Adverity vs. SAP Data Intelligence

Adverity is particularly useful if there is a large range of data sets that you want to combine to get an 'overall' view. Previously we had used Google Analytics, but found that this was too useful for our big client accounts that we were working on. So I think that if there is an individual who is responsible for analytics or data, and also a paid media team then this is a tool which is essential. For companies that have limited activity then I think this tool could potentially over-complicate for less reward.

Incentivized

If you have an SAP products ecosystem in your IT landscape, it becomes a no-brainer to go ahead with an SAP Data Intelligence product for your data orchestration, data management, and advanced data analytics needs, such as data preparation for your AI/ML processes. It provides a seamless integration with other SAP products.

Incentivized

• User-friendly report setup and ingestion
• Easy integration with multiple data endpoints, making it easy for users to drive value
• Incredible customer support, allowing users (regardless of technical background) to act like power-users

Incentivized

• It integrates well with our current ecosystem of SAP products, like HANA.
• It provides end-to-end machine learning operations, with tools for the complete model life cycle.
• It has a simple user interface for novice users, with complex tools also available for power users.
• It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
• It can run in the cloud, no on-premise software management needed.
• Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
• SAP is very actively developing and improving it.

Incentivized

• I think it would have been more user friendly if there was more labelling capabilities, so that when you are sharing the dashboard they would explain what the data is - rather than depending on someone knowing how to use the dashboards or being there to explain it.
• Our teams found that some of the scheduling functionality could be a little big buggy, so this was something that needed extra care and attention, so therefore may be an area that needs to be improved (unless it was just our account and usage).

Incentivized

• Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.

Incentivized

Allow collaborations among various personas
with insights as ratings and comments on the
datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence

Incentivized

I think the troubleshooting process might be streamlined with improved error recording and tracing. A lot of information about issues and how to fix them is hidden away in the Kubernetes pods themselves. I'm not sure whether SAP Data Intelligence can fix this problem it may be connected to Kubernetes's design, in which case fixing it could need modifications inside Kubernetes itself.

Incentivized

Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,

Incentivized

Frankly, the service, UI, and ease-of-use for Adverity made it a no brainer compared to competiton.

Incentivized

One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.

Incentivized

• This tool has allowed us to be able to see areas for opportunities, when all of the data has been combined
• We were also able to better prioritise actions and where to focus our attention, when we had one view where all of the data was together. This allowed us to deliver better results for our clients, and also have a clearer roadmap of activity

Incentivized

• Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
• Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
• It runs multiple ML models which enhances flexibility when managing data.

Incentivized