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Top 10 challenges growth big data service

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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. – PowerPoint PPT presentation

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Updated: 14 August 2019
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Title: Top 10 challenges growth big data service


1
Top 10 Challenges in Growth of Big Data Services
Companies
2
  • 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.

3
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.

4
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.

5
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.

6
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.

7
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.

8
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.

9
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.

10
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.

11
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.

12
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.

13
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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