved safety, and better
customer service. In this article, we will look
at a few of the industries that use data
processing on a large-scale to provide
significant improvements.
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Data Processing in Manufacturing
Large manufacturing processes have the biggest
potential gains from effective data processing,
such as Advanced Process Control (APC),
production refinement, and error tracking. Many
large manufacturing industries are installing
advanced data processing and analytics to
identify exactly where to adjust their processes
to improve productivity. Even smaller
manufacturing processing can gain big increases
in efficiency through data processing. 1. Data
processing methods can streamline manufacturing
by identifying specific areas of 2. Production
waste 3. Product failure points 4. Technical and
process improvement 5. Efficiency improvement
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Where no data processing is completed, its
impossible to determine exactly what contributes
to an increase or decrease in yield. With
effective tracking of all parameters in the
production system, the data can determine exactly
what variable is responsible for improving yield,
reducing waste, or reducing production times.
One chemical manufacturer increased yield by
20, and reduced energy output by 15 through
identifying and correcting a variability in
chemical flow control that directly affected
yield. Without data processing companies, the
contributing factor would never have been found.
In another case, a raw material processing plant
identified that high yield days corresponded to
days where there were increased quantities of
certain chemicals. This led to the refining of a
specific type of extraction process which
improved yield to increase net profits by tens of
millions. Data processing effectively matches yie
ld with all possible parameters to determine
where the highest and lowest production rates
occur, or where losses are occurring, so as to
identify the key reasons for the variation. This
helps improve efficiency and quality.
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Data Processing in Health Care
There are huge amounts of data generated in the
healthcare industry. With improvements in data
technology, the industry is now using data
processing in much more effective ways to improve
services, improve pharmaceutical production and
effectiveness, and improve diagnostics.
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In the fields of diagnostics, large online data
processing capabilities can help health care
providers more accurately match symptoms to
causes, and determine if treatments are
effective. Electronic health records (EHR)
improve patient care by making patients full
record immediately available to healthcare
providers. Research facilities use complex data p
rocessing to improve new medical treatments and
find causes for diseases. Pharmaceutical companie
s use data processing to improve production to
reduce costs of manufacturing drugs. Data
processing is also used in studies to determine
the effectiveness of drugs. Healthcare users stan
d to have huge benefits from streamlined
data-processing in medical industries, by more
effective and lower cost care.
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Data Processing in Retail
Retail industries are becoming far smarter with
effective data processing. This translates into
better consumer services. Strict analysis of
buying trends can allow retailers to effectively
predict which items are in demand at specific
times and match order lead times to cater for
this, improving sales and services. The same
analysis of remaining stock can help effectively
trigger discounts and promotions for items close
to expiry, or those with excessive stock
remaining. Analysis of data across branches can
help immediately identify if any branch is
underperforming, and in which areas, to put a
timely remedial plan in place.
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Specific targeted marketing can be designed
around consumer buying trends. Linking a
customers shopping trolly contents to their
profile can identify customer promotions to send
out. This may include loyalty bonuses, or new
buyer welcomes. It can also target specific
promotions for example if you are buying more
stationary because of new educational demands,
retailers may send you promotional coupons for
uniforms, if youve suddenly increased your
clothing purchases for sports, they may send you
coupons for healthy foods. In-depth data
processing can create marketing opportunities
which keep customers returning more regularly.

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Data Processing in the Aviation Industry
The aviation sector has always been at the
forefront of technology, since safety and revenue
are driven by critical performance improvements,
and their early embrace of data processing is no
different. Two key areas of data processing are v
ital to the aviation industry, safety data, and
sales data. Data processing is used extensively i
n sales and marketing to optimize seat sales and
pricing. Ticketing systems run the complex
analysis of seats remaining to prompt specials
and promotions, or price increases and decreases
with demand. With high costs flight operators
rely on seat sales to stay in business, and only
with complex data processing can effective yields
be obtained. Safety incident and flight data even
t monitoring uses data processing to provide
important safety statistics for improving airline
safety standards. Flight data processing
indicates key events like unstable approaches or
altitude busts. Data processing can link this
data into fatigue monitoring programs, airspace
use, or crew experience levels to provide
preventative strategies. The safety system tracks
incidents in all areas of the operation, and can
identify any significant safety events, for
example, a regular pattern in maintenance events
on a specific aircraft, go arounds or near-misses
at a particular airfield.
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Data Processing in Finance and Insurance
The financial and insurance sectors are another
area where data processing has always been an
integral part of business. Increases in data
processing technology continue to provide
improved accuracy and better customer services.
In finance and insurance data is used to assess
risks, identify trends, analyze investment
performance, and make effective business and
pricing decisions. For investment decisions, only
with the effective use of data can a broker
decide which companies or stocks are the best
choices. Data processing can help solve complex
comparisons of different portfolio options, and
provide concrete results to prove if these
choices are working. In both lending and in insur
ance, determining risks are important to
calculating rates and making decisions. Data
processing of claims profiles can help determine
which factors affect risk with far more accuracy,
to calculate premiums with more assurance and
better tailor packages to customers needs.
Complex modeling of customer data can help
identify reasons for lending defaults, which will
help refine approval processes.
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Data Processing in Agriculture Agricultural data
processing is an area that has been slower on the
uptake because of traditional techniques and
economic influences, but new research into smart
farming has proven significant benefits.
Large-scale producers are proving that data use
significantly improves yield, and this
application is spreading across the industry.
Weather patterns can be used to predict watering
and feeding needs to avoid shortages and to plan
stock and planting effectively.
Soil and yield analysis can be measured against
different planting and watering methods to
determine which nutrients are needed, where
planting failures occur, and which stocks give
the highest yield under which conditions.
Machine sensing and data processing can be used
to ensure controlled crop distribution.
Geo-mapping can help determine fertilizer
requirements. Analysis of environmental sensors
can help predict attack from insects or disease.
Data processing can assist in stock management by
tracking breeding processes, managing grazing,
and regulating feeding needs. Data processing can
drive the use of automation in farming to reduce
labor costs. Far more efficient management of the
agricultural business can be obtained from the
use of data processing in smart farming processes.
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Data Processing in IT The information technolog
y sector in some ways is the backbone behind data
processing, and in other way, data processing is
driving information technology.
Data processing itself relies on effective IT
for data storage, management, and processing.
Data management needs programming and digital
systems to work effectively, so IT is an integral
part of data management. At the same time, IT pro
fessionals are developing more user-friendly data
management systems, as data use becomes more
widespread, there is a strong need to provide
tools for industry professionals to handle data
directly. Automated data management systems are
becoming a new trend in software development.
Data is also driving IT platforms, such as
search, social media, electronic shopping, and
booking services. There is an increasingly
stronger use of data processing in IT businesses,
with the increasing availability of big data
collection and processing tools.
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Data Processing in Industry In many cases, data p
rocessing needs to be outsourced, since the
companies are not expert in data handling. While
outsourcing is a very affordable way to put data
processing into effect, the manufacturer should
work closely with data experts to ensure the data
processing system is put in place effectively.
Every sector can improve with the use of data.
Those with massive amounts of data from
large-scale processes as discussed here are
capable of benefiting immensely from the face
developing capabilities of data services.
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