Data Annotation, Imperative to Drive Excellence

Ever wondered what drives the algorithm? We know that all our social media, as well as our search engines, are algorithm-driven but what actually brings algorithms into being is data annotation. The process of correctly labeling the datasets in order to train the Artificial Intelligence (AI) and Machine Learning (ML) algorithms to identify the data and provide the most accurate results for your queries.

How to train the machines?

The machine cannot process visual information as humans do, it needs to be trained through data annotations in order to help them interpret and understand. Data annotations are basically labeling of the datasets such as text, audio, images, video, etc so that it helps the machines to learn, interpret and make connections to make prediction/decision making.

The more the data the more can be the benefits

According to The Visual Capitalist, by 2025, an estimated 463 exabytes of data will be created globally on a daily basis. Hence, data annotations are both critical and imperative to bring meaning to the bottomless pit of data being generated. Annotating data i.e. labeling the data accurately is the core of any data process and also amounts to more clean data resulting in really efficient data processing. It is an ever-evolving process that is getting sophisticated as we progress with newer technologies. There can be endless use cases for well-annotated data as it has the potential for generating very high-quality actionable insights that could directly impact managerial decisions in businesses.

Types & examples of data annotations

There can be various types of data annotations based on your business requirements and the purpose of teaching and training the machine learning models. Some of the many examples of the type of data annotations that can be done are e-commerce websites, customer surveys, emails, online reviews, social media accounts, chatbots, blog posts, and more. Here text data annotations help to read, comprehend and analyze the textual information and accordingly there are video annotations, image annotations, and more.

Let us talk about the prospects and the scope

Talking about enhancing your data-driven business with AI/ML initiatives can quickly make you realize the challenges of the process. The end result from your AI & ML can only be as good as the data being fed and here, data annotations play an imperative role. The aggregation, tagging, and labeling of the source data that is then used for AI & ML makes the process efficient and accelerates quality data output that can be optimized for actionable business insights. The scope of Data Annotation can be wider than you think.

Let’s go deeper into the scopes of data annotations:

• Training ML algorithms - Qualitative data annotations provide accurate training data to your machine learning process to gain an acute understanding of the real-world conditions which further enhances the learning algorithm and optimizes the data output. This can open a wide variety of opportunities for your business across industries.
• Enhancing AI-based projects - With the help of data annotations, artificial intelligence can rebuild itself if its performance drops noticeably. It can even go as far as to recognize emotions through human body language and voice tone. AI combined with good quality data annotations and ML algorithms can learn anything quickly and improve its intelligence multifold.
• Time & cost effectiveness - The futuristic promise that AI and ML give is eventually backed by progressive and well-versed data annotations as it plays a vital role in ascertaining a strong flow of the right type of data to your business data processes. In the long run, it most certainly benefits your business with timely information for data-driven business decisions to give your organization a competitive advantage.
• Providing better user experience - The primary purpose of AI/ML projects is to provide an ultimately immersive and engaging user experience that eventually simplifies their lives. Data annotations can seamlessly facilitate providing the most relevant and accurate information for the customers’ queries and resolve their conflicts with ease promoting flawless user experience.
• Providing A-grade actionable insights - When qualitative data annotations and data tagging are done then it can provide the right training data to your business AI models. This certainly empowers the data-process to produce the most effective and precise data output to feed your business leading to well-informed data-driven business decisions that boost your company’s revenue multifold.

How can you decide what’s good for you?

Since we have established that data annotations are a core essential for effective AI/ML in a data-driven organization such as yours. Also, data annotations are a complex process as well as a subjective one at that, you as a business have to consider several factors before deciding on how to fulfill your needs of data annotations. We don’t mean to be biased but if you consider us, at Straive as your chosen one for all your training data needs then we can assure you that we will put our best foot forward and see to it that you get the best there is. With our sophisticated approach assisted by human expertise along with superior machine-learning assistance, we will provide your business with excellent industry-standard training data. So pick up the phone and give us a call and let's help you with our best solutions.