Big Data Big Data has become a buzzword in today's world. Big Data technologies allow us to capture, store, manage, and analyze massive (in volume), complex (in variety), and rapidly changing (in terms of transfer speed and structural variability) data. This was not possible with traditional computing technologies.
This term is becoming increasingly important in the business world. Companies use data for numerous activities, such as better understanding customer behavior, identifying new opportunities, and optimizing their operations.
For example, Atlantis Technology, the technology company of the Binter Group, uses Big Data to analyze the success of its marketing campaigns. First, they divide potential customers into two groups, and the marketing campaign is targeted at only one group. During the campaign, they track clicks on the website, on Google ads, and so on, until a sale is made, if applicable. Using this data, they analyze the behavior of the customers affected by the marketing campaign and compare it with the other group to determine whether the campaign was truly successful or if they would have achieved the same success without it.
Big Data plays an important role in the healthcare sector. In recent years, healthcare services have been evolving their use of big data to improve patient care and reduce costs, since large datasets allow for the early identification of high-risk patients. To illustrate this, we can look at the case of the University Hospital of Our Lady of Candelaria, which uses large quantities of images of patients' eyes to determine the degree of diabetic retinopathy.
Big data is also used in the public sector. Governments are using it to improve services and create better policies. For example, the Canary Islands government publishes passenger arrival data for the islands' various airports and ports. This is crucial for companies like TITSA, which analyzes this data to determine peak arrival times and increase bus frequency in those areas. This helps them focus resources on the right areas and create more effective public safety strategies.
According to Gartner's definition from approximately 2001 (and which remains the standard definition): Big data is data that contains greater variety and is presented in increasing volumes and at a higher velocity. This is known as "the three Vs":
- Volume: The amount of data matters. With Big Data, you'll have to process large volumes of low-density, unstructured data. This could be data of unknown value or data from equipment with sensors. In some cases, this can amount to tens of terabytes or even hundreds of petabytes of data.
- Speed: Speed is the rate at which data is received and (possibly) at which action is taken. The highest data speeds typically involve data being transmitted directly to memory, rather than being written to disk. Some smart, internet-enabled products operate in real time or near real time and require real-time evaluation and action.
- Variety: Variety refers to the diverse types of data available. Conventional data types were structured and could be clearly organized in a relational database. With the rise of big data, data now comes in new, unstructured data types. Unstructured and semi-structured data types, such as text, audio, or video, require additional preprocessing to gain meaning and enable metadata.
IBM describes Big Data by incorporating two additional Vs:
- Variability
- The way data is captured can vary from time to time or place to place, creating a certain dependence on the context in which the information is collected. This variability means that data can only be meaningfully interpreted when the context is taken into account. The technologies that make up a Big Data architecture must be flexible enough to adapt to new changes in how data is obtained, stored, and processed.
- Worth
- The ultimate goal of Big Data is to extract value from all stored information through various processes, efficiently and at the lowest possible cost. It is crucial to ensure that the knowledge generated is based on accurate data. Therefore, a Big Data system must extract this value in the form of new information in the most optimal way possible, adapting to all existing and future formats.
From the Chair we will promote dissemination, training and research in Big Data helping public and private entities in the Canary Islands to learn and apply these technologies so that they can become more efficient.
