How to use Big Data to Improve Machine Learning

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The rise of digital technologies in the last couple of decades allowed information to flourish and grow exponentially. People and businesses produce huge volumes of data on a daily basis, so it is getting more difficult to analyze information and draw meaningful conclusions out of it.

This is where machine learning and big data come into play.

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. As such, machine learning helps companies or organizations complete work that people cannot manage single-handedly.

On the other side, big data represents any voluminous amount of structured, semistructured and unstructured data that has the potential to be mined for information. Working together, these two systems can give a big boost to the business.

In this post, we will show you how big data improves machine learning.

The Importance of Big Data for Machine Learning

AI makes it possible for machine learning to self-improve and increase the level of knowledge, but this process is much slower if there is not enough information available for analysis. Big data helps machine learning by providing data volumes necessary for a reliable analysis.

This way, the whole system is getting smarter over time. It can make precise evaluations and help companies improve their operations. For instance, machine learning and big data enable Netflix to give personalized recommendations to the clients, maximizing the profit in the long-term perspective.

At the same time, big data goes beyond individual needs and also gives machine learning insights into territorial preferences. It takes into account cultural differences, demographic features, and other location-related inputs, helping companies to tailor operations so as to fit each market individually.

Besides that, AI is becoming more focused and niche-oriented with the help of big data. Each field of work and business has a different set of rules, so it is important to feed machine learning with enough data to sharpen its abilities.

Practical Value

Now that you’ve seen how big data assist machine learning on a more general level, it is time to see a few real-life examples. Here are some of the most interesting applications:

  • Healthcare

Healthcare has been gradually adopting big data technology because it improves medical interventions in a variety of ways. Namely, big data ensures more accurate predictions, helps prevention, improves clinical trials, and enables a more personalized approach to healthcare.

Patients with sensors and wearables can be easily monitored in real-time, thus minimizing the risk of unexpected issues and late interventions. Besides that, most patients can go home and come back only in case health indicators reveal something unusual. This cuts down the expenses of on-site treatment and makes the healthcare system much more efficient.

  • Finances

Machine learning and big data control a big part of the global financial market. AI monitors thousands of relevant indicators that influence stock exchange and currency trends. It allows round the clock financial services but also prevents frauds by analyzing an entire history of similar cases and detecting potential threats.

  • Retail

Retail companies, particularly e-commerce, exploit machine learning to the fullest extent. We already mentioned the case of Netflix, but there are other notable examples. For instance, Amazon does the same thing – it creates personalized offers based on the history of searches.

But it’s not only about online commerce. Traditional retail can also benefit from big data. According to the research, in-store analytics has a potential value stake of $61 billion through 2018, specifically for its ability to improve workforce efficiency, provide real-time information, and offer operational and shopper analytics.

  • Customer experience

Customer experience goes hand in hand with retail business. AI-based services like chatbots allow you to approach each prospect and become proactive in your desire to convert leads. This makes your customers more satisfied, while the company gains profit and expands the base of loyal clients.

Modern companies embrace machine learning as the powerful system of business analytics, but they upgrade it with big data to obtain even better results and predictions. In this post, we showed you how big data improve machine learning.

Are you thinking about using big data in your business? Do you already have any experiences in this field? Feel free to share your thoughts with us in comments and we’ll be glad to discuss it with you!


About the author: Olivia is a young journalist who is passionate about topics of digital marketing, recruitment and self-development. She constantly tries to learn something new and share this experience on aussiewritings.com  as well as on other relevant websites.

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