One of the technological trends that are marking and will mark in a more impressive way each of the areas of our daily life is Artificial Intelligence, a tremendously advanced science at the service of multiple applications. His way of working is based on the compilation of a huge amount of information that is stored in intelligent databases for later analysis and understanding.
When we refer to the intelligence of this data, it is because, in essence, this is the purpose of AI: to be intelligent. And consequently, it is the goal of all next-gen apps that will change the way things are done. It is not a matter of simply storing the information, but of interpreting it.
We have a great example in autonomous driving vehicles: cars that have the intelligence to respond on their own to unforeseen events and rapidly changing conditions. Their method is based on the intelligence of the data: after collecting an uncountable amount of information, they know how to give it meaning and act accordingly.
Big Data Is Not Enough
Computing should also focus on meeting this goal. We are aware that information has to be secure and connected, but we must also recognize that next-generation products need something else: to know the reason for the data, when and where it is produced, and to analyze its repercussion.
Every two years, companies double – at a minimum – the amount of data they store. But many of them stay there, they do not take more steps in the management of their information.
The future of computing in general and of data management, in particular, involves going much further in the process, creating intelligent information platforms. In other words, the short-term challenge is the use of intelligent databases that know how to understand and reason.
Elements Of Data Intelligence
Smart databases are based on two essential components that every company must include in its information management platforms. These are:
- The live data map: constantly updates the metadata (structural, semantic, usage and of any kind) of all the information that flows in the company.
- The Inference Engine: Analyzes the data to apply logical rules and obtain new information. You can deduce the user’s intentions and provide recommendations on the best way to use this data depending on its purpose.
It is, therefore, a matter of combining the traditional database with the techniques developed in the field of Artificial Intelligence. This union makes it possible to manage complex knowledge through simple information processing.
Advantages Of Smart Databases For Companies
Since we live in a digital age marked by data as the main axis of any business activity, the information management approach must know how to take advantage of all the benefits that advanced technology offers.
The fact of integrating Artificial Intelligence techniques in databases offers these advantages:
- Deduction of facts through the analysis of isolated data and the search for common links.
- Greater flexibility and capacity for managing complex, high-volume data.
- Decreased information analysis time.
- Elimination of format and quality problems when combining data sets.
- More immediate access to information
- Data recovery made easier.
- More advanced capabilities for developers.
Ultimately, smart databases don’t just read data, they interpret it. The objective is to go one step further in the career of Artificial Intelligence and take advantage of the great benefits that its application offers companies in the management of their information.
