The word big data is used in various places, and many people may feel that its importance is increasing. However, the exact answer to what big data actually is is difficult. Here, we will introduce the basics of big data, how to use it and examples, and the challenges when using it.
What is Big data
Big data is often seen as “large amounts of data.”. In the early days when the term big data was actually used, the goal was to collect large amounts of data and derive something from it. However, the word big data in use today is not defined only by quantitative size. It represents something that is a little more complicated and has different possibilities. Let’s take a look at what big data is and the idea of three Vs proposed as a clear definition for it.
Big Data expressed in three V’s
In the early 2000s, TAG Rainey, an ANALYST at an IT research firm, defined big data as requiring having three V’s. The three are volume, velocity, and variety.
When everyone hears the word big data, everyone thinks of “volume”. As you can see, TAG Rainey’s definition also includes the amount of data. In the first place, the idea of what big data will generate from a large amount of data is the basis, and with the evolution, the amount of data handled is even more enormous. The volume defined here also means the amount of data itself, but it also includes the ability to process that vast amount of data.
Velocity does not represent the speed at which data comes and goes. How often the data is updated and how quickly it changes. In particular, the data on the Internet is constantly changing, and unless it is a system that can respond to it, it is not possible to derive results in accordance with the situation. Big data also requires the speed of these changes and the corresponding update frequency.
Variety may be the most distinctive part of the difference between “just a large amount of data” and “big data”. In the case of data aggregation as before, the data was often formatted and stored as structured data. However, big data includes not only numerical data, but also unstructured information such as audio, video, text and email, stock prices and financial information. You also need the ability to process both structured and unstructured data.
As the definition of big data, this “three V” is mainstream, and to summarize these, big data can be described as “a diverse and large number of changes in the data group and the ability to process it”.
Big data includes systems that handle data
As expressed by variety in the definition of the three V’s, big data includes unstructured data as well as structured data such as numbers and strings. Data under these conditions has been difficult to handle with traditional systems, but there is a reason why big data is expected here. There is a growing expectation for the use of these unstructured data, which was previously difficult to handle.
Big data may represent the data itself, but that alone does not expand the range and possibilities of utilization. It must also include a system with the speed to keep up with the changes in this vast variety of information.
Examples of big data use
So when is big data actually being used?
Segregation of consumer behavior with eye tracking data
Eye tracking is a technology that observes the movement of a person’s eyes to understand where they are looking. There is an example of accumulating this eye tracking data and using it for analysis of consumer behavior.
Major beverage manufacturers incorporate eye tracking into vending machines to analyze the collected data to determine where and where products to place. This has led to an increase in the types of data on consumer behavior, improving the effectiveness of analysis and increasing sales.
Increase your site’s confidence with the frequency of ranking updates
The e-commerce industry may be the most enthusiastic about using big data. It is well known that the recommendation function is greatly effective for general e-commerce sites. Big data is utilized in this recommendation function. It is said that how big data can be utilized determines the outcome of e-commerce sites.
In addition to simply utilizing big data, the frequency of updates to recommendation functions and sales ranking functions is also emphasized as an element that leads to the trust of the site. The frequency of big data analysis and the speed at which the results are reflected are increasing in importance.
Specialties are specified from the data of the car navigation system
In some cases, data collected from car navigation systems is analyzed as big data and used safely for traffic. The car navigation system transmits the part where the driver stepped on the brake suddenly, and accumulates data on the server. The safety map was analyzed as big data and created based on the results. The car navigation system reflects the possible occurrence of traffic accidents predicted from big data analysis and notifies the driver. It has been reported that this has greatly reduced the incidence of accidents.
There are many other examples of how big data can be used. Learn more about how big data can be used.
→ Use case of big data – Utilization of big data that has already begun
Three barriers to the challenge of utilizing big data
Big data can do so many things, but there are still challenges. There are three barriers to the use of big data, and if these are not solved, the original effect cannot be created.
Infrastructure for data collection and analysis
Big data requires analytics, and analytics require the right data. When collecting this data, it may contain a lot of unusable garbage data. The more garbage data you have, the less efficient your analysis will be and the longer it will take to reflect the results. If it takes time, the real-time nature of the results may be lost and unusable.
In addition, it is difficult to utilize big data even if there is not enough systems for analysis or system cooperation between departments is not available.
In order to make full use of big data, it is necessary to develop the conditions and environment from data collection to analysis.
Data Storage and Security
One example of how big data is used is analyzing customer purchasing behavior. From this point, it can be seen that big data stored by companies often includes customer data.
The leakage of such information can lead to a loss of trust in the company and even make it difficult to operate the business. We must remember that IoT is widespread and everything is connected to the Internet, and we must be aware of the importance of the information we deal with. When you run big data, you need to pay close attention to security management.
The question of a heavy shortage of human resources
In Japan, the shortage of human resources is regarded as a problem in many industrial fields. The ict field is similar, and there is a shortage of professionals in handling big data. There is an urgent need to develop and secure professionals and data scientists who operate big data.
Big data utilization is changing various industries
We introduced what big data is and what challenges there are.
Today, various industries around the world are about to face major changes through the use of big data. Big data may change companies’ services, sales strategies, and even operational systems. Big data has so much potential and is expected to bring about lucrative change.
