Meta data refers to the information about data. It provides context and details about the data, allowing users to understand and interpret it effectively. It can be seen as data about data, providing information about the structure, format, content, and relationships of the actual data.

Meta data is essential for managing and organizing large amounts of data, as it helps in data discovery, integration, and analysis. It provides valuable insights into the data and helps in making informed decisions. Here are some key points about meta data:

1. Definition and Purpose:
- Meta data is defined as the information that describes the characteristics, properties, and attributes of data.
- Its purpose is to provide context and meaning to the data, enabling users to understand and use it effectively.

2. Types of Meta Data:
- Structural Meta Data: Describes the organization and structure of data, including tables, columns, and relationships in a database.
- Descriptive Meta Data: Provides information about the content and characteristics of the data, such as file names, titles, descriptions, and keywords.
- Administrative Meta Data: Includes information about data ownership, access rights, security, and data management policies.
- Statistical Meta Data: Contains statistical information about the data, such as the mean, median, and standard deviation.

3. Importance of Meta Data:
- Data Discovery: Meta data helps users find relevant data by providing information about its source, format, and content.
- Data Integration: Meta data enables the integration of data from multiple sources by providing information about data mappings and transformations.
- Data Quality: Meta data helps in assessing the quality of data by providing information about its accuracy, completeness, and consistency.
- Data Governance: Meta data plays a crucial role in data governance initiatives by providing information about data lineage, ownership, and compliance.

4. Examples of Meta Data:
- Database Schema: Describes the structure of a database, including tables, columns, data types, and relationships.
- Data Dictionary: Provides definitions and descriptions of data elements, including their names, data types, and allowed values.
- Data Lineage: Shows the origin and transformation history of data, allowing users to track and understand its journey.
- Business Glossary: Contains business terms and definitions, helping users understand the meaning and context of data.

In conclusion, meta data is the information about data that provides context, structure, and meaning to the actual data. It is essential for data management, discovery, integration, and analysis, enabling users to effectively understand and utilize the data.