Xplore: Metadata Management
In this third issue of a series of articles about Xplore, our Data Discovery and Metadata Management platform, we focus on metadata management. In our first article, we cast the light on Data Discovery in Xplore explaining how essential it is for finding the different data assets in the firm and exploiting existing datasets for use by as many data consumers as possible. In the second article, we looked at Data Classification in Xplore and its pivotal role in organising the firm’s data, making it more efficient to search and navigate and reducing redundancies and inconsistencies which would otherwise compromise data quality.
What is metadata and why is it important?
Simply put, metadata is data about data. It is information that describes various aspects of your data, but not its content. If you compare your dataset to a book, the metadata of your dataset would include the book title, the author’s name, the ISBN, the publication date, a description of the book and possibly some user reviews! Metadata, when managed properly, makes your dataset more discoverable and helps users assess if the dataset is relevant for their needs even before they access the data itself. Well-managed metadata also promotes data quality, integrity and reliability.
How does Xplore facilitate metadata management?
The journey of metadata in Xplore starts at data discovery, where crawlers discover the DataSets on a DataStore and pull their metadata into Xplore. The metadata captured by crawlers is the technical metadata and it includes the name of the dataset, its type, its location and the schema of the data (e.g. the column names and types in case of a .csv file). In addition to the technical metadata, data managers and, in some cases data consumers, can add a layer of user-added metadata to describe the data further. This could comprise a user-friendly name for the dataset, a description about the data, additional notes or even user reviews. This supplementary layer of user-defined metadata captures the human knowledge that would otherwise remain undocumented. Tags can also be attached to the dataset to make searching and filtering more efficient. Remember, the richer the metadata, the better described the dataset is and the more likely it is to be picked up in searches and the more useful the metadata would be for users browsing the data. By consulting the metadata (be it the schema of the dataset or some notes left by a user), data consumers can evaluate the usefulness of datasets and thus find what they need more quickly and more efficiently.
Different Types of Metadata in Xplore
Because user-defined metadata can vary with the context of the data and the needs of a firm, Xplore allows data managers to enrich the metadata model with custom metadata fields tailored for their specific use cases. For instance, you could add a Security Level field to reflect the level of confidentiality or security assigned to a dataset or an Intellectual Property Constraint field that dictates the extent to which a dataset can be used in a compliant way. Custom metadata fields can be configured as free-text fields, drop-down lists, date fields or checkboxes.
Configuring a Custom Metadata Dropdown Field in Xplore
Stay tuned to find out more about the other functionalities and features of Xplore in subsequent articles. In the meantime, if you would like to enquire about Xplore or request a product demo, please contact us. We would love to hear from you!