Five Key Criteria to Consider When Evaluating a Data Labeling Partner
By Aaron Bianchi
Jul 14, 2021
Machine learning (ML) and AI have dramatically changed the way many businesses across the globe work. As ML and AI continue to evolve, one of the biggest challenges is to ensure the quality of the data utilized by your systems.
For machine learning to work, your system needs properly labeled data. Without it, your ML model may not recognize patterns, which it needs to make decisions or perform its functions.
This is one reason data scientists and corporations worldwide work with data labeling partners or invest in data labeling tools.
Are you currently looking for a data labeling partner? Before getting started on your search, you must first understand what data labeling is.
What is Data Labeling?
Data labeling is an essential part of ML, particularly Supervised Learning, a common type of ML used today.
Data labeling identifies raw data such as text files, images, and videos and adds context to them. Once data have been labeled, it will be the learning foundation of your ML model for all data processing activities.
As your ML model relies heavily on data labeling, make sure you're working with a data labeling partner that isn't just reliable; your partner should also have sufficient data labeling experience in your industry.
How to Choose a Data Labeling Partner
There are many ways to find professionals to perform data labeling for you. The most popular is working with a data labeling company or contractor.
Essentially, these service providers become an extension of your team. They manage all your data and would often charge by their output volume.
Why should you work with a data labeling company? One of its benefits is that it's more cost-effective than investing in data labeling tools and spending on human resources. Secondly, working with a data labeling service provider ensures the work is done right. When your team doesn't have enough knowledge and experience with data labeling, you'll need to give them time to learn it. Additionally, you'll have to provide more time for them to finish the work, which isn't an efficient use of your company's resources.
When choosing a data labeling partner, don't forget to take the following steps. These will help you find the best provider and make your search more efficient.
Define Your Goals
Setting goals and expectations is crucial, especially when working with professionals outside of your organization. Remember, they will be working on your data. Therefore, they should have a clear understanding of what you expect from them and the service required of them.It would help to have the following information from the beginning:
• Project overview
• Timeline
• Data volume
• Data quality guidelines or overviewSet a Budget
Once you've prepared all the information, the next step is to decide on a budget.Every service provider is different, and all of them would have different rates. Having a budget would make it easier to create a shortlist of candidates, mainly when most of your chosen candidates provide similar proposals or offers.
Create a List of Candidates
Now that you have your budget and project details on hand, the actual search begins!
Don't be in a rush to find the "one" for your company. Instead, take your time evaluating multiple service providers. Do your background research, look for customer reviews, and find out their overall standing in the industry.
Ask for Proof of Concept
Provide a sample task that is quite similar to your project and evaluate how each candidate would deliver the output. This is an easy way to identify a service provider's skills, experience, and reliability. Additionally, a proof of concept could help you determine any possible roadblocks you may encounter once your project starts.
Criteria for Evaluating a Data Labeling Partner
With thousands of companies offering data labeling services, it could be challenging to assess everyone on your list.
The best way to evaluate your candidates is to set some criteria. Here are five you may use when choosing a partner.
Data Quality
Keep in mind that your ML or AI model would only be as good as the quality of data you provide. Because of this, checking for data quality is of utmost importance when looking for a data labeling service provider.
Tip: Don't forget to talk to your candidates about their quality control measures.
Technology
Another benefit of outsourcing data labeling is that you can access tools and technology that your company may not otherwise afford.
Ask your vendors which tools and technology they would use for your project. Their tools should help you maximize your time, resources, and efficiency — all while providing quality data.
Workforce
Sure, a service provider may already work with multiple clients... but that doesn't mean they're suitable for your project. Make sure their staff knows how to handle the type and volume of data you have. This would help get things going smoothly and with minimal supervision from your end.
Security
Confidentiality and data security are crucial when it comes to outsourcing this type of work. You wouldn't want to worry about data leaks and hacks, would you? Inquire about the company's security protocols and process of handling sensitive data.
Social proof
When possible, ask for a list of (past or present) clients. Then, get in touch with them to ask for their feedback on the provider. You may also consider looking into case studies that they've done, which would give you a good idea of the quality of their work and processes.
Finding the right data labeling partner for your company doesn't always have to be complicated. With this guide, you could get started on your search and make sound decisions.
Do you want to learn more about data labeling and how Digital Divide Data could help? Fill out our contact form, and we'd be happy to learn more about your needs and walk you through our process.