Top 10 challenges growth big data service

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Top 10 Challenges in Growth of Big Data Services
Companies
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• There are numerous challenges of Big Data.
  Choosing Big Data solutions is a normal practice
  for most businesses today but that does not mean
  that it is free from challenges. Based on the
  findings of New Vantage Partners Big Data
  Executive Survey 2017, almost 95 percent of the
  business leaders from multinational corporations
  cited that their companies had accepted one Big
  Data project in the last five years or so. Also,
  less than 48.4 percent cited that their Big Data
  strategies gained some quantifiable outcome.

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1. Budget is a Concern

• Though there are many benefits of Big Data
  analytics solutions, the CIOs of Big Data
  services companies find it hard to persuade the
  CFOs and justify the return on investment on Big
  Data. To be candid, the projects are expensive.
• Based on the findings of leading technology
  companies, current projects are costing them at
  least 18 percent of their total IT expenses on an
  average.
• This will increase 25 percent more in the
  subsequent years. The survey respondents said
  that huge investments are necessary to let the
  multinationals Big Data projects mature.
• The major investments include hiring skilled
  staff as well as training current employees, and
  the need for new infrastructure.

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2. Managing data explosion

• Most Big Data solutions companies have problems
  coping with huge amount of data generated daily.
  The noticeable problem lies in the storage and
  analysis of this huge data.
• According to IDCs Digital Universe Report, the
  volume of data stored in the global IT systems
  increases two-folds every two years. The total
  data volume will be adequate to fill tablet piles
  reaching to the moon from our planet 6.6 times.
• Another aspect is that companies have some
  accountability or responsibility for
  approximately 85 percent of such data.
  Furthermore, data in the form of photos,
  documents, audios, and videos is unorganized data
  and difficult to search and evaluate.
• The Big Data solutions companies need to
  implement tools and technologies such as Hadoop,
  NoSQL, Spark, artificial intelligence, business
  intelligence software, machine learning, and Big
  Data analytics solutions to find useful insights
  for making informed decisions.

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3. Data Storage

• Based on the findings of the State of Big Data
  Infrastructure, the use of information in
  companies had increased at an average rate of 16
  percent in 2013-2014 and another 24 percent in
  2016-2017.
• Then, these numbers could be skyrocketing for
  corporations dealing with huge consumer data. The
  IoT will add more to this problem. The question
  which then arises is, where will you store such
  large amount of data?
• The solution is switching to a cloud environment,
  but all enterprises are prepared for the same due
  to legacy problems.
• IBM, for example, has been working on cognitive
  storage to let computers know which data is
  important and what requires elimination.

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4. Visualization Issues

• When most of the data is granular, it is
  challenging, if not impossible for Big Data
  solution providers to make sense of such
  information.
• Pulling out millions of data rows is a cumbersome
  task for analysts responsible for organizing,
  arranging, and presenting the information.
• It is advisable to use data visualization tools
  to derive useful insights from data overload.
• It is better if companies develop new
  user-interactive systems supporting virtual and
  augmented reality.

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5. Hiring and Retaining Big Data Professionals

• The Big Data solution providers need to hire the
  best talents who can develop, control, and run
  the applications generating useful insights.
• This leads to a high demand for Big Data experts
  with average salaries ranging between 116,000
  and 163,500.
• Therefore, hiring and retaining data analysts or
  business intelligence professionals is a big
  challenge now.
• The companies meet the dearth of talent through
  salary hikes, training opportunities to existing
  staff, and retention policies.

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6. Incorporation of Varied Data

• Companies offering Big Data services often face
  challenges related to the integration of diverse
  data from numerous sources.
• Information comes from multiple sources such as
  email systems, social media, and
  employee-generated documents.
• Merging all such information and bringing them
  together to generate reports is incredibly
  challenging. Although the vendors provide a range
  of data incorporation tools and ETL (extract,
  transform, load) to make the process a tad
  easier, the companies are not happy with the
  solution.
• That is why they are resorting to big data tools,
  data analytics software, and integration
  technology.

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7. Leveraging Useful Insights on Time

• The companies specializing in Big Data services
  do not just want to store information but
  leverage the data for gaining useful insights,
  and realize business objectives.
• These goals help enterprises to become more
  competitive provided they can mine the data with
  speed and accuracy.
• Many companies today are switching to new-age
  analytics tools and ETL to attain the required
  speed in mining data and deriving useful
  insights.
• These applications radically help in reducing the
  time required to create detailed reports.

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8. Protecting Data

• Securing information is a major challenge for
  companies dealing with huge data sets.
• The Big Data consulting services ensure the
  protection of mission-critical information.
• They walk the extra mile to secure huge data
  stores from hackers. Most companies, therefore,
  have their data security measures in place for
  their big data requirements.

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9. Data Validation

• Companies receive the same kind of information
  from diverse systems but the data does not always
  match.
• For instance, your e-commerce system may display
  daily sales but your ERP system shows a different
  number.
• To make these records match, secure, and usable
  the companies switch to data governance.
• There are dedicated experts to monitor data
  governance and create a set of rules, policies,
  and guidelines.

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10. Organizational Problems

• People can be a challenge when it comes to big
  data implementation.
• Based on the findings of New Vantage Partners
  survey, about 85.5 percent of the participants
  cited that their companies had a data-driven
  culture, but a meager 37.1 cited that they were
  successful in their endeavors.
• Companies should improve decision making by
  hiring powerful leaders who know about the
  benefits of Big Data and what challenges the
  company.

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Conclusion

• The key to the growth and success of data
  implementation is choosing the right Big Data
  consulting services and deriving useful,
  actionable insights from huge data sets.

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