Top 8 Data Governance Tools
Collibra GovernanceSAS Data Managementerwin Data Intelligence (DI) for Data GovernanceInformatica AxonSAP Data HubAlation Data CatalogBigIDInfogix Data360 Govern
As far as the functionality of the tool is concerned, it's pretty slick.
Collibra is very good at talking to modern database systems like a normal RDBMS, a DB2, or a SQL server or an Oracle.
The product offers very good flexibility.
In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features.
erwin has tremendous capabilities to map right from the business technologies to the endpoint, such as physical entities and physical attributes, from a lineage standpoint.
The solution allows the complete governance process, starting from the data quality, those definitions, and it can get the data quality in the EDC.
The features that I have found most valuable are, first of all, that it comes as part of this whole bundle of Informatica tools. So if you've been implementing Informatica MDM across a business, you'd often find it comes with it. It's been thrown in as a sweetener. The adoption of it is often the challenge because as part of your MDM project, governance is seen as something beyond the MDM and is often restrictive. So this tool actually, for the first time, when you talk to data governance teams, gives a holistic view of what a data governance team can do with this tool.
Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used an
The features that I have found most valuable are the user experience, the credentialing, and that BigID is user friendly. Additionally, you can deploy to several other Microsoft platforms and you can use it for other things, like a bigger element or a report.
Infogix support stands out in terms of quality and response time, and it is really easy to speak with them by phone or by email.
It is an integrated solution that provides end-to-end capabilities for managing the data. It is very useful for cleaning the data. It also allows us to combine data from on-premises and cloud sources. On this unified data, we can perform some advanced analytics to predict customer behavior and create new products. Its management and governance capabilities are valuable. It provides full tracking of the data flow. It provides customers the full control over the data and the ability to protect the data. It enables us to provide the best service to the customers. We also get great support from Infogix.
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Rony_SklarCommunity Manager at IT Central Station
What are key differences between MDM and Data Governance? What are the practical differences in which each of these solutions is applied?