Featured article by Jeremy Sutter, Independent Technology Author
Waterline catalog automatically collects all the data assets in Hadoop and secures it. This enables enterprise users to understand the entire inventory of data and assist in its management. This makes it easier for data engineers and scientists to access the requisite data for their in-depth analytics. In other words, data stewards can curate the data inventory in a much supple perspective. With waterline catalog, credible data is introduced and used to derive crucial insights to create and enhance great value.
It also helps data governance in the entire process by identifying the data heredity, metadata management and administering access control.
Importance of having data inventory and how to choose one
Nowadays, the worlds have become digital, and data is found everywhere. Data catalog has evolved from a nice-to-have to a mandatory requirement. This information will help you in understanding how you can select the best data inventory for your company or business. Let us first address the importance of having this list.
1. Importance of having this catalog
About a decade ago, reporting tools were quite multifaceted, and there was minimal data access in the development of reports meant for the masses. The organization of data, security, and its governance were easily controlled. Fast forward to today where reprint tools are readily available and easy to use. People have developed data cultures culminating in unprecedented data access and self-service.
The exponential growth witnessed with the emergence of cloud apps, IoT and digital transformation of the process has seen the rising of data sources. It is more difficult for the organization to secure and govern data effectively, thanks to the advancement, or rather, the evolving of privacy regulation. This is why waterline catalog has become a mandatory requirement to address the current data management needs. The introduction of data compliance regulations has made it necessary to have data inventory.
2. Selecting your data inventory
There are different solutions that come close to data inventory, but they do not meet the standard requirements. In your data inventory evaluation, you will also notice some answers that would be incorporated with a real data collection. If you have an excellent data collection, you will be able to search a business glossary of data sources as well as standard data definitions. This comes from automated data discovery, classification, and cross-data source recording. To fill a computerized data inventory, you have to analyze data values through sophisticated algorithms to tag the data automatically. You can also scan jobs or APIs that derive data from views, tables, and stored procedures.
An entirely populated data collection gives room for crowdsourcing, annotations, versioning and so on. The administrators of these catalogs ought to assign data source owners, subject matter experts, stewards, and consumers by way of policies that hinge on roles.
Data inventory capabilities
1. An automated filling of the catalog
This is essential to enhance the scanning and loading of metadata collected from a multitude of data sources. Efficient data inventories can use AI and machine learning in profiling, tagging, and filling objective metadata without compromising on quality.
2. Maintaining the freshness of tagging and metadata
Updating the existing metadata can be updated through new and incremental scans. This keeps the collection current, and it is essential when it comes to sensitive data or data that falls under the regulatory compliance policies.
Waterline catalogs have enabled different entities to replace manual metadata tagging with an automated process. This categorizes their data assets in their data pool, which incorporates new data as it is developed. It combines every field of data in the data pool while capturing and learning from group knowledge. The world today has become a data farm, and it is essential to have a very reliable data inventory that will help in the management of metadata and the administration the data access control. This is why data inventories have become crucial to addressing data management needs.
