Metadata Management & Data Governance
Use semantic metadata to extract more value from your data
To put it rather simply, metadata is data that gives information about other data. In other words, they are the labels or tags that can be added to data in order to describe it and ultimately make it more functional, actionable, and understandable. A novel, for example, is described by its genre, author, paperback vs. hardcopy, publishing company, and copyright date, which are all examples of metadata in its various forms.
Since metadata provides descriptive framework and structure, metadata management is key to staying competitive – especially in fast-moving markets. Praised by Gartner Peer Insights for metadata, the PoolParty Semantic Suite combines Knowledge Graphs, Text Mining, Natural Language Processing and Machine Learning to fundamentally change the way organizations deal with data. With PoolParty, companies can build a semantic layer that, when applied to their information architecture, enables them to automatically analyze and create rich metadata. With semantic metadata, they can bridge data silos and gain a unified view of structured and unstructured data.
The Semantic Web Company—vendor of PoolParty—has been named a Visionary in the 2020 Gartner Magic Quadrant for Metadata Management Solutions. Among the strengths of the PoolParty solution, Gartner emphasizes the combination of first and second-generation machine learning, the beneficial combination of knowledge graphs and NLP, and the combination of text mining and semantic classification to develop a comprehensive suite that supports multiple scenarios.
The biggest challenges for organizations without metadata management.
Manual data upkeep
While spreadsheets and relational databases are best used to support numerical data, much of an organization’s data, with an estimated 80% of business data across the globe, is rows upon rows of unstructured, text-based data. These large volumes of text require a great deal of manual time and effort to tag them with meaningful metadata and make them usable.
Simple metadata stuctures
Simply adding metadata in a linear fashion often leads to inconsistencies and is difficult to maintain. With PoolParty, metadata is instead centrally managed in the form of controlled ontologies and vocabularies to then link data sources into a high-quality knowledge graph.
Webinar: Boost Customer Experience with Auto-Tagging & Metadata
Success Story: Consistent metadata for international cooperation with REEEP
PoolParty Application Gallery: Get ideas and insights on how to use semantic technology.
The biggest changes organizations can leverage with PoolParty’s metadata management.
Active metadata makes data management processes intelligent and dynamic because it is overlaid with machine learning that is integrated with human context and knowledge. As a result, active metadata can not only highlight missing, incorrect, or anomalous data, but also help improve the quality of analytics by automatically correcting and enriching data to improve decision-making and avoid costly mistakes.
In a practical scenario, metadata management can help determine next steps in a workflow or business process. Suppose you are a company that manages a customer help desk with different products and services. Each associate is responsible for covering a different help topic (insurance vs. payment vs. product functionality, etc.), so it is important that customers are filtered to the right representatives depending on their issues. Using metadata and a ticketing system, customer tickets can be tagged according to these topics and sent along the right channels to the representative also tagged with this topic. Sophisticated rules based on metadata can help deliver the best quality interactions and services between organizations and customers.
Experience the major benefits of metadata management with PoolParty Semantic Suite today.
Data governance is one of the most demanded use cases for metadata management. Besides helping comply with regulatory and business requirements, metadata management helps assess the impact of a change within a data source. It also supports accountability for the terms and definitions of a business glossary to lead organizations towards the development of a standardized data model.
Automated data and risk compliance
Since data has become one of the most valuable assets to enterprises today, the risks to data security are diverse. In addition, organizations must comply with legal regulations as well as internal policies and procedures. Metadata management helps security and risk professionals be ahead of these two scenarios by classifying data according to risk and security needs. It facilitates data lineage, impact analysis and data management to reinforce privacy requirements.
Monitoring performance and making valuable decisions based on data should be at the forefront of any organization. Metadata management supports building a data catalog for the analytical uses of data across an organization. As a result, organizations avoid confusion and misinterpretation of information, which strengthens their ability to make educated business decisions.