Synthetic data and its importance for the development of your business | AI in business #101

It is a tool that, despite its technical complexity, offers simplicity and security in use, opening up new business opportunities. In this article, we will take a closer look at what synthetic data is, how it can support the growth of small and medium-sized enterprises (SMEs), and in which industries it will be widely used. Get ready for a dose of valuable tips and inspiration that can help your business grow.

What is synthetic data?

Synthetic data, as the name implies, is artificially created rather than collected from actual events. Generated using algorithms and computer simulations, it mimics real data while retaining its statistical and mathematical properties.

There are three types of synthetic data:

• simulation data – created using computer simulations, mimics certain scenarios,
• algorithmically generated data – produced by algorithms, are designed to imitate certain data patterns,
• AI-based data – created using AI technologies such as neural networks to mimic complex data patterns.

According to Gartner, by 2024, as much as 60% of the data used in AI model training will be synthetic data, which underscores its growing importance.

What is synthetic data used for in SMEs?

For small and medium-sized companies, which often struggle with limited resources, synthetic data can be the key to faster growth and innovation.

They make it possible to test and develop new products or services without the high costs associated with collecting and processing real data. They are particularly well-suited to tasks like:

• software testing – without the risk of exposing sensitive customer data or inconveniencing users when new versions of algorithms are introduced,
• AI model training – enabling the creation of more accurate and efficient models without having to buy databases or collect them yourself,
• business scenario simulation – helping to better prepare for various market conditions that are less likely to occur.

In addition, synthetic data allows you to experiment in a controlled environment, which is especially valuable during the prototyping phase of new solutions.

Benefits of using synthetic data

The main advantage of it is the lack of identifying data, which makes it an ideal tool for companies that want to test and develop AI models without compromising privacy. However, the use of synthetic data brings with it a number of additional benefits that can have a significant impact on a company’s operations. Here are some of them:

• provides high quality and balanced data, which is crucial for accurate analysis and decisions,
• eliminate the need for time-consuming data labeling , saving time and reducing costs,
• help reduce bias by creating more balanced data sets,
• minimize privacy concerns , which is especially important in an era of growing awareness about data protection.

Source: Datagen (https://datagen.tech/)

Which companies benefit the most from synthetic data?

Synthetic data is used in many industries, but it can be especially beneficial for companies that need sensitive, dangerous, or rare data. This can include data for:

• healthcare providers – enable the protection of patient privacy and enhance clinical research capabilities,
• manufacturers of autonomous vehicles – allow for the safe and secure testing of technologies under controlled conditions,
• financial sector – support fraud detection and market behavior analysis,

However, before you decide whether using it will benefit your company, carefully evaluate your needs. Ask yourself which types of data are critical to your business. Will it be images, structured data, or perhaps time series?

Also, evaluate the platform’s intuitiveness in terms of who will be using it on a daily basis, as well as the platform’s ability to integrate with your current systems. Make sure the provider has robust privacy practices that comply with industry regulations, and that the platform’s terms and conditions are compliant with emerging AI regulations.

Which provider to choose?

The choice of synthetic data provider depends primarily on the type of data the company needs. Among the most popular options, it is worth considering the following suggestions:

1. Mostly AI (https://mostly.ai/). Its main advantage is an easy-to-use platform that does not require advanced technical knowledge. It provides highly customizable synthetic data, including structured (tabular) data, images, video, and time series. It specializes in generating realistic data that protects user privacy and reduces bias in data sets. AI is most commonly used in the financial sector, retail, and software development companies.
2. Gretel (https://gretel.ai/) Gretel, on the other hand, focuses on structured and textual data, offering tools that easily integrate with existing systems. Their main advantage is privacy protection, which is applicable in finance or healthcare, where anonymity of data is a priority.
3. Datagen (https://datagen.tech/), specializing in 3D data, it offers photorealistic models of people. Their technology is used in the retail sector, in medical simulations, and the development of human-computer interaction using advanced AR and VR applications. Its main advantages are photorealistic results useful for simulating human interaction and developing augmented reality (AR) or virtual reality (VR) applications.

Źródło: Mostly AI (https://mostly.ai/)

Summary

Synthetic data opens up new opportunities for companies, letting them optimize processes, increase competitiveness and accelerate innovation. Its use allows them to explore new areas without compromising privacy and security. Therefore, it is worth considering the implementation of synthetic data in your business strategy to take advantage of its potential and benefits. We encourage you to learn more about synthetic data and how you can use it to grow your business.

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