The concept of Big Data is a relatively new one. It denotes the availability of vast volumes and sources of data, which were not available before. By itself, Big Data is powerful, and when combined with Artificial Intelligence and machine learning, the opportunities presented by this combination are just endless. As big data moves to the maturity phase, firms are now looking for ways to combine the scale of AI and the agility of Big Data processes to bring about an acceleration on the delivery of the much-needed business value.
The Power of Combining AI and Big Data
Most businesses are data-driven. As a result, firms with the right type and quantity of data has the upper hand over rivals. Convergence between AI and big data is promising. Firms can now access large volumes of broken down and categorized data by their usefulness. Traditional computer processors cannot process big data. Big data can best be processed by a GPU database, which has the flexibility needed to handle a significant amount of data of different types.
AI and machine learning emerged decades ago. Consequently, Firms were unable to fully benefit from these technological advances because of lack of sufficient volumes of data coupled with the lack of processors that would analyze large amounts of data in milliseconds. Therefore, Big data technologies can now convert large amounts of data into real-time data.
How Big Data benefits AI and Machine learning
As stated above, AI and machine learning have been in existence for some decades now. Lack of datasets of appropriate sizes prevented technologies that would provide meaningful learning and progress. The application of AI and machine learning in business has been facilitated by the ability to access Big Data.
Early data scientists and statisticians faced limitations in their use of sample sets of data. Today, Big data has made it possible for every data scientist to access and work with unlimited volumes of data. Instead of relying on samples, researchers can today rely on the whole data itself. Process large volumes of data within short periods of time because of big data.
Getting More Accurate Results
Today, data scientists and statisticians no longer need to rely on samples of data in their research. Instead, they can key in the large and granular data available and get more accurate results. As a result, a data driven approach is use for product research. Instead of a hypothesis base approach used in the past. Big data centers of excellence or analytical sandboxes can be used to separate redundant data from predictive and indicative data. Big data and AI help in creating an environment that favors and promotes data discovery through the process of iteration. Consequently, modern day businesses, which are data-driven can adapt faster, engage in more experiments and learn quickly.
How MetLife Leverages AI and Big Data in its Operations
Pete Johnson, one of the thought and technical leaders in the field of AI and Big Data is the face behind the application of Big Data at MetLife. This expert opines that Big Data empowers AI in three main ways:
- Machine learning has scaled up. Big data has made it possible for the development of scaled-up algorithms. Those tasked with facilitating and powering deep learning and recurrent neural networks.
- Big data technology- This technology has made it possible for organizations to process large volumes of data in relatively short durations.
- Availability of huge volumes of data. Therefore, big data has availed large datasets that were previously not available. Today, organizations and individuals can access transcription, ICR, image and voice files, logistics data and weather data. Drive the organization forward by using datasets.
Large volumes of data can be classified into different datasets with the help of big data. AI and machine learning can be used to facilitate data. To succeed in business, you must use AI and big data. Especially in organizations that are heavily dependent on large amounts of data.
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