SAP Master Data Governance Reviews

My technical expertise allows me to provide end-to-end implementation support, including managing interfaces between applications.

We use it for data consolidation, DQM (data quality management), data validation, UI application, and more within the SAP application landscape.

One of the key benefits comes from the data quality features. In large-scale industries with significant amounts of master data, avoiding duplication is crucial. Duplicate entries can negatively impact business operations.

Data quality features also ensure data consistency. By connecting to a central system, we establish a single source of truth. Then, we can reliably distribute this accurate data across all connected systems.

For example, if a company has numerous internal systems, we can maintain all the data in one central location and distribute it seamlessly and securely. Data consistency is a major advantage.

Moreover, we can configure SAP Master Data Governance to establish data accuracy rules.

With SAP Master Data Governance, we can maintain workflows with multiple approvals. Previously, we needed approval from different teams and, finally, from our coding team. 

Now, we can manage a multiple-step approval process. We can even assign a single master data record to two people for parallel approval. This flexibility in workflow management allows us to streamline the upload process and manage tasks efficiently within SAP MDG.

So, the workflow management in SAP Master Data Governance benefited your organization.

SAP is a closed tool. Integrating with it requires a lot of effort and money. It is also very expensive and not flexible. 

If you want to make a change, it takes 30-60 working days compared to others, where you can do things in one hour.

It is very stable. RiverFront is less stable.

We use the platform for centralizing and streamlining the management of an organization's master data.

With MDG, we have established an efficient process for easily managing country-specific data. At an enterprise level, it has proven valuable in imposing control over master data changes across different countries.

SAP Master Data Governance functions as a standard data model, offering users both an inbuilt and custom data model. Regardless of the type of data or attributes involved, users can add, delete, and decompose fields and attributes based on the specific data model, whether it pertains to suppliers, customers, finance, or master data. Once the governance process is completed, the data can be seamlessly moved to the target system, showcasing one of the key advantages of SAP Master Data Governance.

SAP Master Data Governance is a very good product, allowing users to identify duplicate records easily. In the solution, you can store records as golden records and monitor data quality. For consolidation purposes, the solution allows you to use the bulk data.

In my experience with SAP Master Data Governance, I have primarily dealt with the custom data model, involving the addition of new fields under BP categories or vendor sections. When a custom field is added at the product's UI level, data retrieval from the third-party system becomes possible. The SAP Master Data Governance API operates in the background, incorporating the workflow. Once the workflow is triggered, the change request linked to the BP number is updated at the table level, as per the custom data table number requirement, and then the details are pushed to the target system. The aforementioned process stands as an advantage of SAP Master Data Governance.

I've got clients from multiple industries who use the solution across the industries, including consumer products, FMCG, the high-tech industry, services clients, and resources. We use the solution for central finance-related clients, the customer services department, sales and distribution, and the manufacturing process.

I like how the solution integrates with other SAP tools and third-party solutions.

The standard SAP MDG solution is for business partners, materials, and financial master data. For retail, you can manage products and materials through Article Master Data.  

The validation and derivation rules are one of the advantages for maintaining data quality. We can also build approval processes and governance within the system. These are the two main advantages.

Integration:

We can use both inbound and outbound interfaces for integration. SAP MDG has built-in integration capabilities with multiple systems/streams. We can also create custom interfaces if needed, for example, with Adobe or other upstream or downstream systems. It's reasonably good.

When I think about data integration, it is very smooth and simple to upload or download data to and from SAP MDG. There are multiple processes in MDG for this.

The solution is for creating and managing a Master Data across an organization. We implement the solution for customers to streamline the creation, inundation, and dilution of Master Data across domains, such as financial masters.

The main use case is to increase data quality by starting to create the right data with the right people and distribute it to the consuming systems. We want to enable users to be able to identify the golden record for all of a particular Master Data set. For example, to prevent a unique customer from getting mixed up in the use cases. Bringing in data standardization, to prevent users from spending too much time on the creation of the Master Data. This can be done via the implementation of business tools by the customer or sometimes the company itself, preventing the overload of data. Lastly, data enrichment can also be achieved.

Our organization was able to gain more trusted data. For example, if there is a historical record of, five materials but on data profiling, we found that 20% of it cannot be used. With analytics, they can rely on the record of the remaining 80% of the data and it can be used as needed.

The crude operation, creating, reading, updating, and deleting are more streamlined. 

There are data stewards who can take complete control of the information and the creation of the data which goes through them. They are the single point of contact to ask if a particular record is correct or not.

I work on the functional side of this solution. From an operations point of view, that relates to critical attributions, rules, the way in which data quality improves, and the way the tool governs activities with respect to different business stakeholders. I work for a global analytics and consulting company. We are end users and I'm a senior manager.

This is a high-quality solution and provides for proper governance. It's also user-friendly, and we're able to get a lot of customized reports and personalized data. It enables quality output so there's no need to have different applications to check data quality.