How is big data connected to IoT? In addition, what is the relationship between AI, the field where its utilization is most anticipated? We will introduce examples of the use of big data and AI, and technologies that further evolve the connection.
How is big data used?
Even if you’ve heard of the word big data, you may not have a clear picture of how it’s actually used. What is big data and what fields are you expected to use it in?
What is Big Data
Big data is generally recognized as “a general term for technologies for accumulating, analyzing, and processing structured or unstructured data that occurs in large quantities and in real time, or the data itself.”
What defines this more clearly is what is said to be three V’s expressing big data.
Data groups that combine Volume, Velocity, and Variety are treated as big data. Volume represents the amount of data and its processing power, Velocity represents the speed of change and the frequency of updates that can be followed, and Variety is a variety of unstructured data.
In other words, “a group of data with various and large amounts of changes and the ability to process it” is defined as big data.
Read more about big data here.
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Big Data is based on three V-| challenges
Infield where big data utilization is expected
So what fields are this big data expected to be used in?
With the development and spread of IoT, data can be obtained from various things in modern society. You can collect data from everything from factory equipment, shopping that sells well, and words that are attracting attention on social media. This massive amount of data has the potential to create new value.
In particular, big data is turning a hot eye in the fields of logistics and production. By attaching IC tags to products and packages and attaching sensors to various parts of the production line, it is possible to grasp the flow of things. These have the potential to lead to various efficiencies related to production and logistics.
Artificial intelligence and AI are also the most highly anticipated areas for creating new value. Big data, combined with AI, opens up even more possibilities. In the production and logistics fields of the previous article, by analyzing the collected data with AI, it can be several times or several tens of times more effective than human analysis.
In this way, big data can be said to have infinite possibilities by connecting with AI, so various uses can be considered.
The Relationship between Big Data and AI and Issues
The connection between big data and AI with many possibilities. What is that relationship?
The Link between Big Data and AI
Ai research has a long history, and research had already begun in the 1950s. However, the research has been carried on to the present age while rekindling in the winter era by the wall several times.
The rapid development of AI research and development in recent years has been greatly influenced by technological breakthroughs caused by deep learning. Deep learning is one of machine learning systems in which machines automatically extract and learn the necessary data using multilayered structured algorithms. This deep learning requires a lot of raw data before extracting the necessary data, and big data is essential.
In this way, in order for AI to move as close as possible to the expected operation, the machine must accumulate learning. A lot of data is required to accumulate learning. For this reason, it can be said that the development of big data supported the evolution of AI.
Big Data and AI Challenges
The link between big data and AI has opened up great possibilities. But there are still challenges there.
- Safe handling of big data
Big data Is also about customer buying behavior in the big data that many companies demand. This customer’s information often contains a variety of personal information and requires the security of handling it safely. Even if we consider that personal information leakage by companies occurs regularly, it can be seen that it remains as a problem at present.
- An environment capable of supporting huge amounts of data
IoT is spreading at a terrible speed. As a result, the amount of data handled is also exploding. Creating an environment that can handle this huge amount of data is essential for the utilization of big data and AI. In addition, since the importance of real-time is increasing in the use of AI, processing speed is also required. Speed requires data-proof traffic and server performance to speed up
- Training data scientists Experts
Dealing with big data are called data scientists. Despite the advent of an era of big data and AI, there is a shortage of data scientists in Japan. There is an urgent need to train data scientists who are required not only for data analysis but also in statistics and programming skills.
Examples of big data and AI
Although there are still challenges in the use of big data and AI, the possibilities are endless and are expected to lead to new technologies. What are the new possibilities that can be created by combining big data and AI?
One of the most popular ai-based technologies is autonomous driving in automobiles. Autonomous driving is expected to be effective not only in preventing traffic accidents but also in reducing CO2 emissions. The most anticipated thing about autonomous driving is the trucks that support logistics. Labor shortages have become a serious problem in the transportation industry, and it is expected that autonomous driving will lead to improvements in the working environment.
Preventive maintenance is to inspect and repair areas that are likely to need repair in advance in the maintenance of machines. Predictive maintenance has evolved by utilizing big data and AI. AI analyzes past maintenance data to derive precursor signs of failure and timing of failure. By carrying out maintenance activities accordingly, it is possible to prevent the machine from stopping and increase productivity.
AI announcers are already active all over the world. Ai is making it possible to read smooth sentences that are as close to people’s way of speaking as possible. It can respond instantly to emergency broadcasts and can be used in repeated announcements. It’s also worth noting that there are no mistakes to say and that you can customize it to a voice quality and speed that is easy to hear for your audience.
Big data and AI-based analysis and forecasting of sales are used by many companies. Business analytics using AI is not the results of analysis for each such product, but also consulting that shows the way forward as a company. By combining not only data within the company but also trends and data of society as a whole, we predict the flow of society and present actions as a company. In addition, with the enhancement of big data, ai-based business analytics is evolving to the stage where intellectual activities that change into people can be carried out.
Further evolving the relationship between big data and AI
In recent years, technologies that evolve the relationship between big data and AI into more advanced and valuable products have attracted attention. That’s edge computing.
Edge computing is a technology that separates what can be processed at the edge, or field, instead of sending everything to the cloud, and divides processing between the cloud and the edge.
Instead of sending all the data directly to the cloud, you can optimize it at the edge before sending traffic faster. In addition, data required for control where real-time is critical is processed at the edge, and only the data that needs more refined and necessary is accumulated as big data. This also leads to improved learning accuracy of AI and contributes to the evolution of AI.
In this way, edge computing is a hot technology that improves speed and accuracy in the future of big data and AI. With the advent and evolution of edge computing, big data and AI have also evolved.
Big data is tied to a variety of digital technologies
We introduced the connection between big data and AI and edge computing that will further evolve it.
Big data is already being used in all fields, and there are high expectations for the connection with AI. Edge computing is attracting attention as an evolution of that connection. Big data, AI, and edge computing, By combining these three, there is a greater possibility of further expanding the range of utilization and creating new value.
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