Although we may sometimes take it for granted, machine learning is all around us.
Some of our most important modern technologies, such as personal assistants like Siri, or the algorithm Google uses to refine its search engine, wouldn’t be able to operate without it.
Machine learning also plays a role in automated enterprise metadata management. It has influenced companies to make vital improvements that have bettered their overall output. In this article, we’re going to examine the relationship between machine learning and metadata management, how machine learning improves the quality of Business Intelligence (BI), and the ways in which you can apply these learnings to your own organization.
How Does Machine Learning Improve Metadata Management Automation?
Automated metadata management tools and machine learning are deeply connected. How? Well, machine learning uses metadata information such as file types, origin points and file creation dates to find connections between information sets. Through the exploration of different patterns, machine learning understands how to effectively and quickly organize information.
Metadata that comes from the myriad of data systems and storage points managed by today’s enterprise data catalogs, is often scattered and difficult to correlate. BI teams may spend hours or even days trying to locate connections between these disparate data points.
With the right machine learning metadata management strategy in place, the same task that would typically take hours can now be cut down to only minutes. Instead of wasting time manually tracing your data to locate metadata errors, your BI team is now free to dive deeper into insights.
Applying machine learning for metadata management reduces the time it takes to identify valuable connections within the mountains of data that an enterprise has accumulated. Machine learning also improves the process of accessing, understanding, and organizing data; thus, delivering enterprise-wide benefits.
Machine Learning for Data Management Uncovers Important BI Insights
Implementing machine learning for metadata management helps improve overall BI understanding. Teams will now be able to collaborate more effectively, deploy data with confidence and increase productivity.
By combining the benefits of machine learning with the information inherent in metadata management, BI teams can trace all data lineage throughout the organization to find:
- The data’s origin
- Any changes the data underwent during its movement throughout the company’s various BI systems
- Any gaps or dead-ends the data encountered
This allows teams to perform a deep-dive into any issues affecting the health of the data or skewing analyses. With powerful data lineage tools backed by artificial intelligence solutions, BI teams can deliver stronger, more accurate reports to executives. This supports more informed decision-making and brings about greater success for the organization.
Your Company Can Effectively Elevate Metadata Management with Machine Learning
Machine learning platforms process metadata in real-time, offering advanced insights into data at the push of a button. The platform will then process data elements that may occur tens of thousands of times throughout a dataset in just a few seconds. It will then deliver an actionable analysis.
Operation is so easy and intuitive that any company can utilize machine learning for enterprise data management, helping to increase transparency throughout the organization. Regardless of department or where team members are located in the world, they can all access the same high-quality data reports. This democratizes the use of these tools and allows for different departments to lend their expertise in understanding each report. It also unlocks understanding that would have otherwise remained hidden.
Artificial intelligence-powered metadata platforms benefit many different industries, including insurance, manufacturing, healthcare and finance. This technology helps varying enterprises rethink their data processing workflows and become more efficient in their day-to-day BI operations. It is no surprise that more and more small and medium enterprises are adopting machine learning business intelligence tools. Automated data lineage, data discovery, and business glossary/data dictionary help companies achieve better and more accurate results.
