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Adaptive Metadata Manager™
(MM) is a web-based repository that is designed for use in metadata
management and provides the capability to capture the data definitions
from data modeling tools, relational databases, XML Schemas, COBOL
copybooks, and other sources, and the detail of the transformations
that occurred – for example loaded from definitions in extract-transform-load
(ETL) tools. The metadata captured from all these sources is managed
in a role-based environment that provides each metadata role (data
modeler, report developer, business user, data steward …) with
exactly the capabilities and access privileges that are appropriate
for their needs. Adaptive MM facilitates governance, compliance and
transparency of the metadata management process. It is used to:
- Manage a large amount of disparate technical and business metadata,
providing different end-to-end views to a variety of user roles
- Collaborate on updating and managing the information, facilitate
re-use, and manage change, especially through future planning of
different scenarios and timescales
- Construct end-to-end visualizations of the information flows from
any point (e.g. origin, final report, any intermediate point), in
a form suitable for both business and technical users
Metadata Repository – Why is it needed?
‘Metadata Management’ is the process of
managing an organization’s data assets in the context of how
they are used by systems and business processes. This enables effective
changes to the data assets to be made and the full impact of changes
to be understood. Organizations realize the need for a metadata repository
when they have reached the limit of process and data modeling tools
and/or home-grown MS Access databases and spreadsheets and recognize
the need for an open, enterprise scalable repository. Adaptive MM
fulfills the needs for an enterprise-scale metadata repository:
- To manage a large amount of disparate technical
and business metadata, providing different end-to-end views
to a variety of user roles
- To collaborate on updating and managing the information,
facilitate re-use, and manage change, especially
through future planning of different scenarios and timescales
- To construct end-to-end visualizations of the information
flows from any point (e.g. origin, final report, any intermediate
point), in a form suitable for both business and technical users
- By Business Analysts looking for the "single point
of truth" including the necessary collaboration, workflow,
and governance to ensure their metadata is reliable and maintained
in a proper fashion
- To support initiatives such as SOA,
and regulatory compliance that require a comprehensive,
accurate and accessible repository for managing enterprise metadata
in the context of business and technical requirements
- To spot redundancy or use of inappropriate versions
of the information
- To assign value to information by seeing how
it contributes to the business. This allows further decisions to
be made with respect to contingency/risk, accuracy, timeliness and
cost of the information.
- Enforce data ownership and accountability to
ensure the integrity and quality of the data
How Adaptive Metadata Manager works
Harvesting & Integration
Adaptive MM provides a wide array of integration options
with most popular database management systems, data modeling and system
modeling tools – or even home-grown systems based on MS Excel
or MS Access. It uses metamodeling standards to import, transform
and export metadata with tools and metadata sources. Adaptive MM also
uses a transformation technology based on the Metaintegration Model
Bridge to import information from many 3rd party tools and data sources
using their native format. Some of the tools and data sources supported
include:
- Relational database schemas
- XML Schemas
- COBOL Copybook files
- Data Modeling Tools
- Any UML® or CWM® compliant tool
- Business Intelligence tools
- IDEF1X Tools
- OLAP tools
Adaptive MM can capture the data transformations that
take place – for example, via data marts or data warehouses
and through to user screens and reports through its market-leading
support for the Common Warehouse Metamodel (CWM) standard from OMG®.
Support for this standard also enables mapping from business (logical)
definitions through to the technical database definitions, so that
understanding of flows can be translated back to business terms for
business users.
Automated Workflow
Adaptive MM provides an automated and extensible workflow
which manages the flow of changes through the different metadata roles,
and controls visibility to changes until they are approved. The workflow
is controlled by item type specific state transition models that define
lifecycle states, events and transitions.
Collaboration
Adaptive MM provides a complete collaborative environment
for both technical and business people to work together to identify
and address issues:
- Threaded discussion groups can be established
and run on any metadata element
- Recorded assessments for any metadata element
for review and auditing purposes
- Event Subscriptions and automatic notification
using corporate email system
Versioning and Comparative Analysis
Adaptive MM Repository provides versioning and configuration
management capabilities that track changes at the fine-grained object
level. Workspace configurations can be defined at the level of granularity
required by the user and full support for version branching and merging
is provided. A flexible context and release mechanism controls which
versions are accessed, without the user needing to be aware of versioning.
This enables users to work on specific change tasks within a workspace
that will not be visible to the general users until the task is completed,
approved and merged into the main branch.
Data models or schemas that have multiple sources can
be imported into different workspaces and then comparisons can be
performed across the workspaces to understand what the differences
are. This powerful comparative analysis capability is essential for
managing metadata changes in a complex real-world environment.
Analysis and Reporting
Adaptive MM provides dynamic, on demand display of reports
in the web browser window to support analysis and validation. In addition,
information can be extracted from the repository and populated into
a simplified set of relational tables. These tables can be accessed
through a direct SQL interface or 3rd party reporting tools such as
Business Objects, MS Excel and the Eclipse-based Business Intelligence
and Reporting Tools (BIRT) to produce custom reports. This capability
can also be used as a “metadata mart” by performing multiple
extracts for different groups, at convenient (off peak) times, to
populate their own database (metadata mart), on which each group can
use their reporting tool of choice.
Feature Summary
- Role-based user interface including navigation
maps, views, item types and classification schemas tailored to the
needs of each metadata role
- Explicit and extensible data stewardship and stakeholder
roles, and enforcement of access control policies
- Automated workflow for change approval enforces
metadata policies and governance
- Harvesting capabilities enable automatic capture
and integration of logical and physical data models from data modeling
tools, database schemes from databases, XML Schemas and data definitions
from other tools and sources
- Manage logical and physical data models and definitions in an
enterprise-scale repository supporting versioning
and configuration management
- Capture complete data lineage including: ETL
tools, adapters, application-to-application, services, file transfer,
reports, and manual data entry/review
- Dynamic graphical visualization of complex data
lineage relationships to quickly see the big picture as
well as focus on specific details
- Link data elements to software – including
data access and applications, database deployment, processes, and
KPIs (where the data is part of a measure)
- Capture data quality – rules, targets and
actuals
Benefits
- A comprehensive understanding of metadata lineage,
using a powerful view mechanism to allow aggregated visualization
of the lineage of data across disparate systems, applications, databases
and tools
- Discover and manage “collisions”
- inconsistencies of metadata from multiple data sources
- Traceability from taxonomies of business concepts
and terms to logical data models, and physical data schemas
- Workflows to automate the lifecycle of metadata
to engage the appropriate data stewards and stakeholders at each
point
- Enable business users to understand what the
data sources are for information in end user reports
- Understand the impact of changing a data element
- what other data elements, reports and queries are affected
- Identify opportunities for reuse of data assets
through sophisticated search mechanisms
and queries that leverage logical traceability and data
lineage relationships and dynamic result filtering based on classification,
ownership, modification date and lifecycle state
- Effective management of purchased data feeds
by discovering what information is needed, how it is used, and where
there are redundancies in data sources
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