ER/Studio Data Architect vs. Informatica Cloud Data Governance

Data Architect is well suited at organizations of all sizes. It is never too early or unnecessary to enforce proper modelling and design standards on data solutions, and this tool will help that greatly by providing an industry leading data modelling tool, ability to import ETL mappings for data lineage, enforcing and managing naming conventions through the naming convention tool, and publishing of data dictionaries through the report publisher. I was successfully able to build models, provide traceability, and document source to target with lineage throughout for both the business (by providing business definitions in the descriptions), and technical teams (by documenting ETL instructions in text fields) along with field level mapping (by creating "Attachments" representing data sources, tables, and fields) providing easy search capabilities using business friendly terms

Incentivized

The Informatics vision is already determined and with the relationships already configured, or that plasters any new type of vision or relationship between the Assets. As a result, a pedigree diagram is poor and limited with the availability of information on the screen or in reports for consultation and decision making. It has an approval and maintenance workflow that is also limited to assets already made available only by Informática. It will not be possible to see the connection of a technical, functional, and documentary line in a single flow. It allows the registration of all data referring to a DPIA and LIA, but it does not generate a report that allows the aggregation of this set of information in a single place. The tool makes information available to support a decision regarding the DPIA and LIA, but it does not make it available in a unified way as in a report.

Incentivized

• ER/Studio has the ability to provide consistent field names and data types through domains, which are templates. This provides a way to have consistent naming of common fields, like CreatedBy and the data types for the fields. They also have the ability to change all the fields that use that domain to a different data type.
• ER/Studio provides the ability to create custom macros. These macros can be used to apply everything from standard fields based on domains to naming all constraints and indexes. I've also used a macro that comes with ER/Studio to spell check field and table names.
• My favorite feature is the ability to compare your data model to databases for deployments of changes, and to other data models.

Incentivized

• Data Catalog
• Integration with Different Databases.
• Relationship between data and trading rules and trading terms.

Incentivized

• ER\Studio licensing can be cumbersome and upgrading from one version to another usually takes several phone calls and emails to the licensing group to get the update installed and running.
• The repository can be slow when the model count gets larger. By large I mean 20 to 30 models.
• A nice feature that I would like to see is table comments be displayed on the model along with the attributes. Currently you have to choose between the two.

Incentivized

• High Complexity, requires training.
• As it does not allow customization in relationships such as information separately in visual form and even in other tools of the Informatics group such as EDC.
• Navigation is complex.

Incentivized

I can call or email support and both get quick turn around. The only issue is they are on the west coast (US) and have a west coast work schedule and I'm on the East coast.

Incentivized

ER/Studio is the most mature, reach in features and quality and therefore useful. Unfortunately, it lacks compatibility with AWS Redshift.

Incentivized

Overall experience with Axon is average and it is a very manual product. Axon is a very good tool for data governance. User-friendly interface and is integrated with multiple systems.

Incentivized

• ER/Studio has had a positive impact on my project as we can develop the data model and have a clear understanding of business needs before we continue with the development phase.

Incentivized

• Negative impact: high training demand
• Negative impact: high cost of infrastructure
• Negative impact: does not meet privacy management
• Positive impact: very good support
• Positive impact: rapid implementation
• Positive impact: very good data discovery quality

Incentivized