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Data dictionary tools for Netezza
List of tools that enable design and building of data dictionaries .
Data Dictionary is a set of important information about data used within an organization (metadata). This information includes names, definitions, and attributes about data, owners, and creators of assets. Data Dictionary tools provide insights into meaning and purposes of data elements. They add useful aliases about the scope and characteristics of data elements, as well as the rules for their usage and application.
ER/Studio
ER/Studio Data Architect helps to easily reverse- and forward-engineer, compare and merge, and visually document data assets across multiple platforms and data sources. The Data Dictionary is a feature of ER/Studio that allows the sharing of many objects including domains, defaults, rules, and attachments. Using the Data Dictionary you can enforce standards, promote reuse, and build a common framework across all models.
| Desktop/Cloud: | Desktop |
|---|---|
| ER Diagram: |
|
| Export: | HTML |
| Metadata stored in: | Documentation repository/file |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | Data modeler, Entity relation diagram, Model sharing |
| Runs on: (for desktop): | Windows |
Alation Data Catalog
Alation data dictionary defines and describes technical data terms. Data terms could be database schemas, tables, or columns. Once connected to data sources, Alation automatically indexes data and populates catalog pages. For example, a column catalog page shows the technical column name, a business title name, the data type, and popularity. Additional context can be added to the data dictionary, for shared understanding across the organization.
| Desktop/Cloud: | Cloud |
|---|---|
| ER Diagram: |
|
| Export: | MS Excel |
| Metadata stored in: | - |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | ML auto-suggested business glossary terms |
| Runs on: (for desktop): | - |
Key functionality of Data Dictionary tools is to give users the ability to document data. Moreover, very important is the possibility to create a collection of multiple repositories, based on different system engines. For a better understanding of the data, some tools allow visualization of the data structure using ERD (Entity-Relationship Diagrams).
From the organization's point of view, a community module within a data dictionary tool proves to be useful. It facilitates the proper information flow, as well as provides sharing opinions on specific objects among the members of an organization.
Nowadays, data discovery and understanding becomes crucial for proper organization performance. There are many benefits to using Data Dictionaries, such as:
• helps avoid data inconsistencies problems,
• it allows introducing unified nomenclature used in the project,
• Make data searchable, and understandable,
• Create a single source of truth about the data from different repositories,
The prepared list includes simple, open-source data dictionaries as well as more advanced software.