The world of unstructured data – examples of which include documents, images, audio, and video – is growing faster than ever before. IDC, forecasts that 80% of all global data will be unstructured by 2025. With the proliferation of data and distributed storage technologies, management of data is becoming more challenging. Data is accessed from different locations through different interfaces and protocols. Data is modified by users, and contents and properties are changing rapidly. Data also moves from one storage location to another making it hard to search and access. This makes it difficult to abide by data security compliance regulations that mandate stringent data governance. In addition to adopting a data-driven management approach, organizations are seeing increased value in employing metadata-driven management techniques to classify, organize and manage the massive amounts of data that gets generated and stored. Let us take a closer look at what metadata is in the context of file and object storage and how it plays a crucial role in simplifying and streamlining unstructured data management.
What is Metadata?
Metadata is information about the actual data that gets written to the storage media. Metadata identifies the properties of a file or object and helps specify how it should be handled. For example, the content of a file that gets written to a file server will have some metadata about the file type, size, date of creation, last modified date, last read date, etc. These properties can be used to glean information about the file for deciding placement, protection, and other data management operations. For example,
- Based on the last accessed date, the file can be moved to cold storage.
- Based on the file type or size of file, it can be moved to a specific storage location.
The of metadata suggests that metadata will usually contain details about the data that answers one of more of the following seven questions: What, When, Where, Who, How, Which, and Why.
Metadata can either be fixed or customizable. For objects, metadata is mostly customizable and can have any property or characteristic that can help search, retrieve, access, and handle the object later on. There are various types of metadata available, of which we will touch upon three more prominently used ones:
- Descriptive: This provides descriptive information about the data which will be helpful for discovery and identification of the file or object. For example, the name of the file, author, keywords (used for tagging and searching), etc.
- Structural: This provides information on how the data is structured and put together. For example, a PDF file of a storybook can have pages organized as chapters and include a table of contents.
- Administrative: This includes information such as type of file, creation date, access permission, etc. Administrative metadata has more sub-types for further data classification including technical, source, intellectual property rights and digital provenance.
Where is Metadata Stored and Maintained?
Metadata can either live in a database (metadata repository) separated from the actual data payload or along with the content itself.
In the file storage world, metadata is typically virtualized and abstracted from the actual data and stored in a separate central repository. When a software-defined file storage solution, such as DataCore vFilO, aggregates disparate file shares and NAS systems into a unified global namespace, metadata can be used to centrally manage file access, availability, durability, compliance, placement, and protection. Without having to change the hierarchical storage structure of the actual file, vFilO can leverage the metadata to execute data services in accordance with business and IT requirements. AI- and ML-driven policies track changes in metadata attributes to automate file management actions.
In the object storage world, metadata generated by applications and users is either stored in a separate NoSQL database (like Casandra) or stored with the data payload. Software-defined object storage falls into the second category of keeping metadata alongside the object. This makes data more portable and reduces additional database administration activities. DataCore Swarm uses this metadata for searching, indexing, organizing, classifying, and performing other data governance operations.
Benefits of Metadata-Driven Management in File and Object Storage
Using a centralized metadata management architecture in file and/or object storage environments yields many benefits.
Faster File Search and Content Discovery
Particulars about all the data are stored in one place which makes file access easier regardless of where users are connecting from and where files are stored. As long as the managed storage locations are part of a unified global namespace, disparate file servers, object storage or S3 buckets need not be separately scanned, which results in faster search operations and content discovery.
Streamlined Organization and Retention of Data
Metadata management helps index, classify, and organize data across distributed storage locations which makes it easy to manage global data from a single virtual catalog. Interoperability and data exchange across different storage systems, sites, and organizational departments managed under one global namespace are easily possible while maintaining location transparency and hardware independence. When detailed metadata is created, it aids in maintaining clarity of data lineage for long-term data archival and preservation.
Storage Capacity Optimization
Because metadata serves as a centralized single source of truth about the actual data, sharing and reuse of datasets across different departments or users is possible, thereby avoiding the need to create multiple copies of the same dataset and freeing storage space. Metadata helps optimize capacity through data reuse and redundancy elimination.
Efficient Data Governance
By centrally monitoring metadata content and analyzing changes to metadata, storage administrators can automate data placement to meet cost, performance, capacity, availability, durability, and compliance objectives. For example,
- Frequently accessed data can be stored on primary storage and inactive data can be moved to cost effective object storage or the cloud.
- Duplicate copies of data can be created and stored in a specific location.
- Specific data types can be encrypted and protected.
As mentioned earlier, AI and ML capabilities in a software-defined storage solution can be leveraged for unified data and metadata management.
Audit Trail for Compliance and Risk Profiling
When detailed metadata information about files and objects are created and changes logged, it serves as an audit trail for regulatory compliance, helping analysts track impact on data integrity and policy violations. This also helps detect potential security risks as unauthorized access and file tamper events are revealed.
Driving Down IT Cost Overheads
Long-term stewardship and maintenance of data is a complex and expensive affair for IT Ops and data management teams. Metadata management simplifies this by storing properties about the data which can be used to perform informed actions to govern how data is stored, accessed, and protected and thereby reducing storage and management costs.
Contact DataCore today learn about our software-defined storage solutions that help you manage and administer metadata across your distributed file and object storage environments. Benefit from metadata-driven autonomic data services that help improve storage efficiency and performance, optimize capacity, and reduce IT costs.