Seven Big Data Challenges and How to Solve Them

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Seven Big Data Challenges and How to Solve Them
Organizations can get stuck at the early stages
of Big Data projects because they might not be
aware of Big Data challenges and how to solve
them. We will take a look at some of the most
common scary Big Data challenges and how to solve
the challenges if we ever encounter them.
1st Big Data Challenge Lack of In-Depth
Understanding of Big Data One of the major Big
Data challenges is the lack of proper
understanding of Big Data. Some employees in an
organization might struggle to understand the
proper meaning of Big Data, which can lead to
such an organization lacking the needed Big Data
initiatives
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that will help with decision-making. If an
organization does not have a sufficient
understanding of Big Data basics and the benefits
it offers, theres a high tendency of their Big
Data adoption projects failing. The
Solution The top management at every
organization should adopt a Big Data culture.
This involves arranging Big Data workshops and
training for staff at all levels. Employees can
also enroll in Big Data Online Course or register
for Big Data Hadoop Certification. This will
encourage the acceptance and proper understanding
of Big Data at all levels, which in turn
promotes change. 2nd Big Data Challenge
Difficulty in Managing Big Data Growth Just as
the name implies, Big Data can experience huge
growth over a period of time. When this happens,
it can be quite difficult to handle the massive
data growth. Also, adjusting to this Big Data
growth turns out to be a serious challenge that
needs to be addressed. From Big Data online
training research, it is estimated that the
amount of data stored in IT data centers will
continue to accumulate for years to come. So,
figuring out how to manage Big Data growth
storage will become a pressing challenge that
needs to be addressed and solved. The
Solution The best way to solve a Big Data growth
challenge is to learn how to manage large data
sets. Some techniques can be deployed such as
tiering, deduplication, and compression. When
data is compressed, the number of bits in the
data is reduced which will then reduce the data
size. Deduplication of data involves removing
unwanted data duplicates, while the tiering
technique involves storing data in different
cloud storage tiers. A Big Data tool like Hadoop
can be used to solve this challenge. The Big
Data Hadoop Certification will be useful for this
issue. 3rd Big Data Challenge Lack of Skilled
Data Professionals Big Data is a modern-day
technology that requires the control of skilled
data professionals. They include Data Analysts,
Data Scientists, and Data Engineers. These are
certified data professionals with Big Data online
training and certification. They
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have the experience of handling sophisticated Big
Data tools and they are in high demand across
the industry. The Solution A good way to clear
this roadblock is to encourage employers to focus
on hiring skilled data professionals. Companies
can also support the professional development of
employees that work with data by enrolling them
in Big Data online training. They can also pay
for a Big Data Hadoop Certification to help their
employees remain loyal to the course of Big Data
culture. 4th Big Data Challenge Confusion with
Big Data Technology Selection There is a massive
variety of Big Data technologies available in the
market. This means it can be difficult to
determine the right technology to use for a
particular Big Data project. Confusion might set
in when differentiating the technology to use in
storing data or the one that will offer the
fastest speed. Is it Spark, HBase, Cassandra, or
Hadoop? This can be a serious challenge. The
Solution The best way to solve this Big Data
challenge is to seek professional help. You can
hire the services of a Big Data consultant or
expert who will guide you on how to use the
various Big Data technologies available in the
market. Another good strategy involves getting
in-depth knowledge of Big Data technologies from
a Big Data online course to understand them
better. 5th Big Data Challenge Big Data
Security Breaches One of the most daunting
challenges of Big Data lies in how to secure a
huge data set. Many organizations focus more on
gathering data, analyzing data, and storing data
that they leave data security for later. If data
sets are not properly secured, hackers can
breach through and steal vital information.
Companies and organizations can lose a lot of
money if this happens.
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The Solution A good way to solve Big Data
security challenges is to put data security
first. Data security is very important across
every stage of Big Data projects, especially at
the design stages. Another effective way to
solve data security challenges is for companies
to hire security professionals. Other steps that
can help include Data Encryption and Real-Time
Security Monitoring. 6th Big Data Challenge
Difficulty in Data Integration from Variety of
Sources Data can be integrated from a variety of
sources but it is a task that can be quite
challenging. For instance, data can be integrated
from sources like emails, customer logs, data
reports, social media platforms, and even
financial reports. The integration of data is
vital for data analysis, so it is important to
learn data integration for compiling reports and
data analysis. The Solution The best way to
solve data integration issues is to purchase the
right tools. Several tools can be used for data
integration from a variety of sources they
include Microsoft SQL, IBM InfoSphere, CloverDX,
Centerprise Data Integrator, Xplenty,
QlikView, and Oracle Data Service Integrator. You
can check out the Big Data online training
course to learn how to use these tools. 7th Big
Data Challenge Big Data Handling
Expenses Handling Big Data involves spending a
lot of money. These expenses include power
supply, new hardware, and recruitment of data
professionals. If the software is newly
developed, a lot of money will go into
configuration and maintenance. Whether a company
is using an on-premises data solution or a
cloud-based water solution, it is important to
learn how to handle the costs. The Solution A
good way to reduce the cost of Big Data projects
is to analyze company needs and deploy the best
Big Data solutions for the project. Applying Big
Data on-premises solutions, cloud-based
solutions and hybrid solutions will go a long way
to reduce the
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Cost of handling Big Data in organizations. These
are cost-effective solutions that will help you
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