Types of Metadata
There are two distinct classes of metadata:
- Structural Metadata - used to describe the
structure of computer systems such as tables, columns and indexes.
- Guide Metadata - used to help humans find specific
items and is usually expressed as a set of keywords in a natural
language.
Relational Database Metadata
Each relational database system has its own method for storing
metadata. This may include:
- Tables of all tables in database, their names, sizes and number
of rows in each table.
- Tables of columns in each database, what tables they are used
in, and the type of data stored in each column.
This set of metadata is referred to as the catalog.
The SQL standard specifies a uniform means to access the catalog,
called the INFORMATION_SCHEMA, but not all databases implement it,
such as Oracle databases.
Data Warehouse Metadata
Data warehouse metadata systems may be separated into two sections:
- Back room metadata - are used for Extract,
transform, load functions to get OLTP data into a data warehouse
.
- Front room metadata - used to label screens
and create reports
Types of metadata in a data warehouse include:
- Source system metadata
- Source specifications, such as repositories, and source schemas
- Source descriptive information, such as ownership descriptions,
update frequencies, legal limitations, and access methods
- Process information, such as job schedules and extraction code
- Data staging metadata
- Data acquisition information, such as data transmission scheduling
and results, and file usage
- Dimension table management, such as definitions of dimensions,
and surrogate key assignments
- Transformation and aggregation, such as data enhancement and
mapping, DBMS load scripts, and aggregate definitions
- Audit, job logs and documentation, such as data lineage records,
data transform logs
- DBMS metadata, such as: DBMS system table contents and processing
hints
Business Intelligence Metadata
Business Intelligence metadata describes how data is queried,
filtered, analyzed, and displayed in Business
Intelligence software tools, such as Reporting tools, OLAP tools,
Data Mining tools.
Examples:
OLAP metadata: The descriptions and structures
of Dimensions, Cubes, Measures (Metrics), Hierarchies, Levels, Drill
Paths
Reporting metadata: The descriptions and structures
of Reports, Charts, Queries, DataSets, Filters, Variables, Expressions
Data Mining metadata: The descriptions and structures
of DataSets, Algorithms, Queries
Business Intelligence metadata can be used to understand how corporate
financial reports reported to Wall Street are calculated, how the
revenue, expense and profit are aggregated from individual sales
transactions stored in the data warehouse. A good understanding
of Business Intelligence metadata is required to solve complex problems
such as compliance with corporate governance standards, such as
Sarbanes Oxley (SOX) or Basel II.
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