In other terms, meta-data is any information used to aid identification, description, characteristics, location of, access to, data elements and information.

Examples of metadata for the may include terms such as “stock price ”. Business name for a “stock price ” may be referred to as a “sp”. This term may be found in all various business documents (word processing, spreadsheets etc.), business systems etc. This is the crux of Meta data management.

So the question is why is meta-data important? Meta-data serves as a bonding agent that ties various tools and technologies together at an enterprise level. A sound meta-data strategy ensures seamless sharing, exchange and integration of tools and repositories. Developing a meta-data strategy for an enterprise requires co-operation from both technical and business area members in an enterprise.

Technical meta-data is the description of the data needed by various tools to store, manipulate, or move data. These tools include relational databases, application development tools, database query tools, data modelling tools, data extraction tools, online analytical processing (OLAP) tools, and data mining tools. Technical meta-data thus provides the description of the data in an IT infrastructure.

Business meta-data is the description of the data needed by business users to understand the business context and meaning of the data.  Business meta-data defines where the data came from, who owns it and how it gets transformed.
 

Shimo’s Metadata Management strategy commences with developing a metadata management strategy.  According to Manish Malhotra, who is a Sr. Metadata Architect/Meta-data Solution Project Manager (PMP) presently working at a leading financial institute in McLean VA., USA, to have an effective meta-data strategy some essential building blocks include:

1. Identify the technical members most knowledgeable about the data
2. Identify the business area members most knowledgeable about the business data and business processes
3. Have business users identify the data stewards and data advocates for data and processes
4. Determine sources of record for data within an enterprise
5. Determine the usage of meta-data
6. Identify all sources of meta-data including data models, rose models, CASE tools, silo repositories, data dictionaries, glossaries, third party dictionaries, business rules, data mapping documents, business process mappings, data flow diagrams, corporate abbreviations, excel spreadsheets, catalogs etc.
7. Determine the overall architecture for meta-data storage. A meta-data storage architecture defines an organizations overall strategy for meta-data storage and retrieval of meta-data. A centralized repository pulls in all the meta-data in one location, a distributed architecture creates many small focused repositories and a hybrid architecture combines the two for best results
8. Determine integration points and processes necessary to consolidate and integrate the meta-data
9. Determine meta-data reporting and dissemination strategies
10. Evaluate full-life cycle meta-data management tools
11. Standardize and document meta-data sourcing processes
12. Determine how to keep the meta-data up-to-date. This has always been a challenge in organizations. It is important to keep the meta-data refreshed as obsolete or stale metadata can result in wrong decision making
13. Standardize and document the meta-data change management process and procedures
14. Define meta-data security needs
15. Define components of the meta model
16. Identify issues and constraints
17. Form a meta-data steering committee
18. Discuss and confirm the meta-data management strategy with the management

He continues to issue the following caveat: “Remember an enterprise meta-data solution cannot be done with a big bang approach. The meta-data solution project needs to be divided into smaller more manageable chunks. An advantage of delivering a meta-data solution in a phased approach is an early buy-in from the business areas and project champions”. Shimo's product partner for Metadata management is the Data Advantage Group based in San Francisco, Carlifornia.