Collaboration is at the heart of any industry, and that’s only been further emphasized by developments in business intelligence. With strides being made in developing a data model, companies are seeing their workflows trend in the right direction, putting the spotlight on prior hindrances in customer service or product development. The ability to analyze this data for your company’s benefit is all about metadata management.
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Understanding Metadata
You’re probably wondering, what is metadata management? It’s the business discipline that takes a dataset and gives it meaning. Metadata takes the information received by your company’s data management team and improves its usability. Metadata provides context to understand and govern different systems, guiding your business through a digital transformation. This makes data easier to find, providing critical analytics for you and your business as needed.
Metadata is broken down into several distinctive types that provide information their own way:
- Descriptive
- Structural
- Administrative
- Reference
- Statistical
You can create metadata manually or rely on automation for integration. Manually creating metadata allows for greater detail, so it may be a wiser option for more information assets handled by a data governance team. If the information asset isn’t as important, not a lot of metadata is needed. A proper metadata management strategy helps to ensure that business decisions are being made with context and correct data sources.
Metadata Management Use Cases
With renovations being made in data integration almost daily, more companies are realizing that the information they have on hand is just a cloud of confusion with no business context whatsoever. Data may not be in a proper catalog, emphasizing the core problem: lack of data usability. Despite new innovations, this issue is only getting worse, as those gigabytes of unsorted data are now becoming terabytes and even petabytes.
That’s why it’s more crucial than ever to institute a metadata management system. These systems provide a great deal of help to everyone in a company from the CEO down to stakeholders by helping to answer particular questions about certain business processes.
From an analytics standpoint, metadata management clears the way for self-service data catalogs for users to search and understand according to the data they seek. This narrows the scope and saves hours of searching. From an operations outlook, managing metadata assets and data lineages can create a stronger business model, assuring customer and workplace satisfaction by looking into efforts that streamline business without going overboard.
On the compliance end, metadata models help companies achieve regulatory mandates to support data privacy. This allows data governance teams to zone in on critical data elements and document definitions.
Metadata Management Capabilities
With quality metadata, any workplace of any size can foster the power of collaboration. By taking raw data from each business user and placing it into comprehensive metadata management software, companies can arrive at solutions faster than before. This is thanks to real-time analytics and data integration tools that allow for metadata to be discovered and harvested into one place. It creates a great round for reference on occurrences within your sales or operations, while also highlighting the importance of regulatory compliance efforts.
By cataloging these critical data assets, a comprehensive solution can be put in place to effectively create a safe data warehouse to help your company map out its important decisions and information. From discovery and extraction to classification and lineage, metadata is as easy to breeze through as a business glossary for the information a business user may need. With available comments and tags, a metadata service works for the company utilizing it, and not the other way around. It also assures an emphasis on data quality, regularly tracking for additional metadata integration.