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The relationship between Big Data and AI

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Big data and artificial intelligence are able to collaborate to help organizations reap a variety of benefits. Since AI requires large amounts of data in order to learn and make decisions, it is able to utilize big data as a source of raw material.

While big data can store data from various sources, AI can further categorize and filter the content. The more data AI has, the more accurate its output will be. Due to this, these two systems work well together and can offer transformative capabilities for companies, leading to significant advancements for a variety of industries. 

What Is Big Data?

Big data refers to a large amount of data that is generated at ever-increasing rates, making it very hard to manage. In order for information to be classified as big data, it must contain the three “V’s” of volume, variety, and velocity. This data helps reveal valuable insights that traditional data methods cannot achieve.

The data can be collected through various sources such as comments on social networks, information from apps or electronics, questionnaires, product purchases, electronic check-ins, and more.

There are three types of big data, which are defined as structured, unstructured, and semi-structured. Structured big data is any information that can be stored, accessed and processed in the form of a fixed format. Unstructured data is information with an unknown form that poses multiple challenges for processing. Lastly, semi-structured data is information that can contain both forms of data. An example of semi-structured data is data represented in an XML file.

Defining AI

Artificial intelligence, or AI, involves the creation and implementation of computer systems that are capable of reasoning, logic, and decision making. AI relies on data in order to function properly. This data makes it possible for machines to learn from experiences, adjust, and even perform human-like tasks.

The primary goal of AI is to eliminate any tedious tasks and assist in managing extremely detailed information. Additionally, it has the ability to consume and process massive datasets and develop patterns, aiding it in making decisions for future tasks.

When it comes to classifying artificial intelligence, there are various stages that have been defined. These AI stages focus on reactive machines, limited memory, theory of mind, and self-awareness.

  • Reactive machines are those which utilize AI that can only react to certain types of stimuli based on preprogrammed rules. They do not use memory and therefore cannot learn with new data.

  • Limited memory AI is the most modern type and can use memory to improve over time by being trained with newer data. This AI is typically part of an artificial neural network.
  • Theory of mind doesn’t currently exist, but ongoing research for this stage is underway. It pertains to AI that can emulate a human mind and make decisions similar to a human, such as recognizing and remembering emotions.
  • Lastly, self-aware AI, should the stage ever be reached, would feature machines aware of their own existence, giving them true sentience. Machines under this category would be as intellectual and emotional as a human being. Like the theory of mind stage, this AI stage is not currently obtainable.

Benefits of integrating Big Data with AI for your company

While organizations can benefit from big data or AI independently, they can combine both to reap valuable results, such as boosting a business’s performance and efficiency. Additionally, by using AI in conjunction with big data, companies can get advantages like:

  • Obtaining valuable insights – Big data and AI allow you to analyze large sets of data very quickly and efficiently. You can save time for other priorities and identify patterns or trends more easily.
  • Time-saving automation – Artificial intelligence and big data help by automating time-consuming tasks. They can assist with screening and cleansing data, so that the only thing remaining is quality information.
  • Discovery of hidden opportunities – Big data and AI have made it possible to fully analyze extremely large datasets. In the past, you’d miss a lot of opportunities because you wouldn’t be able to dissect so much information.

Any industry can gain value from AI and Big Data

AI and big data can transform industries by allowing them to make data-driven decisions and helping streamline processes. Some fields that can benefit from utilizing these tools include:

  • Healthcare
  • Finance
  • Retail and ecommerce
  • Manufacturing
  • Transportation and logistics
  • Education
  • Energy and utilities
  • Marketing and advertising
  • Agriculture
  • Government
  • Human resources
  • Gaming and entertainment

How these systems complement one another

Some of the ways that big data and AI work with each other include through the following:

  • Pattern recognition and prediction capabilities – Certain techniques of AI such as machine learning can process large datasets to identify patterns that may be hard for humans to spot. By continuing to analyze data, it leads to more informed decisions and, ultimately, better results.
  • Personalization – Big data allows companies to collect certain information regarding preferences, behaviors, and interactions. AI can then take this data and create personalized experiences, such as product recommendations or content curated to that person.
  • Natural language processing (NLP) – Natural language processing is built on big data. With massive amounts of data available, AI models can be trained to understand and generate applications such as virtual assistants and chatbots.
  • Fraud detection and security – Combining big data with AI allows you to analyze large datasets to identify any unusual patterns, letting you prevent any fraudulent activity. 
  • Healthcare and medical applications – With AI’s ability to process big data, it can discover key areas of patient care that may need assistance. Additionally, you can analyze large volumes of medical records, data and clinical studies. 
  • Supply chain optimization – Big data combined with AI can help in the supply chain field by predicting demand and improving inventory management.
  • Natural resource management – Artificial intelligence can examine large amounts of environmental data collected through satellites to improve resource management. This gives organizations the ability to better tackle challenges such as climate change, deforestation, and more.

As you can see, big data working side by side with AI can produce some impressive results. We’re fascinated with these implications and look forward to the changes on the horizon.

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Ally Hosler works with Kent State University’s Ambassador Crawford College of Business & Entrepreneurship.