Introduction to DataSense Technology
Artificial Intelligence is changing how data management and analysis is handled in the age of big data. Organizations are generating more data than ever before and the process of accessing data using traditional methods is not only time consuming but also poses a threat to the data sets. To handle this challenge, AI changes the way we view data in terms of structure, usability, and access. To understand data sense, we’ll take a brief detour and view how human senses work:
Sense and Perception
As human beings, we interact with the world using our five basic senses of sight, smell, touch, hearing, and taste. Each of these senses has an associated organ that sends a signal to the brain which in turn creates the perception that allows us as human beings to understand the world we are in.
We know that the goals of artificial intelligence are perception, reasoning, and learning. In data management, Artificial intelligence goals remain the same, and thus the birth of data sense technology. DataSense technology focuses on detecting data patterns, correlations, outcomes, and inference within the focus data. All the above parameters help to create perception which is the algorithms utilize to create structures, indexing, tagging, classifications among others. The third step is learning from how the users interact with the data whose perception has been generated through actions such as search, access, among others. DataSense technology has modernized metadata, catalog, and taxonomy management.
AI DataSense and Metadata
Traditional data analytics had a limitation in the types of files from which accurate metadata could be successfully extracted. However, AI Datasense can extract metadata from multiple file types in different formats, thus helping provide a better sense of what is in the data. This helps power a faster and smarter search performance.
How DataSense handles Metadata;
AI DataSense and Catalog
DataSense helps create a smart catalog that is important in selecting the right datasets to be used in the creation of machine learning algorithms. It creates indexes that make filters that are far-reaching, adaptive, and effective. It also helps users’ search to be smarter thereby saving time and recommending the data they might want to take a look at based on their job responsibilities. Recommendations made for search are usually based on business terms, contacts, departments among others.
Smart data catalogs assist in:
AI DataSense and Taxonomy Management
AI DataSense helps create categories and sub-categories thereby providing a unified view of the data. By discovering common semantics and terminologies across multiple data sets in the same or different formats. It also creates a hierarchy for the metadata that helps in controlling access and makes search faster. AI DataSense helps taxonomy management comply with data laws such as GDPR. For instance, the customer’s details can be categorized as Category A and the order details can be categorized as Categorized B together with their payment method. In today’s world where data protection laws are in almost all countries, avoiding litigation is a top priority for most organizations. By creating security levels for the data, the chances of accidental non-compliance are greatly reduced.
Benefits of AI DataSense Technology
AI DataSense technology has transformed how data is viewed and accessed by users. Metadata, catalogs, and taxonomy management have been made more efficient enabling ease in how data is accessed and shared. With machine learning capabilities, the algorithms used continue to increase their understanding of the organization’s data. Just like a human brain, AI driven DataSense technology has introduced perception, reasoning, and learning into data analytics.
Want to learn more about how DQLabs uses DataSense™ capabilities to enrich semantics for any type of data? Schedule a demo.