Data annotation Services- Fivesdigital

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• Pros and Cons of In-House vs Outsourced Data
  Annotation Platform
• A staggering 1.145 trillion MB of data is created
  per day.
• Thats a lot, right? But did you know, almost 95
  of this data is unstructured?
• Can this data be used for training AI models?
  Absolutely not! Because for data to be used in
  training AI and ML algorithms, it needs to be
  structured, labeled, and classified. Solution?
  Its DATA ANNOTATION! The data annotation tool
  is used to tag, label, or annotate this
  unstructured data for training AI/ML models. And
  because of the undeniable benefits of data
  annotation in redefining businesses, it has taken
  center stage in technological innovations.
• The next question that might run in your head is
  whether to build an in-house team or outsource
  your data annotation requirements? Lets try and
  find an answer to this question.
• Creating an In-House Data Annotation Team - With
  Your Skilled Workforce!
• Pros
• Building your in-house data annotation team can
  be an ideal option when the volume of data to be
  annotated is less, and the cost of getting it
  outsourced is burning a hole in your pocket. An
  in-house data annotation platform can allow you
  to choose the tool or build it in-house
  according to your business needs and
  requirements. Moreover, having physical
  proximity helps have direct supervision of the
  complete data annotation solutions.
• Lastly, one crucial reason that businesses choose
  in-house data labeling over outsourcing is the
  issue of security. Lately, outsourcing vendors
  have understood the sensitivity of the problem
  and therefore follow stringent confidentiality
  protocols. However, some businesses still feel
  reluctant to share their confidential images and
  information over the internet.

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• Cons
• The disadvantages of having an in-house team are
  pretty evident. The process of data annotation
  is usually cost and time intensive. And on top of
  that, the need to hire and train a professional
  team adds up to the cost of time, effort, and
  resources.
• If you choose to build an in-house team, you will
  be required to constantly manage the team,
  provide a secure working environment, compile
  instructions, research, and create the right
  tools and software. Why is that a disadvantage?
  Because all these tasks can ultimately shift
  your focus from the core functions of the
  business. This is where data annotation services
  from a trusted outsourcing vendor can be your
  ideal choice.
• Outsourcing Data Annotation Services - Always to
  a Trusted Vendor!
• Pros
• Outsourcing your data annotation requirements
  seems to be the most plausible method. How?
  Outsourcing services help you save a lot of time
  and resources. Plus, it also relieves you of the
  stress related to labeling the data yourself.
  Data annotation service vendors bring years of
  experience and expertise, resulting in better
  quality output. Moreover, outsourcing is
  undeniably more affordable than in-house
  annotation.
• A third-party vendor eliminates the possibility
  of any internal bias, resulting in accurate and
  impactful AI training data. Along with providing
  better flexibility and scalability for your
  projects, these service providers also offer
  custom-made solutions in sync with the goals and
  objectives of your data management practices. The
  best part? They can accurately and rapidly
  annotate a massive amount of data in multiple
  formats.
• Cons
• While there are various benefits of outsourcing
  your data annotation needs, there are some
  drawbacks as well. These cons include giving up
  some control over the data annotation process,
  facing language barriers, and choosing the right
  outsourcing vendor from multiple options.
• Although outsourcing vendors data annotation
  tools and services seem like a more ideal and
  reasonable choice, the decision largely depends
  on the size and nature of your business and
  projects.

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