Data management, the process of structurally dealing with data, involves various activities that revolve around organizing, storing, protecting, and controlling this vital and critical element of any organization: its information.
In this way, it is important to understand that, to protect this significant asset, we must first recognize it. Otherwise, how could we protect something we don’t know about?.
Being able to discern what is worth protecting from our data and recognize its value will allow us to concentrate our attention and efforts on it because not all your information is sensitive or confidential, and that is an important assessment to make.
Luckily, a good exercise in data management can really help us with this, but how can we assure it?.
The Challenges of Data Management
Given that, today, organizations commonly generate a vast amount of data from various resources, a great portion of this can easily become unstructured, representing a challenge for any entity or corporation that is concerned about exercising an adequate process of data management that prevails over data security and prevents risk management related to cybersecurity threats.
One of the main problems that pose a large amount of this unstructured, unorganized, and unclassified data is the difficulty it represents for traditional data management systems to encompass it since it is an industrious, highly demanding task that requires a set of punctual characteristics, such as attention to detail, preciseness, and objective criteria of classification, to name a few.
So even if there are different ways of accomplishing this massive task of dealing with unstructured data, like consultancies (third parties that offer these services) or manual sorting technologies, these methods are most likely inefficient and will show slow results, not even being capable of analyzing and classifying the total information from an organization’s repository.
Artificial Intelligence (AI): A New Solution to This Matter
Fortunately, there is an effective solution for data management: artificial intelligence (AI) is revolutionizing data management by offering innovative results for these particular needs, giving your organization the guarantee of identifying, analyzing, and classifying all its valuable information assets with great precision in record time.
This is where AI and the famous machine learning algorithms come into play. By leveraging the power of AI, organizations can automate the process of classifying unstructured data, unlocking its true value.
AI models can be trained to understand and interpret the context, meaning, and intention of any unstructured data, enabling accurate categorization and organization.
For this purpose, a very remarkable trait of AI plays a big role: natural language processing (NLP), a branch of AI that focuses on understanding and processing human language. By working with NLP algorithms, artificial intelligence can analyze textual data, such as emails, documents, receipts, bank account information, etc., and extract key information within its own contexts, such as topics, entities, sentiment, and intent.
These algorithms can automatically classify unstructured text into predefined categories, helping organizations identify their valuable information and the emerging issues that might revolve around it.
How Does AI Work, and How Does It Relate to Data Management?
AI systems simulate human learning by working with iteration practices that are being processed until a pattern is perceived, which is a logical mathematical formula that will lead us to a result or inference.
AI machine learning faculties permit it to find all the possible patterns —thousands of them— in a short time and with great precision.
In the process of data classification, for instance, once the algorithm is trained, we obtain a formula, that is, a set of parameters that indicate the level of confidentiality of a document: a model.
Depending on the data that this model consumes as input, it will make an inference, that is, a verdict, about what type of data category it belongs to.
The Benefits of AI Applied to Data Management vs. the Human Factor
There are numerous benefits related to the use of artificial intelligence in data management that make an interesting contrast to the manual exercise found in the human factor. Among these benefits, we can highlight:
Accuracy: AI can achieve an outstanding level of accuracy in classifying data. Since its algorithms are designed to unceasingly learn and improve from the experience they gain by interacting with information, they become more and more accurate over time as more information is provided to them.
This way, the AI-automated classification eliminates human error by always aiming for consistency that is improvement-oriented.
Although it is important to note that this level of accuracy will depend on the quality of the data that the algorithms are trained on, for example, for training the algorithms on identifying and classifying sensitive information, they would have to interact with the confidential or sensitive patterns that this type of data has, so they can recognize them in the future.
- Speed: AI algorithms can process large volumes of data quickly and in record time, meaning that data classification can be done in much less time compared to manual methods. This way, AI allows the process to be automated, freeing up time and human resources for more strategic tasks.
- Scalability: AI allows you to handle large volumes of data without problems. As organizations tend to generate more and more data every day, the scalability that AI systems permit is crucial. They can accommodate and process large amounts of data without requiring significant new conditions, and this will actually benefit their performance, as the more experience they get, the more their algorithms can learn and improve from it.
- Deeper data analysis: AI not only classifies data, but can also extract valuable information and provide deeper insights about it. AI algorithms can identify patterns, trends, and relationships in the data they analyze, helping organizations gain meaningful insights for making informed decisions.
- Automation of repetitive tasks: Manual data classification can be a tedious task for any human, as it tends to be a repetitive task. AI can automate this process, allowing employees to focus on more creative and strategic tasks that will benefit the organization. By freeing employees from routine tasks, AI can increase productivity and improve job satisfaction.
- Improved data security: AI can help identify and classify confidential or sensitive information in data, which improves data security. AI algorithms can automatically detect personal data, financial information, or any other type of sensitive information, allowing organizations to implement appropriate security measures to protect that data.
- Unified classification criteria: Subjectivity can play an ominous role in the process of data management, since what fits into the labels of what is confidential or sensitive for one person might not be the case for someone else. With AI systems, human errors and biases are minimized, ensuring a more reliable and standardized approach to data organization.
Kriptos: A Reliable Solution
Kriptos applies all the aforementioned characteristics and focuses on improving the data management of your organization by using AI technology to identify, analyze, and interpret the sensitive and confidential information that your company manages.
In this sense, Kriptos algorithms provide a comprehensive diagnosis of your company's information and IT assets, which is a fundamental tool for data protection and necessary to enrich your internal strategies and cybersecurity practices with informed decisions.
