Artificial Intelligence

How AI Helps Improve the Management of Enterprise Data

The gathering and management of data are crucial in building artificial intelligence. It is impossible to create AI systems without prepared and managed datasets. Interestingly, AI comes full circle in its relationship with database management, as it can actually help improve the latter.

AI benefits in enabling data-driven businesses as they strive to transform towards greater operational efficiency.

The reality of having fully AI-enabled databases may still be years or decades away, but the benefits of artificial intelligence on data management are undeniable. These benefits can be summarized as follows.

1. Better query performance and accuracy

Employing artificial intelligence in database querying can dramatically improve the overall accuracy of search results. This accuracy is not based only on the keyword or phrase used per se. It also takes into account the context of a search query.

For example, the identity of the person doing the search and the other terms previously used can set the context for the query and yield more accurate results.

2. Enhanced operational efficiency 

Database efficiency is a common issue for a lot of organizations. This issue is particularly true for enterprises involved in AI development. They need a reliable data management platform that effectively automates unstructured data processing.

Having a system that makes it easier and faster to use large amounts of data is crucial. Artificial intelligence automates database governance and monitoring. It also facilitates the intelligent management of resources used whenever data queries are made. 

3. Improved data exploration

Data access and preparation are among the most significant barriers to the adoption of machine learning.

AI can help address this barrier by expediting data exploration while reducing development cycles by integrating developer tools and frameworks. This allows data scientists to do a lot more with less time.

4. Data analytics for more users

Traditionally, data analytics is not available to everyone in an organization. It is limited to a few key persons who are expected to make critical business decisions. These decisions can be significantly improved when the decision-makers have access to the analyses of raw data.

AI is useful in performing inexpensive data analytics at different scales for different purposes, which can serve the needs of most users in an organization.

5. Database administration automation

Effective AI and database administration integration are important in efficiently dealing with the staggering growth of data volumes that enterprises have to deal with.

Conventional database management cannot keep up with the rapid growth of data used in the interconnected modern world. There is a need for smart automation to allow database administrators to focus on tasks that require more sophisticated decision-making and ingenuity.

More focus can be appropriated to high-impact tasks like data security with database administration automated effectively.

Enterprise data management are getting more and more resource-intensive and complicated over time as organizations accumulate more kinds and volumes of data.

However, with the help of AI, the burden of effectively preparing and managing data eases, especially when it comes to machine learning.Image:

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