How Do Big Data and Artificial Intelligence Work Together?

Writer : Michael Aurora EG

How Do Big Data and Artificial Intelligence Work Together?

Before the world even knew what big data was, it was engulfed in it. Big data had amassed a massive amount of stored information by the time the term was coined, which, if properly analyzed, could reveal valuable insights into the industry to which that data belonged.

IT professionals and computer scientists quickly realized that sifting through all of that data, parsing it (converting it into a format that a computer can understand), and analyzing it to improve business decision-making processes was far too difficult for human minds to handle. To complete the enormous task of extracting insight from complex data, artificially intelligent algorithms would have to be written.

As companies expand their big data and artificial intelligence capabilities in the coming years, data professionals and those with a master's in business analytics or data analytics are expected to be in high demand. The goal is to keep up with and leverage the massive amounts of data generated by our computers, smartphones, tablets, and Internet of Things (IoT) devices.

AI vs. big data

At this point, big data is unquestionably here to stay, and AI (artificial intelligence) will continue to be in high demand for the foreseeable future. Data and AI are combining to form a synergistic relationship in which AI is useless without data and mastering data is impossible without AI.

We can begin to see and predict upcoming trends in business, technology, commerce, entertainment, and everything in between by combining the two disciplines.

How Artificial Intelligence (AI) is used in Big Data

The internet now offers a level of detail about consumer habits, likes and dislikes, activities, and personal preferences that was previously unavailable. Social media profiles and activity, product reviews, tagged interests, "liked" and shared content, loyalty/rewards apps and programs, and CRM (customer relationship management) systems all contribute potentially insightful data to the big data pool.

Collecting consumer information

One of AI's most valuable assets, regardless of industry, is its ability to learn. Its ability to recognize data trends is only useful if it can adapt to those trends' changes and fluctuations. AI can determine which aspects of customer feedback are important by identifying outliers in the data and making adjustments as needed.

Artificial intelligence and big data are now seemingly inseparable due to AI's ability to expertly work with data analytics. Every data input is pulled from AI machine learning and deep learning, which is then used to generate new rules for future business analytics. However, issues arise when the data being used isn't good data.

Business analytics

According to Forbes, a combination of AI and big data can automate nearly 80% of all physical labor, 70% of data processing work, and 64% of data collection tasks. This suggests that, in addition to their contributions to marketing and business efforts, the two concepts have the potential to have a huge impact on the workplace.

Because fulfillment and supply chain operations, for example, rely heavily on data, they're turning to AI developments to provide real-time insights into customer feedback. Businesses can structure their finances, strategies, and marketing around the flow of new data in this way.

Before running the data through a machine learning or deep learning algorithm, there must be an agreed-upon methodology for data collection (mining) and data structure. Professionals with degrees in business data analytics can help with this. Companies that are serious about getting the most out of their data analytics will prize them highly.

The fusion of artificial intelligence and big data

AI and big data can complement each other to achieve greater results. First, data is fed into the AI engine, which improves the AI's intelligence. Next, for the AI to function properly, less human intervention is required. Finally, the less people are required to run AI, the closer society will be to realizing the full potential of the ongoing AI/big data cycle.

Humans who have been trained in data analytics and AI algorithm programming will be required to participate in this evolution.

The ultimate goals of AI, according to software company XenonStack, are as follows:

  • Reasoning
  • Automated learning and scheduling
  • Machine learning
  • Processing of natural language (the ability to understand human speech as it is spoken)
  • Vision in a computer (the ability to extract accurate information from an image or series of images)
  • Robotics
  • General intelligence

Massive amounts of data will be required for these AI fields' AI algorithms to mature. Natural language processing, for example, will be impossible to achieve without millions of samples of human speech that have been recorded and broken down into a format that AI engines can understand.

As AI becomes a more viable option for automating more tasks, big data will continue to grow in size, and AI as a field will expand as more data is available for learning and analysis.

Big data and artificial intelligence could be the key to your future success.

The online Master of Science in Business Data Analytics degree from Maryville University is focused on meeting the demand for business analytics experts. Graduates of this online program will be qualified to work as statisticians, data scientists, data analysts, or actuaries in the workforce.

Students can learn how to manage large data sets, orchestrate multiple infrastructures, monetize data, and make decisions based on valuable analytics insights at Maryville University. Employers will value graduates because they will be given the training and knowledge to combine business operational data with the most up-to-date analytical tools.

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