Strategic Business Impact of Big Data: Analysis and Future Trends

This report explores the business impact of big data, highlighting its potential to provide organizations with a competitive edge through smarter decision-making and increased efficiency. It discusses the evolution of big data, emphasizing its characteristics of speed, volume, and variety, and examines how organizations are leveraging it to gain insights into customer behavior, optimize operations, and drive innovation. The report also addresses the challenges associated with implementing big data strategies, including data management, security concerns, and the need for skilled professionals. Furthermore, it emphasizes the importance of a comprehensive assessment phase to ensure successful adoption and long-term benefits, suggesting an integrated approach involving various stakeholders. The report concludes that while implementing big data practices can be complex and require fundamental changes to existing business processes, the potential benefits for organizations in terms of increased profitability and improved decision-making make it a worthwhile investment.

Running head: INFORMATION SYSTEM
Big data and its business impact
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Abstract
In this era of technology, big data comes to an essential trend which is majorly used by
organizations. The organizations are achieving business benefits by analyzing huge knowledge.
The objective of this paper is to determine the business benefits of big data. The paper highlights
that big data could be a powerful source for organizations if used widely. With the use of big
data, organizations can make smart decisions. The use of big data also provides a platform where
organizations can bring efficiency in the system. However, there are various implementation
challenges and it is important that organizations must assess various internal and external threats
before making any investment decision.

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Introduction
The motto of huge knowledge is to supply higher degree of resources and storage, scale
back the time of computation and smart business deciding. The term big data indicates the size of
the data that how complex this data is evolving and this creates the urgency of handle it aptly. It
evolves around the 3 main characteristics that is speed, volume and selection. Here speed stands
for the growing rate of data speed that how enormously data is growing via social media
platforms like Facebook, Twitter and to name a few. Then it comes to volume which depicts the
size and density of the data and last but not the least selection, it is critical because as the more
data arise, the precise the selection should be in order to avoid wastage data and grasp useful
data. Each day world produce a pair of.5 large integer bytes of data; ninetieth of the information
within the world nowadays has been created within the last 2 years alone. Knowledge is growing
at exponential rate and also the consultants of the information analytics technology don't have
enough data to investigate that giant quantity of information (Chen, Chiang & Storey, 2012). Big
data represents 3 main aspects of interest. First one lacks arrangement of such a huge data then
from this how to create opportunities and with this technology how to create higher value with
low cost. With the use of big data organizations can actually save the cost in long term.
Impact of Big Data in business
Organizations square measure grappling with what huge knowledge is and the way it effects
their organizations and the way it makes edges to their organizations. A survey is conducted
during which found that the sole twelve p.c organizations square measure implementing or
corporal punishment the massive knowledge strategy and seventy one p.c organizations square
measure attending to begin the look stage. It’s clear that organizations want smart data of

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shoppers, product and rules, with the assistance of huge knowledge organizations will notice new
ways that to contend with alternative organizations (Jagadish et al., 2014). The organizations of
the planet square measure victimization the massive knowledge for his or her future selections.
Styles of selections that organizations will build from huge knowledge square measure smarter
selections, future selections and selections that build the distinction. Organizations square
measure creates business selections on the premise of the transactional knowledge in past and in
gift however there's another quite knowledge that square measure non-traditional, less structured
knowledge for instance weblogs, social media, Email and pictures that may be used for effective
business selections creating. Oracle offers the product to accumulate and organize these
knowledge varieties and analyze them to seek out new insights. Steps of this method square
measure following -:
 Decision criteria square measure addicted to the choice factors those square measure
social factors, technological factors and economic factors (Buhl, Röglinger, Moser &
Heidemann, 2013).
 Candidate eventualities, There square measure completely different eventualities that
organizations will choose for giant knowledge e.g. huge demand and optimistic.
 Technologies can measure data of warehouse, cloud analytics, embedded analytics and
large knowledge image.
 Technology Assessment indicates the size of international market, enterprise adoption
magnitude relation, entrance restrictions and strength of business.
By adopting this strategy organizations will get the fruits of huge knowledge. The use of big data
helps organizations to increase online presence. The online presence offers multiple benefits
instant comparisons, impulsive buying and suggestions based on previous purchase. It helps in

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better sales generation, faster speed to market for retailers and shared demand creation. In simple
terms, it can be said that the use of big data can help organizations to improve the business
metrics like profitability. With the use of big data, markers have better inferences to drive their
marketing campaign.
Mining of data to embarked business growth
In production surroundings huge {data mining|data methoding} process doesn't finish. a
decent huge knowledge analytics platform has factors like speed of development, robustness,
simply analyze large quantity of information. Information is growing in terms of size and variety
day by day. As we observed its effects on business, Twitter raised aptly that the power of
analytics before the exact time and if any organization chose to be ignorant then such problems
can be a huge troublesome in an upcoming time. Extracting info from the stream knowledge at
real time is that the great way to come back to understand what's happening at the spot. Stream
knowledge gain terribly high speed and it's terribly troublesome to investigate stream knowledge
at real time, stream knowledge needs terribly economical algorithms for mining, that algorithmic
rule ought to be correct. Online news, social media and small blogs square measure the samples
of streams created by the users. Solutions to contend with these streams weren't designed. Samoa
was a platform for mining these streams (Jagadish et al., 2014). This is often a tool for on-line
mining within the cloud surroundings. Samoa will be run on completely different distributed
stream process engines like storm. In future Samoa is going to be open supply, which is going to
be evolution within the analysis space of the massive knowledge stream mining.
Impact on business via big data applications

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Big data has been applied in many business industries. Federal agency analyzed the
estimates and fashioned unjust intelligence on that to support the ultimate reaction. Applications
of big data has been majorly impacted the oil and gas industries. A population raises its usage
and extraction has also been increased. It works in a dual segment. As on one line it help in
analyzing the upcoming usage of oil and gas and on other side Data scientist use big data to
extract the resources of oil and gas as per their environmental records. Impact results are in
dilemma as on one side they are using data to make healthy resources usage and on other side
they are trying to optimize the utility. Similarly such business impacts have social motives also.
Role of big data took a new dimension where White House had decided to keep all the speeches
of Barrack Obama in lieu of influence people for elections that has long term beneficial
connections with big corporate houses.
Impact on business with Big data structure
Big corporations are structuring their business data in such a manner through which they
can attain a maximum traffic. Researchers are attempting to style a knowledge analytics system
that supports higher degree analytics. CLAaaS stands for Cloud-based Analytics-as-a-Service.
CLAaaS was a abstract design for the massive knowledge analytics within the cloud
surroundings. Its options, that square measure customization, collaboration and help.
Implementing CLAaaS during a personal cloud will create knowledge privacy. Camcube may be
a cluster style and it used a topology to attach servers directly with each other. Camdoop is
employed to extend the aptitude like process of packets in networks to perform aggregation of
information (Zhu & Huang, 2014).As there is a little comparison within input and output. To
overcome this issue we tend to adopt a replacement technique by decreasing traffic rather than
increasing information measure. Camdoop have property that camcube uses to forward traffic to

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perform in network aggregation of information. Bigtable is employed to store structured
knowledge having size in petabytes. During knowledge model of Bigtable has delineate. Bigtable
store knowledge of Google applications. Net compartmentalization, Google Finance and Google
earth square measure applications of the Google (Jichang, Danxiao, Xin, Zijian & Xiuting,
2014). These applications have completely different needs for storage. The storage, assortment
and use of information may also produce new vulnerabilities and risks. When analyzing these
risks a framework has been projected to assist the effective use of information (Alam, Sajid,
Talib & Niaz, 2014). During this framework few domains square measure thought of that square
measure ethics, governance, science and technology. By victimisation these all domains along
organizations will be more practical whereas creating their selections and avoid the failures of
future comes. The strategy that is employed for the quick and correct analysis on the massive
knowledge sets square measure sampling, it is that the knowledge set which just about represents
the all knowledge set (Jichang, Danxiao, Xin, Zijian & Xiuting, 2014).
Way forward for organizations with Big Data
It is pretty convincing for organizations to accept and acknowledge the benefits of Big
Data. However, the implementation of big data practices its difficult. It requires a fundamental
and radical change in the existing business process. In some of the cases, organizations have to
change the existing business processes from scratch to accommodate big data practices. It is
important that organizations should have strong policies and procedures in place to manage the
practices and concepts around big data. The use of big data would be beneficial for organizations
only when they can they have a strong assessment phase in place. In the assessment phase, the
organizations should involve multiple stakeholders. One of the recommended ways for
organizations is to assess the business impact in short term and long term. There is always a

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possibility that organizations may not be able to develop the business case for the use of big data
in short term. However, the use of big data would have a positive impact on organizational
business in long term.
Conclusion
Here the bottom line is that data is rising day by day which is making business complex.
Hence to tackle with this one has to implement its applications to avoid problems in future that
can also lead to huge losses. Business houses which are majorly using big data and applying it in
their strategy to get fruitful results are Google, eBay, LinkedIn, and Facebook. Big organizations
are mixing big data into their analytics strategy to get data managed which will increase the
consumer base in terms of reality in future. The sixty-three-p.c. organization reports that the
utilization of huge knowledge is useful for his or her firms and organizations. Organization’s
over seventy p.c. of client and products knowledge square measure used for the business
selections creating. Challenges that seem planning big data sampling and building prediction
models from the massive knowledge streams. The above paper highlighted that the business
impact of big data should be studied from a long-term perspective rather than short term. An
integrated approach with an inclusion of various internal and external stakeholders would also
help the organization to devise and implement an effective strategy around the use of big data.

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