BigID vs SAP Data Hub comparison

"The data classification offered by the tool can help companies improve their security strategy"

"I like BigID's in-depth discovery and scanning capabilities, especially for unstructured data. This feature is a standout compared to competitors. The tool's data classification capabilities are impressive. It offers custom classifiers and a blend of regular exploration and artificial intelligence, making it a next-generation solution. This enhances data security, and its security posture management is straightforward and user-friendly."

"BigID integrates well with our other products."

"BigID has one of the best technical support teams."

"BigID's scanning feature is its most valuable component."

"Data classification is highly effective due to its automatic capabilities."

"BigID is more advanced than Microsoft Purview when it comes to machine learning and AI development tools."

"The most valuable feature of BigID is its large number of classifiers, which allow us to scan for specific data such as SSN numbers."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"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 another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"The challenge we encountered was with data connection across multiple databases. We struggled with configuring the data connection successfully. However, with the assistance of dynamic teams, we resolved this issue."

"The tool currently lacks security features."

"Improvement could be made in data consent management and data privacy impact assessment."

"I want them to focus on data mapping, assessment, automation workflow, and privacy incident management."

"One concern I have with BigID is regarding certain scans, like the multi-scan. The issue is that we can stop and retrieve these scans, but once they start, they go through an enumeration process."

"BigID is making some forays into the GRC space, and that's a natural progression. I'd like to see that improve so that data governance is better, data risk is identified, and the ability to control and mitigate it."

"BigID is expensive. I prefer McAfee."

"I want them to focus on data mapping, assessment, automation workflow, and privacy incident management. The privacy tools have not been widely used, and they have not invested much in privacy code privacy tools."

"The company has everything offshore."

"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"The pricing depends. If you have thousands of data sources to connect and manage, and you struggled with an MDM package in the past, you'll find BigID valuable and even cheap. But if you're a small business, it's probably not the right tool for you."

"The solution is not licensed per user but rather based on capacity. For instance, organizations with large amounts of data, such as 50 GB or more, are the ones that typically qualify for BigID."

"I think that BigID's pricing is very reasonable."

"The product is expensive, but so are all competitor tools"

"The solution is expensive."

"The Cloud is very expensive, but SAP HANA previous service is okay."