Data is the mainstream in any business. While the global digital footprint is expanding drastically, managing the data has become an obvious challenge for any and every organization. AI is a valuable resource in the adequate management of data including providing advanced ways to improve data quality, accessibility and security. More and more advanced tools employed by AI and ML are hitting the channel to augment the data management process and enable the business for future-ready.
Assessing the data quality and managing the captured data is a critical part of every enterprise’s project strategy. Poorly managed data increases the complexity of decision-making and leads to increased difficulty in solving specific problems.
But the growth of Artificial intelligence has unlocked unique capabilities in analyzing data at a large scale and providing actionable insight from structured and unstructured data. Integrating AI-based solutions into the existing data architecture enabled the organization for higher-level data analysis and interpretation.
The use case of AI is it can automate the key functional areas of data management like Data Quality, Data Governance, Data Catalog and Master Data Management(MDM). The intelligent version of AI tools enabled organizations to transform their traditional data warehouse into a smart ecosystem by automating data collection, reducing errors, identifying duplicate data, completing missing data, and validating the accuracy of the data.
Advantages of using AI in the data management process
Nevertheless, managing a large dataset in the digitalization era is likely not be possible without AI tools. With AI, businesses can explore new possible ways to solve specific challenges they face.