Thursday, July 30, 2020

Metadata Driven Solutuions

Metadata is data that provides information about other data. Many distinct types of metadata exist, including descriptive metadata, structural metadata, administrative metadata, reference metadata, and statistical metadata.
  • Descriptive metadata is descriptive information about a resource. It is used for discovery and identification. It includes elements such as title, abstract, author, and keywords.
  • Structural metadata is metadata about containers of data and indicates how compound objects are put together, for example, how pages are ordered to form chapters. It describes the types, versions, relationships and other characteristics of digital materials.
  • Administrative metadata is information to help manage a resource, like resource type, permissions, and when and how it was created.
  • Reference metadata is information about the contents and quality of statistical data.
  • Statistical metadata, also called process data, may describe processes that collect, process, or produce statistical data.
Metadata, properly managed, is the powerful tool to make things happen. We can have processes and solutions which are driven by metadata.

In application building process which is metadata driven, instead of building the desired application directly we define the application’s specifications. These specifications are fed to an engine which builds the application for us by using predefined rules.

Instead of building a package to create a dimension, for example, we can provide the dimension description (metadata) to a package generating engine. This engine is then responsible for creating the defined package. Once the package is executed, it will create and maintain the prescribed dimension.

Why is metadata driven so much more efficient than traditional methods?

  • Creating a definition of a process is much faster than creating a process. A metadata driven approach results in building the same asset in less time as compared to traditional methods.
  • Quality standards are enforced. The rules engine becomes the gatekeeper by enforcing best practices.
  • The rules engine becomes a growing knowledge base which all processes benefit from.
  • Easily adapts to change & extension. Simply edit the definition and submit to the engine for a build. Need to inject a custom process? No problem, create a package the old fashioned way.
  • Enables agile data warehousing. Agile becomes possible due to greatly increased speed of development and reduced rework required by change.
The ongoing proliferation of devices joined with the distributed nature of data sources has created an indispensable role for metadata. Metadata provides knowledge such as location of the device and nature of the data, which facilitates integration of data regardless of its origin or structure.

Enterprises are incorporating data quality and data governance functions as part of data integration flows. Embedding these processes in the integration pipeline necessitates sharing of metadata between the integration tools, and the quality and governance tools.

Metadata also facilitates performance optimization in integration scenarios by providing information on the characteristics of underlying sources in support of dynamic optimization strategies.

In content management, folder-less approach allows you to search for and access files however you want – by client, project type, date, status or other criteria. It's completely dynamic, enabling you organize and display information how you need it, without the limitations of antiquated, static folder structure.

All you do is save to files and tag the file with the properties you need, and you are done. No more wandering through complex, hard-to-navigate folder structures, trying to guess where to save a file. With metadata you just quickly describe what it is you are looking for.

Metadata management software provides context and information for data assets stored across the enterprise. ... Metadata management tools include data catalogs, or assemblages of data organized into datasets (e.g. searchable tables or other arrangements, facilitating exploration).

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