Data Modeling Reports

From Data Modeling tools, reports can be easily generated for technical and business needs. The reports that have been generated from logical data model and physical data model are called as business reports and technical reports respectively. Most of the data modeling tools provide default reports like subject area reports, entity reports, attribute reports, table reports, column reports, indexing reports, relationship reports etc. The advantage of these reports is, whether they are technical or non-technical, everybody would understand what is going on within the organization.

Other than default reports provided by data modeling tools, a data modeler can also create customized reports as per the needs of an organization. For example, if an expert asks of both logical and physical reports of a particular subject area in one file(e.g in .xls), logical and physical reports can be easily merged and reports can be easily generated accordingly. Data Modeling tools provide the facility of sorting, filtering options and the reports can be exported into file formats like .xls, .doc, .xml etc.

Logical Data Model Report:

Logical Data Model Report describes information about business such as the entity names, attribute names, definitions, business rules, mapping information etc.

Logical Data Model Report Example:

Physical Data Model Report:

Physical Data Model Report describes information such as the ownership of the database, physical characteristics of a database (in oracle, table space, extents, segments, blocks, partitions etc), performance tuning (processors, indexing), table name, column name, data type, relationship between the tables, constraints, abbreviations, derivation rules, glossary, data dictionary, etc., and is used by the technical team.

Physical Data Model Report Example: